We live in the 21st century. The world around us is constantly changing and data has become unquestionably the most valuable asset. Data is essentially the information that is stored or transmitted electronically. Everything we see on computers and the web from YouTube to Google searches to emails to Excel sheets is a form of data. It is essential for everyone be it individuals, businesses, or governments and the demand for data is rising exponentially. This article is a guide to data analytics in project management. Must read to gain in-depth knowledge about it.
Most of the Business decisions are taken based on data and we just can’t get enough of it. It is widely believed that future wars will be fought over data and with the help of data, but raw data is like raw food, it’s not of much use unless we perform some actions on it.
In itself is just a set of numbers or words and to make sense of it we need to analyze and evaluate it so that raw data becomes useful and actionable information and this is done with the help of data analytics.
Data analytics is the process of collecting, evaluating, processing, and analyzing data to find correlations, trends, and insights that can be translated into informed decisions.
It is important for organizations to understand the effectiveness of their past decisions in terms of measurable or quantifiable indicators as well as help them to understand consumer behavior in a better manner. It essentially provides scientific backing behind a decision. Data Analytics usually involves the following steps:
Define the Question-Defining the questions means deciding on what exactly one wants to know. It is very important as it gives direction to the whole process of data analytics.
Data Collection– Data collection involves gathering data from online platforms, online surveys, Excel sheets, and databases. It is necessary to make sure that data is relevant in relation to the questions the organization aims to explore with the help of data analysis as the kind of data used will have a direct bearing on the conclusions.
Cleaning the Data-Cleaning of data is making data accurate and free from errors. This process involves looking for missing values, removing inconsistent values, getting rid of duplicate values, identifying superfluous data, and deleting it. The Cleaning of data is essential if want to get credible results.
Analyse Data– This step involves the use of various techniques and statistical tools to explore and understand the data in a more cohesive manner.
Data Visualization– After analyzing the data, the data is presented in visual forms such as pie charts, bar graphs, and dashboards. Data visualization helps in sharing large amounts of complex data into easily interpretable information.
Data Interpretation and Decision Making-Data Interpretation involves reviewing the data. It helps in understanding patterns, trends, and inter-relation between different variables so that concrete conclusions can be drawn from the data and effective decisions can be taken.
Before we understand the use of data analytics in project management, let us first understand what is meant by project management. Project management is a process through which the project goals are achieved with the available resources.
It involves detailed planning and effective allocation of company resources with the goal of solving the problem within the given deadline. Project Management is done in the following steps.
Project Definition– It defines the scope of the project and determines its objectives and limitations. The project definition should meet the expectations of all the stakeholders such as the client, the company, and the employees.
Project Planning– it involves a wide range of activities such as budgeting, scheduling, organizing, and distributing work. The roles of different individuals are defined and milestones are set.
Resource Management– It involves allocating and managing resources to achieve objectives set in the project definition. It is a very important part of project management as the resources are scarce most of the time and there is a need to make optimum utilization of resources to meet project management goals.
Risk Management– Risk Management deals with figuring out and analyzing the potential risks associated with the project and also providing a roadmap to deal with such risks. There are different types of risks associated with a project such as financial risks, operational risks, or market risks. Risk management helps in developing strategies that will reduce as well as hedge the risks the project is exposed to.
Project Execution– Project execution is the most important step in the project management process. It involves rolling out the project. It involves coordinating the team, monitoring progress, and coming up with solutions to meet the project objectives. Effective planning can help in smooth project execution.
Communication and Stakeholder Management– Communication is the key to the successful implementation of any project. It is necessary to have an unhindered and clear flow of information to team members so that they understand their roles and execute the project properly. Clients should also get timely information about the progress of the project and milestones achieved so that they can suggest changes if they require any.
Quality Management– Quality Management deals with maintaining standards in terms of project delivery. The quality could be assessed in the form of certain predefined criteria and regular quality checks to make sure that the quality of the project is not compromised.
Project Closure-It is associated with the completion of the project which usually aligns with achieving objectives that are set out in the project definition. It also involves the evaluation of problems that were faced during the implementation of the project.
The project Management process involves interpreting and analyzing data for different objectives such as risk management, project execution, and Quality Management.
Data Analytics can be used to break down complex data with the help of charts and graphs and uncover new patterns that can help in understanding the behavior of different variables thus data analytics becomes the bedrock of project management. Data Analytics is used in project management in the following ways:
Visualization-Data Analytics is of great use to project managers as it helps in simplifying complex and large amounts of data into easily understandable visual representations. It becomes easier to identify patterns with the help of visual representation as compared to identifying them on data tables.
Different types of visual representation tools are used for different types of data for example, Bar charts are used for discrete values such as expenditure by customers whereas line charts are usually used for showing data over a period of time.
Performance Monitoring-Data Analytics plays a key role in enabling the stakeholders to monitor the performance of the project. Data analytics helps in figuring out the key variables that are essential in meeting the goals set in terms of Key Performance Indicators (KPIs) so the performance can be measured in a quantifiable manner and corrective action can be taken in the areas the performance is lagging.
Risk Management– Data Analytics has a special role when it comes to assessing and mitigating risks. Data analytics can be used for risk identification, risk assessment, risk mitigation, and risk monitoring by analyzing large sets of historical data and identifying patterns that are leading to an increase in risks.
For example, In the financial industry Income data of past customers could be analyzed to identify the customers who could default on their loans.
Check here the top-ranked data analytics courses to get a high-paying job:
Resource Optimization– Data Analytics plays a key part in resource optimization as resource optimization is one of the most important goals for any project manager. Data Analytics can be used to find out the areas where resources are not fully utilized and any bottlenecks that are occurring such data can be used for making more efficient policies.
It can also be used for predicting demand so that inventory and working capital are managed accordingly. For example, Bar charts are used for representing discrete values whereas.
Forecasting and Planning-Forecasting is one area where data analytics plays a key role with the use of tools such as Time series analysis. Time series analysis to find out patterns in historical data about sales or inventory and thus make informed decisions. Machine learning algorithms could be used to identify patterns in data and identifying such patterns will provide vital information in planning.
Tracking Progress– Data analytics is very important in tracking the progress of the project by using the data analytics to identify the main milestones and Key performance indicators (KPIs), Continuous tracking of these milestones will give insights that could be vital inputs in taking corrective action if required.
Stakeholder Management– For any type of project there are different kinds of stakeholders such as customers/clients, the company’s management, and the team members.
Data Analytics makes it easier for each one of them to track timely developments in the project and take a logical course of action. For Example, Data regarding the performance of team members could be analyzed and tasks could be given according to their efficiency in different areas.
Prescriptive Analysis-Descriptive analysis uses past data to identify recurring patterns and general trends whereas predictive analysis is used to predict future performance with the help of data.
Prescriptive analysis uses both descriptive and predictive analysis and goes beyond just finding trends and aims to suggest the best course of action for the project manager thus making the decision-making process a lot less complex.
Managing Project Portfolios-Data Analytics can be very useful for project managers when they are dealing with multiple projects at the same time. Data analytics will make it easier for the managers to identify the projects that are lagging behind in deliverables so a project manager can divert more resources and time to such projects analyzing data from the different projects will also help in identifying trends and the kinds of project that require any special attention and resources.
Project Integration across various disciplines– Data Analytics could guide project managers with the help of Project integration as most of the modern-day projects are not department-specific and require the expertise of various departments. By integrating data from various departments, a project manager can get a more holistic view of the project and make more efficient decisions.
Quality Control-Use of Data Analytics is of great significance when it comes to Quality control as providing top-notch quality is the main priority for every project manager. Data Analytics could be used to identify key variables that could measure quality and could be used to track any improvement or decline in quality over time and take necessary steps to address any issues related to the decline in quality thereby optimizing the quality control process.
Measuring the Success of the Project-Data analytics provide clear quantifiable answers about the success of the project. Data indicators related to costs, logistics, and different sub-areas could be analyzed furthermore customer satisfaction levels could also be ascertained with the help of data collected from surveys thus giving the project manager a clear idea about the level of success of the project.
Thus, we can say that data analytics is one of the most integral parts of project management as it plays a key role in a whole array of areas ranging from project planning to measuring customer satisfaction. It will become very difficult for project managers to deliver on project milestones without the use of data analytics in project management. The comprehensive application of data analytics makes it an indispensable resource for project managers.
Tools Used for Data Analytics in Project Management
There are a lot of tools of different kinds that are used for data analytics in project management. Such tools simplify the process of data analytics. Some of the most popular tools for data analytics are-
Spreadsheet Software-Spreadsheet software is one of the widely used and easy-to-understand project management. Software such as Google Sheets, Microsoft Excel, Apache OpenOffice, Apple Numbers, and LibreOffice are a few of the popular tools used for data analytics.
Spreadsheet tools help in breaking down data in the form of pivot charts, bar graphs, and pie charts. It also allows the users to apply different kinds of formulas to data so that they can make more sense of the raw data.
Business Intelligence Tools-Business Intelligence tools play a key role in collecting, analyzing, identifying patterns, and visualizing with the help of data. They also provide interactive Dashboards that make it more convenient for the user to understand and use the data. Business intelligence tools also provide comprehensive reports that can give a vital grasp of data.
