Top 6 Data Analytics Courses in London With Placements

by | Nov 2, 2024 | Courses, Data Analytics

Over the past decades, there has been a massive increase in demand for data-related roles. It is said that “Data is the new oil”, so in line with the futuristic goals in mind, all major global organizations worldwide are leveraging the data which they already possess or are in the process of acquiring the same from external sources. Learn these rewarding skills with the best data analytics courses in London.

List of best data analytics courses in London The hiring for data analytics roles has increased by almost 50-70% annually. People from varied backgrounds are trying to break into the data industry. London is one of the financial hubs in the world, this article will walk you through data analytics courses in London to get you a break in the data analytics field.

Data Analytics – The Demand and Hype

Data analytics is a method of applying quantitative and qualitative techniques to analyze data and aiming to gain valuable insights. With the help of Data Analytics, we can explore and conclude the data. Companies across the globe generate a vast amount of data in the form of transactional data, customer-related data, and log files. In addition, consider social media which generates an ocean of data every single second. Companies are looking into ways of generating some meaning or value out of data that could help in their business growth.

Successful Data Analytics Relies on several Things Such as

  • The quality of data collected
  • The amount of data collected
  • The skill level of data analyst employed to make meaning out of data
  • The tools used to analyze data.

The role of Data Analytics is one of the most sought-after professions in today’s scenario, so there is no better time than now to venture into data analytics courses in London.

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Tools Exposure at Data Analytics Courses in London

Tools play an important part in the Data Analytics process. Learning different tools can help speed up data analytics. There are pros and cons to each of the tools, some require programming skills while others are easy to use using the drag-and-drop feature.

Some Popular Tools Used in Data Analytics

  • Tableau

Tableau is one of the best commercial data analysis tools available for creating interactive visualizations and dashboards without extensive coding knowledge. Tableau can handle large amounts of data better than many other tools and is extremely user-friendly. It has a graphical drag-and-drop interface. However, It’s not ideal for pre-processing data or creating more complex calculations.

  • Power BI

Power BI is a new entrant venturing into data analytics tools. Power BI allows users to quickly and easily create interactive visual reports and dashboards. Power BI has excellent data connectivity—it works seamlessly with Excel because it is a Microsoft product, but it also works with text files, SQL servers, and cloud sources.

  • QlikView

QlikView uses interactive analytics in conjunction with in-memory storage technology to analyze massive amounts of data and use data discoveries to aid decision-making. It provides both social data discovery and interactive guided analytics. It can manipulate massive data sets quickly and accurately.

  • Python

Python is a programming language with numerous applications, it is a must-have for any data analyst. Unlike more complex languages, it focuses on readability and is widely used in the tech industry. Python is also extremely versatile, with a plethora of resource libraries suited to a wide range of data analytics tasks. The NumPy and pandas libraries, for example, are excellent for streamlining highly computational tasks while also supporting general data manipulation.

  • R

R is a popular open-source programming language. It is commonly used in the development of statistical/data analysis software. The syntax of R is more complicated than that of Python, and the learning curve is steeper. However, it was designed specifically for heavy statistical computing tasks and is widely used for data visualization. R, like Python, has a network of publicly available code.

  • Apache Spark

Apache Spark is a software framework that enables data analysts and data scientists to process large amounts of data quickly. It was created in 2012 and then donated to the non-profit Apache Software Foundation. Spark is a big data analytics framework that distributes computationally intensive analytics tasks across many computers.

SAS (Statistical Analysis System) is a well-known commercial suite of business intelligence and data analysis tools. The SAS Institute is a pioneer in a data analytics tool, they developed long back around the 1960s, and it has evolved since then. Its primary applications today are customer profiling, reporting, data mining, and predictive modeling. Designed for the enterprise market, the software is generally more robust, versatile, and user-friendly for large organizations.

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Benefits of Joining Data Analytics Courses in London and the UK

The demand for talent for all data-related careers remains all-time high and is likely to grow in the future. Companies are looking to hire people who are proficient in Data Analytics and who can find hidden patterns and meaningful data relations, unseen trends. The career offers high-level job satisfaction to those who have a curious mindset and who can question the data.

