Top 7 Online Data Analytics Courses With Placements

Data analytics is fetching ground like never before. Data analytics has brought a quantum change in the way we live and businesses do their business. Corporations, start-ups, SMEs, and large organizations around the world are generating huge amounts of data to reduce costs, focus on target marketing, and optimize existing processes. One thing is certain, data analytics will be the core of countless technological solutions. In this article, you will find the best online data analytics courses to help you learn the process.

List of best online data analytics courses

People already use analytics for making various decisions in their lives. From choosing the best routes to reach a destination to the identification of waste using quality tools.

Data analytics is crucial to many organizations and there has never been a better time to add that skill to your resume. With more people using online tools to analyze data, companies are finding it easier to understand the data they’re collecting.

What Can Data Analytics Do?

Data analytics helps in improving decisions and having a better understanding of a phenomenon. If I say by learning online data analysis courses, you could answer questions such as – should I buy more stocks, is a particular type of medicine effective, or how much any product can fetch sales in any season?

Then, it wouldn’t be wrong because if you can accurately predict how much product can grab your paying customer you can plan your procurements to meet the demand. If you can prove the effectiveness then you could be helping people’s health and well-being. Conversely, if the results don’t come as desired then you could also prevent people from buying the medicine.

Also, check out a few other online courses that will bring a rewarding career ahead:

 

Data Analytics – Formats  and Types 

1) Big Data

2) Structured and Unstructured Data

3) Metadata

4) Real-time data

5) Machine data

Big Data –

Big Data is a term to describe a huge volume of complex data that databases of traditional database management applications can’t use.  Big Data is characterized by the 5 V’s which are Volume, Velocity, Value, Variety, and Veracity. Volume determines the quantity of data, Velocity refers to the speed of data growth, variety describes its source and Veracity refers to the quality of data.

Structured and Unstructured Data –

Structured Data is a traditional data model of rows and columns whereas unstructured data is in the form of pictures, text, or video.

Metadata –

Metadata is another form of data that reads and provides information about other different data such as unstructured data.

Real-time Data

Data that is processed and presented at the same time is called Real-Time Data. Real-time data is very useful in stock markets to make decisions upon information received at that moment.

Machine Data –

Data generated automatically from machines such as physical devices, software, and clouds collectively called IoT ( Internet of Things) is called Machine data.

Types of Data Analysis

  1. Diagnostic Analysis
  2. Predictive Analysis
  3. Prescriptive Analysis
  4. Statistical Analysis

 

1. Diagnostic Analysis

Diagnostic Analysis identifies the root cause by identifying and collecting additional data and reporting to outliers about why the event occurred. For example, if a descriptive analysis tells you that 5% of sales dropped, a Diagnostics Analysis will tell you the root cause of the 5% drop in sales.

2. Predictive Analysis

As the name implies, Predictive analysis is about predicting what is likely to happen in the future of a given problem. Predictive analysis is very beneficial for business planning. Predictive Analysts create a model and use the relationship between set variables to make predictions. For Example; Predictive Analysts may predict a correlation between off-season and a drop in sales. Hen based on this business may spend less on advertising campaigns and so on.

Must read about the most-opted:

 

3. Prescriptive Analysis

Prescriptive Analysis looks into what happened why it happened and what is the best course of action that can be taken to avoid the problem in the future. Google Maps serves as the best example here. It considers all the best possible routes to reach a point by all modes of transport.

4. Statistical Analysis

Statistical Analysis looks to answer the question – What Happened? This type of analysis comprises data collection, interpretation, and then a presentation on the dashboard. Statistical Analysis is further divided into Descriptive, Inferential, and Text Analysis

a) Descriptive: Here Analysts summarize numerical data by means, deviations, and percentages in the form of categorical data.

b) Inferential: This involves working with samples from given data. Analysts come to different conclusions from the set of data by choosing different samples.

 c) Text: Text Analysis is also called Data Mining and is one of the most direct methods of data analysis. Text Analysis uses databases and data mining tools to know patterns of large datasets. Data Mining or Text Analysis helps convert raw data into useful information.

 

So What is Data Analytics and Why It Is So Important in Business? 

Data Analytics is a process of collecting, cleansing, and visualizing data and drawing conclusions about the results they contain. The techniques used in Data Analytics enable to extraction of raw data and drawing patterns to get insights from it. The importance of Data Analytics is increasing at a rapid speed, today Data Analytics is seen as a crucial part of businesses for planning on resources, making financial decisions, and meeting customers’ expectations.

Data Analytics Helps In:

  • Targeting Customers
  • Reduced Operational Costs
  • Problem-Solving
  • Effective Marketing
  • Customer Service
  • Smooth Operations

For businesses to understand and interpret solutions in a meaningful way, data analysis is crucial. In simple terms, data is the organization, interpretation, structuring, and presentation of information. As organizations become more technologically savvy, they are also becoming more research-driven.