The tools also allow you to run different kinds of queries for more customized needs. Some of the most popular business intelligence tools are Microsoft Business IB, Tableau, SAP Business Objects, IBM Congo Analytics, and Qilk Sense.
Statistical Analysis Software- These are specialized programs that are meant for users who want to do an in-depth and more complex statistical analysis. They have very powerful libraries which help in dealing with large data sets.
Since they are capable of working on large data sets, they can also be used for financial Modelling and building predictive models. Such tools are used by Business Intelligence Unit departments of various corporations. Some of the most popular statistical analysis software are SAS, Minitab, SPSS, R, and JMP.
Data Visualization Tools-Data visualization tools present data in a visually appealing and in a more interactive manner thus helping the project managers to comprehend complex data easily and making data more usable.
They provide data in interactive visual formats such as tables, pie- charts, Bar Graphs, Histograms, and Infographics. The engaging nature of the data in the form of highly interactive visuals thus helps in better communication and decision-making. Popular data Visualization tools are Tableau, Fusion Charts, QlikView, Highcharts, plotty, and D3js.
Machine Learning Framework-Machine learning frameworks are highly sophisticated and the most advanced tools of data analytics in project management. Machine learning models are advanced in the sense that the algorithm is trained in a manner that it can identify trends based on past data and build the model.
The model is not static but dynamic since it can reflect and adapt to the changes in data thus making a more precise predictive analysis along with optimizing project schedules. Some of the most popular machine learning frameworks are Py torch, Tensor Flow, Theano, Keras, Scikit learn caffe, and Mx Net.
Text Analytic Tools-Text Analytic tools are a unique kind of application that is used for non-numeric text data. Text Analytic tools are used to make sense of unstructured data. These tools make use of the technique of Natural Language Processing (NLP).
These tools can be used to extract meaningful information from the text data such as identifying the sentiment of the text, i.e. whether the text is written in a positive, negative, or in objective manner in addition to the sentiment analysis these tools can also identify the key highlight or the main theme of the text. Such tools are also capable of extracting vital information from the text such as names or addresses.
These types of tools are mainly used for customer feedback analysis and social media monitoring. Some of the commonly used text analytic tools are Google Cloud Natural, Language API, General Architecture for Text Engineering, -GATE, Datum Box, KH Coder, ODA Miner Lite, and Text Minning extension.
Data Integration and ETL (Extract, Transform, and load) Tools-Data Integration Tools help in extracting data from various different sources and place the combined data in a single place. These tools usually follow a three-step process which consists of extracting the data from different sources, then sanitizing the data and removing irrelevant and superfluous data, and finally loading the sanitized data at the preferred location.
Data integration is a very important part of data analytics since there are vast amounts of data available to any organization but such data is usually scattered over different documents, Data Integration Tools help in getting all the appropriate and workable data in one place thus providing the project managers the right kind of inputs to base their decision making on. Some of the popular Data Integration Tools are Hero Data Matillion, SAS, IBM Infoshare Datastage, Oracle Data Integrator, and Informatica Power Center.
Though, a lot of Data Analytics tools are available in the market for applying data analytics in project management the right tool for any company or user will depend on a variety of factors such scale of the organization, the complexity of data, and the objective of the organization thus depending upon the requirements a project manager can use any single tool or a combination of above-mentioned tools to achieve his goals.
FAQs
How much of a project efficiency could be improved by applying data analytics in project management?
The use of Data analytics in project management can improve project efficiency by many folds but extra care should be taken in choosing the right kind of data analytics tool or a set of tools. Such tools should be chosen which are tailored according to the project.
Data Analytics is performed on past data but the business environment is changing every day so can we completely rely on the use of data analytics in project management to achieve project objectives?
There are various tools such as machine learning tools which not only detect past trends but also make dynamic models that can adapt to changes in data and identify the most subtle trends However, data analytics has some limitations as data analytics tools and their analysis do not take into account extreme events such as natural disasters and political turmoil which can affect the project.
Is it viable for a small business to use data analytics as small data sets are available?
Data analytics is a scientific way of analyzing trends and risks associated with a project it will be equally imperative for a small business to use data analytics in project management to get better at decision making however small business would not need very expensive sophisticated data analytics tools for small business basic data management tool will be enough.
The type of banking that includes the organization of large and complex financial transactions such as mergers or initial public offering (IPO) underwriting is known as Investment Banking. Investment Banks raise money for companies in a variety of ways such as underwriting the issuance of new securities for a corporation, municipality, or other institution and also managing a corporation’s IPO. Investment Banks also play advisory roles in mergers, acquisitions, and reorganizations. The top 8 investment banking free courses will guide you if you want to make a career as an investment banker.
What is Investment Banking?
Investment banking is centered around raising money for companies, governments, and other bodies with activities including underwriting new debt and equity securities for all types of corporations.
The Concept of Investment Banking
Investment banks will for instance underwrite new debt and equity securities for all types of corporations aiding in the sale of securities alongside helping with mergers, acquisitions, and reorganizations. Investment banks provide guidance to issuers regarding the offering and placement of stocks and also broker trades for institutions and private investors.
Many large investment banking systems are affiliates or subsidiaries of larger banking institutions. Some have also become household names with the largest being Goldman Sachs, Morgan Stanley, JPMorgan Chase, Bank of America Merrill Lynch, and Deutsche Bank.
Broadly speaking, investment banks assist in large and complicated financial transactions. If an investment banker’s client is considering an acquisition, merger, or sale they may provide advice on how much a company is worth and how to structure a best deal.
Investment banks will hire investment bankers who can help corporations, governments, and organizations plan and manage large projects which will help their clients save time and money by identifying risks associated with the project before the client moves forward on signing a deal.
Theoretically speaking, investment bankers are experts at measuring the current investing scenario so that businesses and institutions can turn to investment banks for advice on how to plan their development so as to get the best returns. Investment bankers can customize the client’s recommendations to the present state of economic affairs.
Top 8 Investment Banking Free Courses For A Successful Career
1. edX
This program is an initiative by edX and is offered by The New York Institute of Finance. These investment banking free courses will help you by giving a boost to your financial skills and offer you ways of having a successful career in Investment Banking and Finance.
List of Modules that you will learn:
Module 01: Investment Banking
Module 02: Buy-side Institutions
Module 03: Alternative Investments
Module 04: Related Finance Opportunities
Module 05: Career Prep Strategies
Module 06: Overcoming Generational Stereotyping
Module 07: Your Authentic Story
Module 08: Your Personal Brand
Module 09: Cover Letters/Emails
Module 10: Elevator Pitch
Module 11: Impact Interviewing
Why choose this course?
This course will help you gain knowledge of the financial sector so that you can speak confidently when starting or advancing your career in Investment Banking and Finance.
In addition to industry jargon, you will also learn about the hiring processes and the strategies to tell your story in the most compelling way to attract recruiters.
Taught by instructors with decades of experience on Wall Street, this course will guide students from a wide range of backgrounds, including business, economics, engineering, sciences, and mathematics with the required career skills for a future in Investment Banking and Finance.
Free Preview is also available and you can access Module 1 for free. For full course access you have to upgrade to a verified certificate.
Benefits of the Course:-
Engage with industry professionals like experienced practitioners.
Expand your knowledge of the various financial institutions that exist.
Learn the industry jargon.
Find your professional fit.
Elevate your EQ.
Other Important Details:-
Duration: 2 Weeks/ 3 to 4 Hours per Week (Self-paced, Progress at your own speed)
Course Fee: Free (Optional Upgrade Available)
Institution: NYIF
Subject: Business & Management
Level: Introductory
Prerequisites: None
Language: English
Video Transcript: English
Associated program: Professional Certificate in Introduction to Investment Banking
This program is offered by Coursera in collaboration with the University of Geneva. In the investment banking free courses, you will learn how to make smart investment decisions in a global world and also about the various aspects of a wealth-generating investment portfolio.
List of Modules that you will learn:
Understanding Financial Markets
Meeting Investors’ Goals
Portfolio and Risk Management
Securing Investment Returns in the Long Run
Planning your Client’s Wealth keeping in view a 5-Year Horizon
Why choose this course?
You will be earning a Certificate upon completion which you can share on your social profiles.
100% online courses – Start instantly and learn on your own schedule.
Flexible Schedules with which you can set and maintain flexible deadlines.
Beginner Level – No prior experience required.
The course will take approximately 5 months to complete with a suggested pace of 2 hours/week.
English – Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, German, Russian, Spanish.
By enrolling in the investment banking free courses, you will gain a better understanding of valuation and investments along with income statements, balance sheets, and stocks. The publisher of this course is Khan Academy.
List of Modules that you will learn in the investment banking free courses:
Introduction to Valuation and Investing with Learning Outcomes
Price and Market Capitalization
Introduction to the Income Statement
Earnings and EPS
Introduction to the Price-to-Earnings Ratio
P-E Discussion
ROA Discussion 1
ROA Discussion 2
Depreciation
Amortization
P-E Conundrum
Enterprise Value
EBITDA
Introduction to Valuation and Investing with Lesson Summary
Introduction to Valuation and Investing with Course Assessment
Why choose this course?