  • Informed Decision-Making

The most obvious advantage of data analytics is the use of data to inform and justify key business decisions. This is typically accomplished in two steps. To begin, predictive analytics can help predict what will happen in the future based on the data collected. In contrast, prescriptive analytics can then be used to indicate how your business should respond to these predicted changes.

Data analytics eliminates the need for guesswork and manual labor. Whether it’s selecting the right content, planning marketing campaigns, or creating new products. Organizations can use data analytics insights to make more informed decisions. As a result, better outcomes and customer satisfaction are achieved.

  • Improve Efficiency

Organizations can use data analytics to streamline their processes, save money, and increase production. They spend less time creating ads and content that aren’t relevant to their audience’s interests. Many businesses use data analytics to improve operational efficiency.

For example, collecting and analyzing data about the supply chains on which the company relies to identify where delays and/or bottlenecks occur can help predict where future problems may occur and how to best avoid them.

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  • Improve Customer Service

Data analytics enables you to tailor customer service to their specific requirements. It also provides personalization and strengthens customer relationships. Data analysis can reveal information about customers’ preferences, concerns, and more. It allows you to make better product and service recommendations. It also helps adjust the pricing.

  • Effective Marketing

Data analytics provides valuable insights into the performance of your campaigns. This aids in fine-tuning them for optimal results. You can also identify potential customers who are most likely to engage with a campaign and convert it into leads. Data analytics can provide a detailed analysis of current customer behavior trends, including all subgroups such as gender, age, location, and so on. This enables marketers to tailor their strategies to appeal to each of these audiences uniquely.

 

Skills Required for Data Analytics Courses in London

Data Analytics requires a skill set that comes from multiple different fields. They need to understand data analysis while possessing software skills has some advantages over others. Most Data analytics job listings indicate that they prefer candidates with a quantitative degree in any of these fields:

  • Computer Science
  • Engineering
  • Computational Statistics
  • Data Science
  • Mathematics

However, most employers understand that data analytics is a constantly changing field, and the most extensive qualification a candidate needs to possess is the ability to learn new tools. However, companies are willing to hire individuals who don’t hold the preferred qualifications but can still do the job. One can self-learn the skills required to become a Data Analyst, and we will provide you with learning institutions to become a Data Analyst in the next section.

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Top 6 Data Analytics Courses in London

Some of the reputed institutions providing data analytics courses in London:

 

1. IIM SKILLS

IIM SKILLS was incorporated in the year 2015 by Vaibhav Kakkar and introduced their first course in content writing. Since then IIM SKILLS began with its journey as an educational company that offers a wide range of courses in different fields worldwide.

Among the range of courses offered by IIM SKILLS, Data Analytics Courses in London have the highest ranking. The course duration for data analytics courses in London is 6 months followed by 2 months of optional internship. The course is completely certified & tool-oriented.

 

Weekly assignments help the students gain practical knowledge which makes them career-ready. London is a country full of opportunities and career scope. So those who opt for data analytics courses in London will open doors to many career options that will enhance their analytical skills leading to career growth and success.

Also Read: IIM SKILLS Data Analytics Course Review

Course Name – Data Analytics Course

Fees: 471.37 Pound Sterling + Taxes

Interest-free EMI payment is available.

Other Professional Courses from IIM SKILLS

 

Contact Information: 

+919580740740, info@iimskills.com

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2. Queen Mary University of London

This program is application-based and helps to put the learning into the context of real-world challenges. The program is suitable for those who have an interest in problem-solving and some understanding of probability and statistics.

The student will be assessed by a mixture of formal examination and coursework in taught modules which will be approx. 70% and the rest 30% based on self-directed Data Analytics Project work. The campus is located in London’s east end which offers a rich cultural environment.

The lectures will be held offline in the self-contained residential campus. The study mode university offers both Full-time and Part-time study.

Course Highlights and Advantages of Pursuing Data Analytics Courses in London From Queen Mary University

  • Learn from expert academics and industry practitioners, many of whom are Alan Turing Institute Fellows.
  • Attend Lectures and Seminars from Queen Mary’s Institute of Applied Data Science members.
  • This curriculum is highly practical and will have industry ties to assist you in applying what you learn to problems in the real world.