In this free course, you will learn to analyze balance sheets and income statements
Outlining depreciation and amortization
Learn to identify good stocks from bad stocks on a basic level
Listing the components of a balance sheet
Define Return on Assets along with Return on Equity
Learn to use metrics such as EBIT and EBITDA to assess the risks involved in an investment
Describing the roles of sell-side and buy-side analysts
Discussions on how Enterprise Value can be a better indicator than P/E at determining the value of a business
Benefits of the Course:-
This Free Online Course Includes: 1.5 to 3 Hours of Learning
CPD Accreditation
Final Assessment
Developed by experts in their fields by the course publisher Khan Academy
Other Important Details:-
Certify your skills with a CPD-accredited Alison Diploma/Certificate.
Stand out from the crowd by adding your Alison Certification to your resumé which will help you to stay ahead of the competition.
Advance in your career by sharing your Alison Certification with potential employers to show off your skills and capabilities.
By joining the Finance Foundations course by LinkedIn Learning, you will be getting a comprehensive overview of Finance from reading a Balance Sheet to understanding Derivatives and Securities. This course is mentored by Brigham Young University business professors Jim and Kay Stice.
List of Modules that you will learn in the investment banking free courses :
Introduction to the Essence of Finance
What Is Finance?
Finance inside of companies
Finance outside of companies
Chapter Quiz – 4 questions
Understanding Financial Statements
Introducing financial statements
Overview of financial statements
The balance sheet
The income statement
The statement of cash flows
Common ratios: Debt and current ratios
Common ratios of Return on sales, asset turnover, and ROE
Common ratios: Price-earnings ratio
Forecasting financial statements
Chapter Quiz – 14 questions
Short-Term Financial Management
The operating cycle
Cash management
Managing receivables and inventory
Obtaining short-term financing
Understanding internal controls
Chapter Quiz – 10 questions
Risk and Return: Introduction
What is a risk?
Why we don’t like risk
Reducing risk through diversification
Beta: The concept
Beta: Examples
Risk-free rate
Equity risk premium
Capital asset pricing model (CAPM)
Chapter Quiz – 10 questions
Obtaining Long Term Financing
Introducing long-term financing
Does capital structure matter?
Factors influencing optimal capital structure
Cost of capital of all debt or all equity financing
Cost of capital: Split debt-equity financing
The weighted average cost of capital
Chapter Quiz – 8 questions
Understanding Securities Markets
Introducing securities markets
Learn the differences between a stock and a bond
Stock markets
Bond markets
Publicly traded shares: What impacts the share price?
Initial public offering (IPO): Microsoft
Can you pick stocks in the stock market?
Chapter Quiz – 5 questions
Financial Institutions
Introducing financial institutions
Traditional banks
Investment banks
Investment funds: Index funds
Investment funds like Managed funds, private equity funds, and hedge funds
Insurance companies
Chapter Quiz – 5 questions
Capital Budgeting
Introducing capital budgeting
Capital budgeting overview
The time value of money
Example: Buying a car in Hong Kong
Chapter Quiz – 4 questions
Personal Financial Planning
Introducing personal financial planning
The secret to financial security
The importance of personal budgeting
Simple savings and investment plans
Chapter Quiz – 3 questions
Conclusion
Reviewing corporate finance
Why choose this course?
1 project file
9 chapter quizzes
Access on tablet and phone
Certificate of completion
Continuing Education Units available
Benefits of the Course:-
Beginner Level Course
The duration of the course is 2 Hours and 40 Minutes.
You can do the course for free along with other courses in your first free trial month.
Explore here the other in-demand courses for career development:
The course is available on YouTube and the lecturer is Professor Robert Shiller.
List of Modules that you will learn in the investment banking free courses :
Chapter 1. Key Elements of Investment Banking
Chapter 2. Principles and Culture of Investment Banking
Chapter 3. Regulation of Investment Banking
Chapter 4. Shadow Banking and the Repo Market
Chapter 5. ECON 252 to Wall Street
Chapter 6. Steps to Take to Work on Wall Street Today
Chapter 7. From Wall Street to Silicon Valley with Experiences at Facebook
Chapter 8. Fougner: Question and Answer Session
Why choose this course?
Professor Robert Shiller explains the concept of investment banking by comparing it to consulting, commercial banking, and also securities trading.
Professor Robert Shiller will also talk about some of the principles that John Whitehead, the former chairman of Goldman Sachs, has formulated.
The principles are the answer to the power that investment bankers have, and also their impact on society.
The regulations of the Government on these powerful investment banks have been a debatable issue for many years, especially so now since they played a significant role in the world financial crisis of the 2000s.
Benefits of the Course:-
The duration of the course is 1 Hour and 11 Minutes.
The course is free of cost.
The complete course materials are available at the Yale Online website: online.yale.edu
The medium of instruction is in English.
Looking for financial modeling courses? Here are the best ones for you:
Benefits you will get from the investment banking free courses:-
You will be learning from 3 times New York Times Best Selling Author and Hedge Fund Manager Phil Town.
FREE personalized online course.
List of Modules that you will learn:
Chapter 1 – How to start investing
Chapter 2 – What types of investments will give you maximum returns
Chapter 3 – How to invest for small funds like $20 to $5,000
Chapter 4 – How to invest money to grow your wealth
Chapter 5 – What to Invest in Stocks and What to Look for
Chapter 6 – How to evaluate a company by using financial metrics and investing calculators
Chapter 7 – How to buy stock and Where to purchase them
Chapter 8 – Investing Books that every investor should read
Why choose this course?
You can learn the foundation of investing in 5 easy-to-follow lessons
2 hours of interactive guides and videos
Simple exercises and quizzes to test your knowledge
You will get access to tools used by investing experts for faster and simpler research
7. Skill Share
Benefits of the Course that you will be getting from the investment banking free courses:-
You can get started for Free with the free trial
Get unlimited access to every class
Taught by industry leaders & working professionals
List of Modules that you will learn in the investment banking free courses:
Class Overview
Valuation Overview
Discounted Cash Flow Overview
Discounted Cash Flow in Detail
Discounted Cash Flow Common Questions
Leveraged Buyout Overview
LBO Detailed Steps
LBO and Circular Reference
LBO Common Questions
Paper LBO Framework
Paper LBO Practice Example
Relative Valuation Overview
How to Pick Comps and Precedents
Example of Multiples
Comparable Companies How does it work?
Precedent Transactions How does it work?
Relative Valuation Common Questions
Advantages and Disadvantages of Each Valuation
Ranking the Different Methodologies
Other Valuation Methodologies
Project
Why choose this course?
This course will give you strong basic concepts to answer all the basic valuation questions including the following examples:
Walk me through a DCF
What are the 5 ways for a private equity firm to boost its return in an LBO?
Our comps set gives us a 12x median for EV/EBITDA, and the company we are valuing has $100mm in EBITDA so what would be the implied valuation?
8. Wall Street Mojo
Wall Street Mojo provides beginner-friendly content and is one of the best destinations for finance, accounting, and investment-related information.
Benefits of the Course:-
You will get free access to the course by registering with your email id.
Beginner-friendly course with an introduction to Investment Banking, Ratio Analysis, Financial Modeling, and Valuation.
List of Modules that you will learn in the investment banking free courses:
Part 1 – Introduction
Part 2 – Investment Banking vs. Commercial Banking
What is an investment bank?
What is a commercial bank?
Investment banking vs. commercial banking.
Part 3 – Equity Research
What is equity research?
How does equity research make money?
What is a typical Equity Research job profile?
Clients of the equity research department
Part 4 – Asset Management Company
What is the Asset Management Company or AMC?
How does an asset management company work?
Part 5 – Buy Side vs. Sell Side
In this part 5 video tutorial on Buy-Side vs. Sell Side the following are discussed: –
What is the sell side?
What is the buy side?
Key differences between sell-side and buy-side
Part 6 – Sales and Trading
In this part 6 video tutorial on Sales and Trading, the following are discussed: –
What are sales and trading?
Sales function
Trading function
Part 7 – Raising Capital
How do companies raise capital?
Role of investment bankers in raising capital.
What is an Initial Public Offer
(IPO) and Follow-on Public Offering or FPO?
What are private placements?
Part 8 – Underwriters
In this 8th part on Underwriters, the following are discussed:-
What is Underwriting
Role of Investment Bankers in Underwriting IPOs
Part 9 – Market Making
In this part 9 on market-making by investment banks, the following are discussed: –
Market making
Role of investment bankers in market-making activities
Part 10 – Mergers and Acquisitions
In this part 10 video tutorial on Mergers and Acquisitions, the following is discussed –
What are Mergers and Acquisitions or M&A?
How do investment bankers help in M&As?
Due diligence for M&A.
Investment Banking PitchBook
Part 11 – Restructuring and Reorganization
In this part 11 video tutorial on Restructuring and Reorganization, the discussions are on the following topics:-
What is restructuring?
What is reorganization?
Investment Banker’s Role in Restructuring and Reorganization
Part 12 – Roles, Positions, and Hierarchy
This part 12 video on Investment Banking Roles, positions, and responsibilities discusses the following:
Analyst
Associate
Vice President
Managing Director
Part 13 – Front Office vs. Back Office vs. Middle Office
In this part 13, the following are discussed –
What is a front office?
What is a back office?
What is a Middle office?
Front office vs. Middle Office vs. Back Office
Part 14 – Conclusion
FAQs
❖ How to start a career in Investment Banking with investment banking free courses?
There needs to be more than just doing investment banking free courses and getting certified to start a career in Investment Banking. Doing Internships will help you get ahead in your career if you are just starting out. Enrolling in an Analyst Course will help you to further succeed in your career as an investment banker.
❖ Is Investment Banking a high-paying job?
The average salary of an Investment Banker is around 12 to 15 Lakhs per annum according to a LinkedIn survey.
❖ What are the eligibility criteria to become an Investment Banker?
The eligibility criteria to become an Investment Banker are as follows-
A master’s degree in financial mathematics or a degree from a law college is desirable.
The grades obtained by a candidate in their master’s or bachelor’s degree are also taken into account.
The candidate must have also received at least 55% aggregate marks in the qualifying examination.
Conclusion
So after going through all the details about investment banking free courses a question that may arise in your mind is whether investment banking is worth it or not. Though the field has its own complexities, at the same time one can build a career and be a successful Investment Banker. The most important thing required is a passion for finance and the ability to work hard learn from experience and improve with time. Additionally, the investment bank jobs and salaries are on par with the industry and as a result, the one joining would be emotionally and financially satisfied with this career.
Do you wish to kick-start your career as a Data Scientist? Well, look no further because this article covers all the answers to your queries related to data science. The rapid growth of artificial intelligence and enormous transformation in machine learning have turned data science into a booming industry due to their swift data processing properties. India provides the best online and offline courses for data science. Moreover, Bareilly, a city in Uttar Pradesh, India, which acts as a medical and educational hub has several well-established educational institutes providing numerous courses. To learn in detail about the Top 7 Data Science Courses in Bareilly read this article further. This read is not limited to the location-specific institutes, it also covers online courses, so go ahead and give it a shot.
Let us know the top data science courses in Bareilly with a brief introduction to data science.
Introduction to Data Science
Data Science is a thorough study and interpretation of the data in question, followed by the creation or/and utilization of required tools and techniques for achieving desired solutions/better results.
It is an interdisciplinary passage that integrates various areas of artificial intelligence, statistics, computer engineering, and mathematics to analyze the data. In other words, Data Science assists in figuring out answers to various questions related to data collection, data analysis, and application of the solution found after the analysis.
Though used interchangeably, the terms data science and data analytics are quite different from each other. Imagine, Data Science as a tree that contains complete data processing, whereas Data Analytics is just a branch of this tree with only one focal point – data analysis.
Data Science Serves as an Aid to a Business
Data Science can help a business in the following ways-
By Tracking Mistakes of the Past:
It can reveal previously hidden patterns that can further be broken by a business for its advantage.
By Being Diligent in the Present:
It can discover new problems which can result in out-of-the-box solutions by the business.
By Predicting Changes Likely to Happen in the Future:
It can also help a business become ready for future circumstances by forecasting changes that are coming its way.
Explore These In-demand Data Science Courses Near You:
The Data Science industry has a lot of potential and money. A Data Science Professional can excel in this field by learning technical skills, developing soft skills, and staying updated. The increased data flow in business(es) has resulted in higher demand for data scientists.
Various employment opportunities are opening up for the Data Science Degree/Certification holders.
The Career Opportunities in This Field Are Not Restricted to Becoming a:
Data Scientist,
Machine Learning Engineer,
Data Analyst,
Data Engineer,
Data Architect, etc.
Qualifications Required for Becoming a Data Scientist
Any 1 or more of the following is essential to be obtained to become a data scientist-
Bachelor’s Degree, or/and
Master’s Degree, or/and
Certification Course
Top 7 Data Science Courses In Bareilly With Placements
1. IIM SKILLS
About the institute:
IIM SKILLS is an Ed-Tech Company providing live online and self-paced courses since 2015. It started with a Content Writing Master Course but it later expanded to various skill-based programs like Digital Marketing, Advanced SEO, Business Accounting and Taxation, Data Analytics, and many more.
IIM SKILLS strongly believes in the practical implementation of the theoretical knowledge gained. The teachers make sure that virtual classrooms are interactive. This institute ensures the growth of its students by assigning tasks periodically along with the deadlines to submit those tasks, followed by detailed feedback from IIM SKILLS team members.
Furthermore, IIM SKILLS has trained 45,000+ students globally in a mere 8-year time span.
About the Course:
IIM SKILLS’s Data Science Master Course is recognized as one of the top data science courses in Bareilly because of its 160+ hours of sessions with experienced trainer(s), 100+ hours of practical tasks, 16+ hands-on live projects with the use of tools like Jupyter, Flask, ChatGPT, R, Python, Alteryx, SQL, Power BI, Tableau and AI.
Most courses fail to bridge the gap between theory and application of the same in practical life, which leads to individuals being unsuccessful in landing a job even after spending an ample amount of time and money on earning a certification from an established institution. However, this course skips this error by primarily focusing on the impartation of skills in a manner that by the end of the training the trainees are job-ready.
The course curriculum takes a deep dive into the concepts of Statistics, Artificial Intelligence, Machine Learning, and Deep Learning.
Course Duration: 11 months.
Course Fee: INR 99,900/- + 18% GST.
The Additional Appealing Features of IIM SKILL’s Data Science Course Are as Follows-
Choose weekday and weekend batches as per preferences.
Guaranteed Internship.
Definite Placement opportunities.
Lifetime access to reading material and lecture recordings.
Interest-free EMI is available.
Group discounts are accessible on 3 or more registrations.
UnCodemy is a Noida-based IT training institute serving online as well as offline. It is one of India’s top IT training institutes with 54,000+ students trained by 145+ industry experts. This institute majorly focuses on practical training so that the trainees are prepared for the real world.
UnCodemy imparts offline training in multiple Indian cities. It offers various IT courses like Data Science, Software Testing, Python, Java, Data Analytics, Full stack development, and many more.
About the Course:
UnCodemy’s Data Science Course is considered one of the top data science courses in Bareilly, due to tons of efforts put in by their team members in teaching this course making it a specialty course of this institute. This institute begins multiple batches for this course every month. The course comprises 150+ hours of syllabus and live lectures of 90+ hours. The practical part of the training helps trainees understand and use 15+ tools such as Jupyter, Python, Tableau, etc.
Special characteristics of this course include special batches with flexible timings considering the working crowd, 100% placement guarantee, experience letter, mock interview, 3-6 months internship certificate, and no biases between offline and online students.
The Course Curriculum Covers-
Fundamentals of Data Science.
Usage of Python, SQL, Excel, Tableau, and Power BI in Data Science.
Elements and Tools of Data Visualization.
Various Machine Learning Methods.
Basics of Natural Language Processing.
For further information like course fee, duration, or any other query, contact +91 7701928515.
3. Simplilearn
About the Institute:
Simplilearn has helped transform the careers of 5 million+ professionals with the help of a variety of courses and certifications provided by them since 2010.
About the Course:
Simplilearn offers one of the top data science courses in Bareilly in collaboration with International Business Machines (IBM) Corporation, a multinational IT company. This course provides students with interactive online sessions, lifetime access to study material, and certification by IBM.
Furthermore, Generative, Explainable, Conversational AI, and ChatGPT are some of the skills taught during this course. The functioning and practical application of 14+ tools are also covered in this course. Moreover, 25+ hands-on projects are assigned to the trainees to gain real-world experience.
Knowing the fundamentals of mathematics, statistics, and any programming language are listed as the preconditions to take full advantage of this course. The course curriculum is loaded with basic to advanced knowledge about Data Science and related topics.
Course Duration: 11 months.
Course Fee: INR 57,000/- (inclusive of all taxes).
For a detailed curriculum and a clear way forward, contact toll-free no. +1800-212-7688.
A Few More Data Science Courses That You Should Explore Near You:
Future Group of Institutions is based in Bareilly itself. This institution is one of the top 10 colleges in the Indian State of Uttar Pradesh. This institute also has a collaboration with IBM.
About the Course:
Future Group of Institutions’ Bachelor of Technology in AI and Data Science Course is one of the best data science courses in Bareilly for receiving the finest offline data science training in Bareilly. If the students aspire to enter the field of data science at an early age, then aspiring candidates can opt for this degree course directly after clearing 12th std.
Precondition: 12th pass with PCM (Minimum 45% for General/OBC and 40% for SC in PCM).
Course Duration: 4 years.
Course Fee: INR 90,000/- per year.
A lot of candidates could hesitate before investing 4 crucial years of their life in a degree course for learning AI and Data Science, whereas they can just earn certifications from other online institutes in just a matter of 3-12 months for the same course covering the same topics.
However, the students need to understand that earning those certifications in a short span doesn’t ensure speedy success. The short-term course certificate(s) will be of no use if a person isn’t willing to put enough hours into practising the skill. In skill-based courses, only practice and experience can help a person accomplish goals.