The Program is Divided Into Semesters, and the Structure is as Follows

  • Three compulsory modules
  • Five elective modules (to be chosen from 12)
  • Final project and dissertation

Compulsory/Core Modules

  • Data visualization, manipulation
  • Probability and Statistics for Data Analytics
  • Project Dissertation

Elective Modules

  • Financial Data Analytics
  • Advanced Machine Learning
  • Neural Network and Deep Learning
  • Programming in python
  • Graph and Networks
  • Time Series
  • Computational Statistics with R

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3. Imperial College Business School

MSc Business Analytics prepares you to make data-driven and evidence-based decisions and to drive business transformation. The students will receive rigorous technical and quantitative training, as well as opportunities to apply the learning in a practical scenario.

Why Should You Join the Business Analytics Course in London From Imperial College?

Imperial College London is ranked in the top 10 universities. The college offers Full-time as well as part-time study modes. Full-time study mode is a one-year intensive course conducted in South Kensington, London. The part-time course is two-year and can be attended from anywhere in the world without interrupting the job.

The Program is Structured as Follows

  • Core Modules

The theoretical and coding foundations you need for analytics are quickly built with core modules. They serve as the program’s foundation and will arm you with a strong set of skills and knowledge.

  • Elective Modules

By taking electives, you can tailor your degree to your specific career goals.

  • Projects

The program concludes with a choice of projects: a Consulting Project (Business Analytics on-campus), a Work Placement/Work-Based Project, or an Individual Research Project, followed by the Business Analytics Report.

 

4. London Metropolitan University

This course will teach you the theoretical, technical, and practical skills needed to work as a data analyst. You’ll be well prepared for a career in data analytics after graduation, thanks to an expert teaching team, access to specialized software, and work on real-world business cases.

Why Study Data Analysis Courses in London From London Metropolitan University?

MSc in Data Analytics from LMU will teach vital subjects including data mining, statistical modeling, business intelligence, and data visualization. The MSc program will help students gain exposure to key industry resources and real-life business cases.

 

The student will also be trained to use specialist software required for Business Analytics. This course’s modules were created with the assistance of industry professionals, some of whom will be present to teach you in specific classes.

These experts will guide you through advanced data science techniques. You’ll learn about financial mathematics, statistical modeling, and forecasting, among other things. Furthermore, in the MSc Project module, you will have the opportunity to create your unique piece of work.

The student will be assessed based on written reports, practical and research assignments, demonstrations, presentations, group work, and assignments.

The Program is Structured in a Modular Way With the Following Modules

Data Analysis and Visualization

This module delves into the fundamental concepts of data analysis and visualization. The module introduces descriptive statistics for exploratory data analysis, correlation analysis, and the linear regression model.

Graph and text data analysis techniques for web and big data, as well as reporting and visualizing the results, are also covered. The module includes a significant practical component that allows students to apply data analysis and visualization techniques.

The Goals of This Module Are to: 

  • Enable students to understand fundamental concepts in data analysis and visualization.
  • Expertise in data analysis with descriptive statistics
  • Enable students to acquire knowledge of graph and text data analysis.
  • Provide students with practical skills in applying data analysis.

Data Mining and Machine Learning

This module provides an understanding of the fundamental concepts, algorithms, and processes of data mining and machine learning. It covers data analysis, pattern mining, clustering, classification, and regression using machine learning algorithms and data mining techniques.

The Objectives of Data Analytics Courses in London Are to: 

  • Provide students with a fundamental understanding of data mining and machine learning concepts, algorithms, and processes.
  • Comprehend the purpose and breadth of data mining and machine learning applications
  • Comprehend and compare the techniques and tools available for different types of data analytics problems
  • Provide students with hands-on experience using data mining techniques to solve real-world analytics problems.

 

Project

The module allows students to plan and complete a large piece of individual work. In addition, the module aims to encourage and reward individual creativity and effort by working on research or company/local government projects. The project is an exercise that can take many different forms depending on the nature of the project and the subject matter. Students will be encouraged to complete projects for local businesses or government agencies.