Moreover, starting a career in data science at such an early age, and 4 years of detailed studies and practical training can work wonders for a student’s career.
The course curriculum incorporates all aspects of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). They provide 100% placement assistance by bringing various companies including MNCs to their campus itself.
For a better understanding of the complete four-year plan and other queries related to admission, contact +91 9917480040.
5. Learnbay
About the Institute:
It offers interactive online sessions and also has a placement cell to help its trainees land a job. This institute provides an opportunity for desiring candidates to choose from a plethora of options and caters to the requirements of a broader audience.
About the Course:
Learnbay presents 8 different courses for training in data science and related topics, which ranks their data science courses as the top data science courses in Bareilly.
List of Learnbay’s Data Science Courses-
For Freshers: Data Science and AI Program.
For Data Science Enthusiasts: Data Science Foundation Program.
For becoming Job ready: Certification in Advanced Data Science and AI.
For Professionals:
Tech: Certification in Advanced AI and ML.
Non-Tech: Certification in Data Analytics.
Working: Master Certification in Data Science and AI.
Working: Master Certification in Business Analytics.
Bonus Module: Advanced Certification in Generative AI.
The above-mentioned courses majorly cover math, statistics, programming, and the functioning of SQL, Python, Power BI, Tableau, and AI tools. These courses also propose several choices to their trainees about domain specialization. These courses also differ from each other concerning curriculum, duration, fee structure, and eligibility criteria.
Course Duration: 4 – 13 months.
Course Fee: INR 75,000/- to 1,35,000/-
For detailed information about any course of your choice from the above-mentioned list, contact- +91 7795687988.
Edureka has successfully trained 1 million+ trainees via online sessions. This institute’s course completion rate ranks highest in the training industry.
About the Course:
Edureka’s Data Science Master Course is identified as one of the top data science courses in Bareilly because it covers 13 different courses about data science under one umbrella. This course includes 250+ hours of interactive live sessions, followed by 50+ tasks and 6+ hands-on projects. Easy switch to another batch is one of the USPs of this course.
The course curriculum is gigantic, inclusion of Big Data Hadoop and Spark distinguishes this institute from other data science institutes in Bareilly. This course embraces Statistical Analysis, Python, Tableau, Big Data Hadoop, Spark, and Artificial Intelligence from end to end.
Course Duration: 34 weeks (As it is a self-paced course, the duration might differ from trainee to trainee).
Course Fee: INR 89,999/-
For resolution of any further doubts, contact +91 8951755412.
7. Udacity
About the Institute:
Udacity’s founder, a Stanford Professor came up with an innovative idea to teach an AI course online for free and that was the birth of Udacity, a tech training institute. It has a team of 700+ trainers.
About the Course:
Udacity’s Data Science Nanodegree is listed as one of the top data science courses in Bareilly because of its interesting course curriculum. The number of diversified and quality topics clubbed together for such a brief course is quite astounding.
This Course Incorporates the Subject Matters Mentioned as Follows-
Meaning of Data Science and its process, and Communication with the Stakeholders to share the findings with them.
Best Software Writing Practices to sharpen students’ software skills.
Data Pipelines such as Machine Learning, ETL, and NLP.
Experimental Design, Recommendation Engines, and A/B testing.
Optional course topics include- Neural Networks, Essentials of a Command Line, Git and Github, Linear Algebra, Practical Statistics, Data Visualization, Python, SQL, and Spark.
The potential candidates are requested to check the list of matters on the official website of this institute, the basic knowledge of which is mentioned as a prerequisite to enter this course.
Course Duration: 4 months.
Course Fee: Udacity works on a subscription basis – monthly membership at INR 20,500/-, or one-time 4-month membership which is considered by them as an average time to earn a nano degree at INR 69,700/- (Discount applicable). The fascinating part is that the subscription not only gives access to this one course but also to the complete list of courses, skills, and projects provided by this institute.
Frequently Asked Questions
Q. How to be sure to choose data science as a career or not?
By understanding the fact that if you truly believe you possess basic knowledge of machine learning or databases, powerful analytical, programming, or problem-solving skills, or any interest in math, statistics, or new tools and technologies, then now is the time to enter this industry.
Many reports on the data science industry by various Indian and International sources only show an upward curve for the upcoming years. Even the websites of the above-mentioned institutes teaching top data science courses in Bareilly mention increased job opportunities in this field.
Hence, if you are keen on taking up data science as a career, then give it a chance now so that you can make the most of this booming industry when it reaches its peak in the following years.
Q. How to choose one out of many data science courses in Bareilly?
Initially, shortlist a few courses according to your preference(s) depending on the course duration, course fee, session timings, etc. Furthermore, request a demo class from your preferred choice of institutes.
Moreover, request a counselling session, in case you have any doubts regarding joining the course or if you are confused between two or more courses provided by the same institution. Additionally, call and ask queries, if any.
Finally, don’t forget to read reviews about the institute and the course offered by them on Quora, Reddit, and LinkedIn before joining the course because you can find some genuine personal experiences shared on these sites, which can help you make your decision.
Q. What is the right choice between online and offline data science courses in Bareilly?
Nowadays, online institutes are breaking age-old stereotypes regarding the lack of attention on online students by delivering interactive live sessions effectively. There is no difference left between online and offline studies anymore.
However, you can always have a preference of your own but all I am saying is that the presumption that studying offline assures better training is not true anymore. Hence, choose offline courses because they are genuinely worth it and not because they are offline.
To conclude, the only correct choice amongst the above-listed data science institutes in Bareilly is the one that suits your needs at the moment.
Q. Which are the top 10 institutes for data science in India?
The institutes covered under the above-mentioned list of top 7 data science courses in Bareilly in addition to the below-mentioned 3 institutes will illuminate the top 10 data science institutes in India.
The 3 additional data science institutes in India to enlarge the list of options for you to choose from are as follows-
Great Learning
360DigiTMG
ExcelR
Q. Is it possible for people all over the world to gain benefits of the top data science courses in Bareilly?
Yes, the majority of courses recommended in this article can be accessed through online platforms which makes it possible for anyone to learn from the best data science institutions in Bareilly from any part of the world.
Conclusion
Data Science is a broad term that assists an entity in reading data which can further influence its decision-making by revealing patterns and behaviors with the help of various principles, tools, and techniques.
Due to the strong and unique characteristics of data science and its advantages to a business, various body corporates including MNCs are in search of hiring professionals from data science and related fields.
The increased demand for data scientists has also inspired multiple institutes especially IT Training institutes to include data science training in their list of courses.
These institutes have acknowledged the fact that companies all over the world are going to need professionals from data science and related fields in the next decade. The top data science institutes in Bareilly are waiting to train you but are you ready to learn from them?
Data science courses in Nungambakkam are one of the most demanding professions and act as an edge to your hunger for achieving goals and dreaming high to iron the path of success. Nungambakkam is a downtown city of Chennai that is accompanied by many top-rated institutes offering the most prestigious program of Data Science Courses both online and classroom offering placement assistance.
In this article, we will unbox why to enrol in these top 10 Data Science courses in Nungambakkam, the importance of learning Data Science, the future of Data Scientists, and the job opportunities.
Nungambakkam
Nungambakkam, a downtown city of Chennai, is abundant with Multinational commercial establishments, important government offices, a Cultural centre, and shopping malls. Due to this, it witnesses a boom in demand for skilled Data Scientists and brings many top-rated Institutes offering Data Science courses in Nungambakkam into the purview. If you want to be part of one of the most prestigious programs, Nungambakkam is the place to be.
In this era of innovation and expansion data has become the key to success for the business all over the world. Over the past few years, the volume of noise has changed its way of handling, managing, and buffering the core area of business. A few years back, handling data used to be a difficult task but now it’s just a one-click away with the emergence of Data Analytics.
Before indulging in any course it’s important to understand the core subject and decide whether the amplitude of industry is one for you.
What is Data Science?
Data Science is an academic field that uses statistics, scientific methods, computer science, and algorithms to extract knowledge from unstructured data. It is a sphere that deals with mass data using tools and techniques to find implied patterns and bring out solutions which is indeed beneficial in business decisions.
The data comes from various sources and formats. The professional who handles the whole process and monitors that everything is running smoothly is called a Data Scientist. Thus we can say Data Science is a combination of science, a research method, a discipline, and a profession.
Data Scientists work in six stages. Foremost is to understand the role of the Data Scientist.
Roleplay of Data Scientist
Understanding the business problem
Collecting of data
Exploring data analysis
Model building and evaluation
Communicating results and
Deployment and maintenance of data.
Understanding and deep study of the subject is prior important.
Now the question arises about the eligibility criteria for entering into the course of Data Analytics.
Eligibility for Pursuing Data Science Course
Data science is an emerging course that is available in various universities and certified institutes of Nungambakkam. It can be learned seemingly as well as with various specializations like Python, AI, and Data Analytics.
Online Data Science courses act as a good option for a fresher for a better understanding of Data Science. A person who has a Bachelor’s degree in the field of computer science, statistics, mathematics, or engineering can also apply for Data Science Courses.
After pursuing 12th, students from science backgrounds can also be eligible for any Data Science course may be graduation, diploma, or certification. All these facilities are quite available in the Top 10 Data Science Courses in Nungambakkam.
Skills Require to Learn to Be a Data Scientist
While searching for a good institute one must know about the skills required to be a good Data Scientist as it is the prerequisite requirement in finding the best out of the Top Ten Data Science Courses in Nungambakkam.
So to Be a Data Scientist One Must Pursue the Following Skills:
Knowledge of programming is a must to be a Data Scientist i.e. Python, SQL, and languages like Java, and C++. This will be very helpful at times of scripting, manipulating, and extracting data.
Statistical Analysis- A data scientist should know how to implement correct statistical models.
Machine learning algorithms are the backbone of data. Data Scientists should know how to build and implement models and utilize them for production.
Pre-processing of Data-It’s very important that the data generated is of good quality and usability and for the same the professionals have to be well equipped.
Technology use- They should be at their best when it comes to technology. They should be capable of using various tools like Spark, and Hadoop and cloud platforms like AWS, and GCP.
Not all the skills you have to learn in one instance, but the more you are in practice with these tools the more options will be open for you in the market at large.
Keeping all these perceptions in mind the syllabus of Data Science has been designed by the Top 10 Data Science institutes of Nungambakkam.
Why Pursue Data Science as a Career in Nungambakkam?
Data science is a wide subject and for the same proper training, expertise knowledge, and guidance are required. Nungambakkam is the place where all your questions will be answered, all your requirements will be fulfilled. They use the best modern teaching methods. They provide in-depth knowledge of the subject, and cover techniques like data collection, extraction of data, cleaning of data, integration, and mining.
You are trained well on how to deal with Python, and R programming languages to handle data science models, statistical models, and hypothesis testing. In Nungambakkam, the faculties constantly be with their students and try to make them learn new technologies, and terminologies and make them flexible enough to use them with practice.
They prepare students by giving theoretical knowledge as well as practical training. On time to time basis they give students exercises and real-world projects to build confidence in them. The best part is they provide government-affiliated certificates and a hundred per cent placement to their students. That means before leaving the campus they have jobs in their hands. So all this makes these top ten Data Science courses in Nungambakkam one of the best Data Science course hubs in India.
Explore These In-demand Data Science Courses Near You:
The role of Data Analytics is highly transferable and is available in both private and public sectors including finance, manufacturing consultation, government education, and many more. This can easily be figured out by seeing that every day approx. 2.5 billion population Google search globally or something or other.
Lakhs of stories come on Instagram on an hourly basis, and thousands of videos are uploaded on YouTube or Netflix. Data is generated widely in all these areas and to handle this Data Scientists are required. Data Science professionals believe in a smart workforce. They act as a chain between the business and the end consumers.
In the present scenario, Data Science has become one of the top career options for people with a technology background. A study was taken and the figure that came out showed the huge requirement and need for Data Scientists in the coming years, say more than double. They are the decision maker and backbone of any company.
The company’s progress and meeting consumer requirements is all in the hands of the Data Scientist and for all these criteria the remuneration of the Data Scientist is very high. Data Scientists are among the most highly paid professionals all over the world.
They are in great demand in different sectors including banking, financial services, entertainment, health, retail, automobile, telecommunication, and many more. Every month approximately five thousand positions are open for them.
The average salary of a Data Scientist is Ten Lakh per annum and if a data professional is well learned with Python, R, and Machine learning, he can earn more than above. The remuneration varies with the expertise, knowledge, and skills of the professional. It is anticipated to have more job options in the future for Data Science professionals like:
Data Engineering
Data infrastructure
Research work
Application Architect
Infrastructure Architect
Enterprise Architect
Machine Learning Scientist
Hope this information will find the best to your knowledge to help you kick-start your career in the field of Data Science. Therefore, we have compiled a list of the top ten Data Science courses in Nungambakkam along with necessary details regarding their syllabus, duration, and much more information that will be helpful for you.
Top 10 Data Science Courses In Nungambakkam With Placements
1. IIM SKILLS
IIM Skills is one of the growing online institutes providing education at a reasonable price. IIM SKILLS is known for its courses which are designed by skilled professionals. It provides government-authorised certification in the Data Science Courses.
The course is designed to cover all the important topics in depth. The course is conducted of 6 months of live sessions and 2 months of internship. In addition to this, they give rigorous training with practical assignments.
Course Duration: 11 months.
Course Fee: INR 99,900/- + 18% GST.
The Benefits of Pursuing a Data Science Course in IIM SKILLS Are;
Live lectures.
Doubt-solving sessions.
Assured internship
24*7 online support
Practical Training
Lifetime access to recorded study material.
Knowledge of tools and software
Interview Preparation
Their Syllabus Includes;-
SQL, Python, Jupyter Chat GPT, Regression, Model selection, Web-based interface analysis, Tableau, and Alteryx.
Data Analysis and Reporting, Data Visualization in Excel, Overview of Dashboard, VBA, RDMS Concepts, and Power BI.
They provide the best learning experience with knowledge and skill.
Imarticus Learning is a Chennai hub, which provides certification courses in Data Science and Analytics. They provide 6 month course both online and classroom with 100% placement assurance. The classes are scheduled for 300+ hours with 25+ projects are equipped with 10+ tools and have 400+ hiring partners.
The Syllabus Covered Are –
Practical applications of Data Science.
Expertise knowledge in Python, SQL, Data Analytics, PowerBI, and Tableau.
Their expert faculties deliver robust curriculum using interactive modules and fit-on training methods.
The highlight of pursuing a Data Science course here is it helps in making a resume and helps you participate in coding Hackathons learn to tackle complex business problems and get opportunities to compete in a national level competition.
3. Besant Technologies
Ranked as No. -1 Data Science Training institutes with certification in Chennai. It has 15+ experience in software training and placement. Besant Technologies has around 20+ branches in Chennai and Bangalore. They are available both online and in classrooms.
The Syllabus Covered Under their Data Science Courses in Nungambakkam:
Data Science with Python.
Machine learning
SQL
Artificial Intelligence
Deep learning, NLP
Tableau, Tensor flow, Jupyter
Besant Technologies has award-winning faculties in the domain from top IT backgrounds. They prepare students with industry experts and make them on board for placements. They have a dedicated program manager who ensures students’ progress and makes them learn to build real-life projects in Data Science.
4. Great Learning
They are one of the known online classes for providing PG Programs in Data Science and Business Analytics. It is a 12-month course with dual certification and 100% placement. The syllabus is designed by the faculty at UT Austin Mecombs School of Business and Great Lakes.
The syllabus covers tools and techniques like Python, Tableau, SQL, Chat GPT, Machine learning, and Predictive Modelling.
They assist with projects and concepts through weekly live sessions.
They also provide online videos in case you miss the lecture.
Their dedicated team is always there to guide you with your queries.
Faculties are highly qualified and experienced.
A Few More Data Science Courses That You Should Explore Near You:
To acquire a successful career as a Data Scientist one can switch to 360 DigiTMG. It provides 184 hours of intensive classroom training in the classroom as well as online.
They Offer:
Access to 150 + hours of practical assignments.
2 Capstones Live projects.
Assurance of Job Placement Assistance.
Accelerate your career with 360DigiTMG and become a Data Scientist by indulging in Data Scientist Course Certification and gaining mastery in area-specific skills, tools, and techniques. It is designed to meet the requirements of both work professionals and beginners.
This course will equip students with a strong understanding of fundamental concepts of Data Analytics. Here students will learn advanced Data structure, Data collection process, and programming abilities.
Students will gain expertise in working with all kinds of Data unstructured or structured. They learn to build effective Data Visualisation.
6. LIBA [Loyola Institute of Business Administration]
LIBA provides a diploma in AI with Data Science. The course will run for 5 months. It has both online and classroom sessions. The course is based on a hybrid model of 100+ hours [classroom + virtual].
The Benefits of Choosing This Institute Are:
They provide expert and career coaching sessions.
They offer a thorough knowledge of case studies and help in building confidence.
Students have a convenient learning format, placement assistance, and have hybrid mode of delivery.
The program is designed for both freshers and working professionals.
Offer support 24*7, 7 days a week.
Anyone with having Bachelor’s degree with a minimum of 50% or equivalent passing marks can apply for enrolment.
7. Simplilearn
Simplilearn is one of the best known for online Data science courses. It provides an 11-month certification program and enables candidates to work on real-world projects using aligned tools.
The Benefit of Enrolling is Simplilearn:
They provide an IBM certificate.
Live sessions are conducted by industry experts.
The key feature is they have AMA (Ask Me Anything) which is conducted by IBM leadership.
Candidates learn Python, SQL, Machine Learning, and Generative AI.
The program is designed keeping in mind the journey of students as Data Scientists.
For more details check its website- simpliliearn.com
8. Coursera
If you are interested in joining the Bachelor’s Degree in Data Science Course, then Coursera is the right place.
The Key Features of Coursera Are:
They provide courses like Data Analysis, Machine Learning, Probability, and statistics.