The module’s goal is to encourage and reward individual creativity and effort. It also aims to provide students with the following opportunities:

  • To have the opportunity to assimilate the knowledge they gained in their course and apply it in new areas.
  • Using established research techniques and methods, apply newly acquired knowledge and techniques to a specific problem.
  • To establish the project framework by a set of specifications pertinent to the subject of study.
  • To manage a large piece of work by confining the problem within the constraints of time and resources available.

Programming for Data Analytics

Through the introduction of application programming for data analytics, this module strengthens students’ foundation in programming principles. The module covers common data structures in programming, flow controls, data input and output, and error handling. The module focuses on data manipulation and presentation for data analysis in particular. A significant practical component is integrated into the module to teach students how to prepare data for analysis and develop data analytical applications using a programming language (e.g., Python).

The Objectives of Data Analysis Courses in London Are to:

  • Enable students to gain an understanding of programming principles.
  • skills in programming design and coding
  • expertise in data manipulation and presentation for data analysis
  • Develop students with practical skills in data analytical application development.
  • Improve students’ integrative reasoning, problem-solving, and critical thinking skills.

 

5. Brainstation

BrainStation’s Data Analytics courses in London are designed to help start a career in data analysis. The course helps one build job-ready data analytics skills required to succeed in the modern workplace. Train stations experience data professionals will expose students to industry tools and complex datasets which will help develop essential data skills and knowledge.

Data Analyst instructors at BrainStation have experienced data professionals who work at the world’s most renowned companies. The campus is located in the Centre of London. The train station also helps build a data analysis portfolio. The course is conducted on campus, live, and expert-led.

The Course is Structured in 3 Units

  • Intro to Data Analytics
    • Apply Data Strategy
    • Learn Data Cleaning
    • Excel Data Analysis
  • Database Operations & Advanced Data Analytics
    • Learn Database Fundamentals
    • SQL for data analysis
    • Advanced data analytics
    • Large Data sets
  • Data Visualization
    • Tableau Data Visualization
    • Build Tableau Dashboards
    • Data storytelling

 

6. General Assembly

The General Assembly data analytics courses in London are designed with a focus on real-world use cases. The course helps translate data into meaningful insights. The course is ideal for beginners looking to upskill. The mode of study is online or on-campus. To complete the course, the student has to complete capstone projects and other smaller projects to reinforce their learning.

Why You Should Join the General Assembly’s Data Analysis Courses in London?

The course equips students with Pre-prep course lessons. When a student enrolls, the institute provides students with online, self-paced preparatory lessons to help them succeed. This helps students gain a common vocabulary and be able to collaborate with other batch mates.

 

This course is designed for students with a wide range of professional backgrounds and experience levels, including beginners, and takes a deep dive into the data analytics process, including data collection, cleaning, analysis, and visualization. Learn how to use Excel, SQL, and Tableau to turn raw data into a critical decision-making tool.

FAQs

1. Do data analysis courses in London offer promising careers?

In the current market scenario, skilled data analysis is the most sought-after career with a competitive salary in London and other parts of the UK.

2. What skills does a Data Analyst need?

Skills required for data analysis include Structured Query Language (SQL), Microsoft Excel, Critical Thinking, R or Python–Statistical Programming, Data Visualisation, and Presentation Skills.

3. What is the career path in data analytics?

From an entry-level role such as data analyst, one can progress to senior analyst or data scientist.

4. What are the tools used in data analytics?

Some of the widely used tools include SAS, Tableau, QlikView, Microsoft PowerBI, Python, and R.

5. What is the average salary for a Data Analyst?

The average salary for a Data Analyst in the London area is approximately GBP 39500 per annum.

Conclusion

Data Analytics is one of the most lucrative and rewarding careers to look forward to in the future. The Data Analysis courses in London listed in the article will help one enter the field of Data Analytics. Students participate in London’s excellent cultural, business, and financial learning environment. Thus, the above programs open the door to career growth for Data Analytics professionals.

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