Teaching is done online with professional faculties.
The syllabus contains learning of Python, SQL, Statistics, and R Programming.
For beginners, the course is for 3 to 6 months.
Candidates who want to invest their money and time for a Bachelor’s degree may apply here.
9. Indian Institute of Management
Indian Institute of Management offers Executive Post Graduate Diploma program in management and Artificial Intelligence. Their main aim is to assist the candidate by enhancing their skills. The curriculum is designed by industry experts and award-winning faculties from IIM, Indore.
Their Syllabus for Data Science Courses in Nungambakkam Covers –
Analytics Framework and Decision-making
Business strategy
Programming like Python, R.
Data Visualization
Blockchain Technology
Text mining and more.
The Key Features for Enrolling in IIM Are-
They provide self-assessment assignments for better understanding.
Case studies are given to understand the concepts better.
Highly experienced guest lecturers are invited.
10. Jigsaw Academy
Jigsaw Academy provides Post Graduate Certificate Program in both Data Science and Machine learning.
The Benefits of Indulging in Jigsaw Academy Are-
The course is said as PGCP IN DSML WITH a 100% placement guarantee.
The duration of the course is 9 months of live sessions.
They provide certification from the Manipal Institute of Technology.
They enhance Artificial Intelligence and emphasize Machine Learning for the creation of intelligent machines.
Students work on 7 intensive projects + 2 Capstone projects.
So to get a comprehensive program blended with knowledge and concept learning you may adopt Jigsaw Academy.
After going through a lot of research and taking feedback from faculties and ex-students, the five best recommendations for Data Science courses in Nungambakkam both online and classroom are:
IIM Skills, Nungambakkam
Imarticus Learning Centre
Besant Technologies
360DigiTMG
Simplilearn
FAQs
Can the Data Science Course be pursued after the 12th?
Yes, a candidate who has cleared 10+2 from any recognized board in Mathematics, Physics, and Statistics can apply.
Why Nungambakkam is one of the best choices for a Data Science Course?
If you go with the statistics, Chennai is one of the top three IT hubs in India. It is a privileged city in terms of academics. The next four to five years are indicated as a rainbow time for the Data Science students.
Many renowned national and international companies like Adani, and Netmagic are functioning here. So the opportunities are more in Nungambakkam and they have the best-trained faculties from IT to teach. For better understanding can refer to the above Top 10 Data Science Courses of Nungambakkam.
Which is a better option Data Science Course online or offline?
Data Science is a course that can be done online as well as offline (classroom). Both online and offline classes have their advantages and disadvantages. For people who want flexibility in time and comfort may opt for online classes.
Those who prefer to gain experience face-to-face may opt for offline classes. So, the ball is always in your court as it is a matter of once own priorities, preferences, and needs. Keeping in mind both the options Top 10 Data Science Courses in Nungambakkam is designed.
Which company hires Data Scientist?
In today’s world, the requirement of a Data Scientist is not specified to any particular industry but it is spread widely. Data scientists find opportunities where a lot of data has to be handled like Banks, Insurance Education, and many more. Companies like Delloite, PwC, and Microsoft also hire data scientists. So the jobs related to Data science are endless.
What is the difference between Artificial Intelligence and Data Science?
Artificial Intelligence makes computers think like humans while Data Science deals with data methods, scientific analysis, and statistics and suck out meaningful data from the data provided.
Conclusion:
If we forecast the world of business for the next 10 + years will find data as a lifeline of the business community. A company’s success and failure all depend on the knowledge and usage of data. By assimilating Data Science techniques in business, companies can now forecast future growth, predict potential problems, and build strategies for success. This Data Science is based on the 5 ‘P (Purpose, People, Process, Platform, and Program).
The government has also collaborated with experts in the academic and business fields to create a centre of excellence that will act as a hub for Data Science innovation and training. These initiatives enhance the position of India as a focal point for Data Science hence, contributing to the economic and technological growth of the country.
To survive in business adoption of Data Science is of prime importance for the business, individuals, and company. In this digital era of science and technology, India can create new opportunities for growth and innovation by transforming Data Science in the modern world. India is growing rapidly to become a leading centre for Data Science.
These Top Ten Data Science Courses in Nungambakkam will excel you in skills and techniques with certification.
We live in a data-driven world where data is now more valuable than ever. With the rise of digitalization, these data are being processed to benefit almost every sector. For the smooth functionality of any business institution, systematic research on corresponding data is conducted by an expert. There are different ways through which this research is carried out by experts or data scientists. Data analytics vs Data mining- the two distinct streams of processing data fall under the same umbrella of Business Intelligence.
Depending on these two methods, a specialist can comprehend valuable data and provide insights to the business organization. Consequently, it helps the business grow by making the right decision in future plans and investments. In this way, when a company becomes assured about its performance in today’s competitive market, it gets a lot of scope in satisfying customers and earning better profit.
Why is It Important to Know the Difference Between Data Analytics and Data Mining?
There’s one similarity between Data analytics vs Data mining- both are parts of Business Intelligence. Other than that, these two have a lot of differences between them. Whereas data mining helps us to understand the pattern of collected information, data analytics goes further to organize that dataset to determine crucial decisions.
The terms Data analytics vs data mining are often used interchangeably, but that is absolutely incorrect. Yes, they are related since data mining is a part of data analytics. The two have different methods and goals.
Data mining, a subset of data analytics, includes tracking patterns, association, classification, detection, etc. Data analytics is a prolonged process that entails statistics, mathematics, and operating systems. Thus the multidisciplinary subject data analytics makes evident use of the findings from data mining.
Therefore, while understanding the minutes of data studies, it is obviously worth understanding the main differences between data analytics and data mining. For a reader who is a novice in this field, both of the topics data analytics vs data mining are individually discussed below for a clear understanding of their differences.
Data Analytics is a broad field of data collection, inspection, and transformation of data to create useful information and discover solutions. This vast field extensively relies on the application of OR (Operations Research), Statistics, and Computer Programming to draw effective conclusions.
With these tools, an analyst gathers valuable information from previous performances; and studies them to establish the most reliable decision. In this era of social media and exclusive usage of search engines, data is spread all over the world.
Honing proper analytical skills, one can dig into this ocean of available information to understand the affinity of the generation.
This results in understanding the customer in every sector, providing them with the best available facilities. Thus a data expert helps you to understand the trends, reveal opportunities, and provide concrete decisions.
Data Analytics comprises many subjects like Machine Learning, Data Science, Applied Statistics, etc. Data Analysis is often confused and misunderstood with Data Analytics.
It should be noted that Data Analysis is one of the subsets of Data Analytics and Data Analysis consists of cleaning, modeling, transforming, and questioning the data.
Data requirement: The first step in the data analytics process is to decide what type of data you need for your analysis and then proceed to gather them.
Data collection: Once you are convinced of your requirement, you have to look for the sources to avail the data. There are various sources like questionnaires, case studies, direct observation, surveys, etc.
Data cleaning: Before sending the data for analysis, it is important to sort out the necessary data. This will clean up duplicate records or data having any kind of error. This is a mandatory step in organizing useful data.
Data analysis: A number of tools and software for data analysis are available in the market to help you process or analyze the relevant information. Some examples of such tools are – Rapid Miner, Chartio, Redash, Metabase, Excel, R, Looker, etc.
Data interpretation: Once the data are processed using the mentioned tools, it is time to interpret the result and move towards making the most solvent decision using that.
Data visualization: Next is the time for presenting the insights graphically so that it is understandable for everyone. It helps people to read the datasets and compare the results with others. Some popular methods of visualization are – graphs, charts, pie charts, maps, bullet points, etc.
Data Mining, also referred to as Knowledge Discovery in Data (KDD) is the process of sorting valuable data from vast data sets. With the help of advanced analytics tools and techniques, help businesses predict future patterns and make the most suitable decisions.
Data mining is an important part of Data Science that uses advanced Data Analytics techniques to transform valuable information into creating business planning and strategy. The information it gathers can also be used in Business Intelligence (BI).
In this way, Data Mining not only scrutinizes the historical data but also examines the currently streaming data. Effective Data Mining supports planning business strategies and implementing them. Beginning with marketing, sales, customer support, advertising, manufacturing, etc, Data Mining aids in operating finance and HR.
Even critical cases like fraud detention, security breaches, and risk management, etc are also benefitted by Data Mining. In this way, Data Mining affects not only business but healthcare, government, sports, etc.
Data Mining techniques basically work on two different levels. On one hand, it describes the target dataset. On the other, it predicts the consequences using a machine learning algorithm. In these ways, it surfaces the most important information, filters, and organizes them to create valuable results.
The task of a data scientist is to identify outliers through regression and classification methods. He or she is responsible for extracting necessary information, and collecting and visualizing data for concrete decision-making of the institution.
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Stored data in a database: This is also called a database management system (DBMS). Every data stored in the database is related. Software programs manage these data and help to access them hassle-free. These data are mainly of three types, e.g., shared, distributed, and concurrent data. All these data are stored securely by the software programs.
Data warehouse: This is a single data storage that gathers data from different sources. The collected data then go through the process of cleaning, integration, loading, and refreshing. After that, the data are stored in a unified plan.
Transactional data: Every single online transaction has a unique ID. For example, flight booking, online shopping, and even a click on a website – all these transactions are stored in the database and help in the data mining process.
Others: There are many other varieties of data, like engineering data, multimedia data, data streams, spatial data, etc.
Process of Data Mining
The complete process of data mining follows the below-mentioned four steps-
Setting of business objectives: This is the foundation of the whole data mining process and is considered the most important one. Business stakeholders should work with the data mining expert to chalk out the main motives and achievable goals of the business. For the data scientist, this can be the hardest part demanding extra time and research to understand the business objectives. After the research, the target should be set by the expert and the same must be sanctioned by the company.
Preparation of data: Once the goal is marked then it becomes easier to chalk out the plan of data mining. The data scientist will then identify the particular information that will be able to answer the pertinent question to the business. These relevant data are then sorted and cleaned. In this step, all types of noises- e.g., missing values, outliers, and duplicates are removed. If the sorted data contains too many dimensions, then it is again calculated and cut down to only useful predictors, otherwise, too many dimensions may slow down the process of achieving accuracy.
Model building and pattern mining: Depending on the nature of the collected data, they are modeled with data relationships, such as correlation, sequential pattern, etc. A deep Learning Algorithm may be implemented in this step.
Evaluation and implementation: The finalized data become ready to be evaluated. If the result meets with the desired output, the dataset is used as a dependable predictor to guide the business with the best knowledge and plan for the future.
Data Analytics Vs Data Mining- the Key Differences Explained
1 Types:
Data analytics is of four distinct types, they are-
Descriptive analytics: This uses historical data and uses simple mathematical tools like spreadsheets.
Predictive analytics: This uses statistical analysis along with Artificial Intelligence to identify possible results.
Diagnostic analytics: Using machine learning, this digs into historical data to understand patterns and correlations (if any) of data.
Prescriptive analytics: This uses machine learning and artificial intelligence to help businesses in ultimate business-making. This is the most complex type of data analytics.
The main types of Data mining are-
Pictorial data mining: This transforms collected heterogeneous data into pictorial presentation. It helps in power plant monitoring, flight control, etc.
Text mining: This extracts high-quality data from different written texts through a computer. Through statistical pattern learning, data is derived from written texts such as websites, reviews, books, etc.
Social media mining: More often than not, this data mining is used in traditional or digital marketing. Valuable data is derived from user-generated content in social media and mobile applications to understand and categorize the user.
Web mining: in this process, useful data is automatically derived from web searches and restored from the World Wide Web. The result is used in e-commerce, content analysis, health care services, etc.
Audio and video mining: Multimedia or audio-visual is very accessible nowadays. From this video, huge data sets are extracted and then applied in the fields of security, entertainment, education, and medicine.
2 Tools:
There is no single tool that can address all data analytics or data mining tasks. If you can find one tool that satisfies most of your needs, there must be a secondary tool for some other tasks left.
The tools essential for data analytics are-
Microsoft Excel, Python, R, Jupiter Notebook, Apache Spark, SAS, Tableau, KNIME, etc.
Let us now highlight the different methods in both data analytics vs data mining-
Some of the most used methods for data analytics are-
Cluster Analytics- This is the process of finding objects of similar groups to form clusters. This algorithm is based on machine- learning and works on unlabelled data. Clustering can be done in different ways, such as – density-based, constraint-based, distribution-based, centroid-based, etc
Cohort Analysis- This is behavioral analytics that categorizes data in a data set into cohorts or groups that share the same traits or behavior. By analyzing, the cohorts can understand well about their attitudes and choices.
Regression Analysis- This method is used to realize the relationship between two or more variables. The result is presented in a graph through independent and dependent variables.
Segmentation Analysis- In this method, users or products are divided into different groups to deliver customized advertising, brand positioning, etc.
Time series Analysis- This method is useful for non-stationary data, that is, data that fluctuates over time. Industries like retail and finance make use of this method.
Data Mining methods are-
Association: In this method of data mining, the co-occurrence of associated items is found in a collection. For example, when a shopper puts different items in a basket, it is possible to recommend some other associated items.
Classification: Through classification, we assign a class label to each item in a dataset. Classification is of two types- binary classification and multi-class classification.
Clustering Analysis: It is the process of grouping similar objects into one cluster. For, at first, the partition of data is made and then the label of the group is assigned according to their distinguishing features.
Prediction: By processing input datasets, the numerical output is generated through an algorithm. Unlike classification, this numerical output does not contain any label.
Decision trees: This structure contains root nodes, branches, and leaf nodes. The internal node denotes tests, the branch denotes the outcome of the test, and the leaf node denotes a class label.
4 Subject-matter expertise:
In data mining the following skills are quintessential-
Knowledge of Linux:
The idea about a programming language:
Knowledge of essential tools:
For data analytics, the below-mentioned prerequisites are needed-
Learning of data visualization tools:
Knowledge of programming language:
Probability:
Econometrics:
Programming language:
5 Hypothesis- testing:
A hypothesis is a supposition made with limited evidence and needs further investigation to be approved.
Data analytics heavily depends on the hypothesis that gives information to be tested. For that matter, it even tests on the results derived from data mining.
The data mining expert does not need to conduct a hypothesis. He comprises the collected data or discoveries in a mathematical or statistical.
6 Skills Required:
The different skills required for data analytics vs data mining are discussed below.
Data analytics skills:
Probability and statistics: These two are the founding pillars of data analytics. Using these skills, an analyst estimates value for further research. The statistical approach is mainly based on probability.
Data visualization: In data analytics, it is very important to visualize the outcome through charts, graphs, etc. This visual representation demonstrates the complicated result in a simpler way so that all the stakeholders understand and can take decisions relying on them. One common visualizing tool is Tableau.
Programming language: There are some very useful programming languages to make the analyst’s task smoother. Beginning with Excel, he can hone his knowledge of programming languages like R, Python, etc.
Econometrics: It is a branch of economics that deals with statistical and mathematical models. With the knowledge of econometrics, the analyst can foresee future trends and make better predictions.
Data Mining skills:
§ Programming language: A set of programming languages used for data mining. They are- JAVA, Matlab, SQL, Python, R, etc. Depending on the dataset one working with, a particular program is selected. However, the most common of them are Python and R.
Data processing frameworks: These frameworks extract insights from large datasets. Some of the most implemented frameworks are Hadoop, Spark, etc.
Operating system: Linux is the most popular OS for the data mining process.
Database knowledge: To process the large dataset, one must have knowledge of Relational databases (SQL, Oracle) and non-relational databases (Document, MongoDB, Cassandra, etc.)
7 Size of the Team:
Data analytics is a lengthy process that usually requires a group of people. This team will ask questions, draw patterns of responses and reach a conclusion. Although machine learning, Artificial Intelligence, etc. are used in this process, the lengthy process requires human involvement.
Data mining can be conducted by a single person also. With the right technological skills and knowledge of software, he will write down the data findings.
Frequently Asked Questions on Data Analytics vs Data Mining
1 Which is more in demand – Data Analytics vs Data Mining?
Data analytics help in making hypotheses whereas data mining makes data useable. So, both of them have different fields of application. As data scientists are currently ruling the world with new-age science and technology, there is a dearth of experts in both. None of the above-discussed streams are conventional stereotypical subjects to have huge competition and lots of competitors. So, one has only to hone their capability to be hired by big companies.
2 In brief, what is the main difference between Data Analytics vs Data Mining?
Data mining is a step in the complicated process of data analytics. This step focuses on scientific and systematic methods of data collection and then, deriving insights from those data. Data analytics goes on further by using those data to create hypotheses and build models on that.
3 Name four main models that are used in Data Analytics.
The four main models for data analytics are –
Descriptive
2 Diagnostic
3 Predictive
4 prescriptive
4 Write about two useful models used in Data Mining.
1 Predictive model / Statistical Regression: As the title says, through this model, data are converted to form predictions about the future performances of the company.
2 Descriptive model: In this model of data mining, data are described in a readable format. It extracts from the stored data and creates reports by monitoring them.
5 Data Analytics vs Data Mining- write some applications of each.
Application of data analytics:
Data analysts can help strengthen security by supplying valuable data on crimes to police. Geographical and historical data analysis of a particular crime-driven area helps in locating such spots and eventually necessary action can be taken.
Application of data mining:
Data mining applications can help in business revenue by investing capital in an efficient way. The sale of a particular item at a particular time of the day can be researched using data mining techniques. The production and availability of that particular item will help in better revenue for the business.
Conclusion: Data Analytics vs Data Mining
With the wide usage of computers research on data has taken a leap. Although the two terms data analytics vs data mining – are often used interchangeably, the above description points out their distinction. On one hand, these differ in implementation. On the other, the experts in the two fields require different skills. With the sheer power of computers, experts are playing with data to explore more in this field. Between data analytics vs data mining, whichever side you may choose, the above details enlighten you to appreciate the importance of the other. The data-driven 21st century needs mindsets with a knack for coding to make a revolution. So, this was the guide to data analytics vs data mining.