Today, any business that wants to make scientific decisions needs to analyze data. The process is streamlined, money is saved, and customers are offered what they want. Businesses do not want to invest in advertising campaigns and target demographics that have some interest in their products and services.

Data analysis helps businesses to track their product’s performance on targeted demographics. Through data, businesses get a clear picture of targeted audiences’ spending habits and their interests.  The data also helps them in setting prices determining the average length of advertising campaigns and some cases even calling off the product.

As a result of data analysis, Coca Coca-Cola beverage giant created the hashtag #Shareacoke to increase customer retention and acquisition, Netflix uses data analysis to target its advertisement campaigns to reach success. Amazon uses innovation to make products.

Get a detailed guide about the other most trusted courses for a rewarding career:

 

Data Analysis Testing Methods

Quantitative Data Analysis is done by working with numerical variables like statistics, percentages, and measurements. It involves using algorithms and mathematical analytical tools to get insights into any value

Techniques of Quantitative Data Analysis 

Regression Analysis is a statistical method to predict an outcome of historical data, it helps in understanding and building a model to predict the outcome based on the model.  Regression analysis is used to predict behaviors of both dependent and variable factors.

For example, if you want to know what type of Vine people buy, then you would find data on people, their age, financial status, etc who buy Vine. Regression Analysis has two primary types:  Simple Linear and Multiple Linear

Simple linear regression analysis is a mathematical representation of a single independent and normally dependent variable. Whereas, In Multiple linear aggression, there are multiple variables with the normal dependent variables. Multiple linear regression models can help in complex relationships of different features and can help to map relationships between multiple variables.

On the other hand, Qualitative Data Analysis is mostly used by businesses. This approach is non-numerical and works with certain identifiers such as labels, and statistical percentages. Quantitative Data Analysts may use interviews, observation, and review documents to get a result.

Have a look at these advanced:

 

Techniques of Qualitative Data Analysis 

The Qualitative data analysis is made on two main approaches:  Inductive and Deductive Approaches. The inductive approach refers to the collection of data from general observations to conclude with a theory. This type of method is also called the Bottom-up approach as it involves building a set of ideas from a specific view.

In the deductive approach, a researcher is drawn to achieve an accurate answer given that the results are established.  There is no possibility of any invalid conclusion if no mistakes were made.

Excel, SQL, Tableau, or Python – Which Technology Do I Learn First?

Many learners have this question in mind when they hear of tech knowledge required for any particular course they want to start with. Learning Excel is one of the best ways to get started in the field of Data Analytics and Excel is such a software that many are intermediate level. Many employers still run their entire data analytics through Excel. So, job opportunities for skilled Excel data analysts are also there.

If you know Excel then learning SQL is a good decision. SQL is a query language for databases like  MySQL, and PostgreSQL, online data analysis courses are more focused on syntax and data modeling. Many businesses store their company data in SQL databases and appoint an analyst to extract, summarize, and create a report.

After you have learned about SQL and got some spreadsheet experience, you can move on to learn R. R – Ruby language program is used for statistical computing, scientific research, Data Analytics, visualization, and presentation of data. It is more object-oriented. It emphasizes quality reporting for visualizations and creating interactive web applications.

The R language is designed for Data Analysis and is important to have good knowledge if you want to have a career in data science. However, there are certain drawbacks in R such as slow performance and lack of testing features are some of the reasons that most data scientists and analysts prefer to look for other languages such as Python.

Python is a powerful and versatile language used for various computer tasks like building websites, automating tasks, and doing data analysis. Its flexibility for beginners has made it one of the most used planning languages today. Python is used in the fields of Artificial intelligence, Web development, Mobile application, and Game development.

It highly depends on your goals to learn there are several factors to consider before you start. SQL is interesting to learn because its paradigm is different. SQL robustly handles data. For Example, SQL can handle huge data and can at the same time handle crashes and keep the database system still in a consistent state.

For Data Analysis, you follow a process where you need to gather raw data, and clean and build algorithms. You will then visualize and create a report. To manage data, as a first tool, you’d require SQL or NoSQL databases. NoSQL has gained popularity with big data like the data managed by Google, and Facebook.

Given the current situation of the world, businesses are becoming more data-oriented, hence getting to know SQL is very useful. On the other hand, for job prospects, the best would be Python then SQL, and then R.

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 What Does A Data Analyst Do? 

Data Analysts are professionals who help businesses in making better decisions to generate good revenues. Data Analysts are responsible for extracting data from databases, excel sheets, and CSVs applying statistical analysis, and converting them to readable formats in the form of summary reports and dashboards.

If Data analysis seems right up to your next career skill, then keep on reading for the best online Data Analysis Courses with certificates.

The listed 5 online data analytics courses will teach you everything you need to know about the job title Data Analyst. Did I mention that these courses will cost you less than the cost of a traditional degree? So, if you don’t have a degree, you can still become a Data Analyst by taking online data analytics courses from a trusted provider.

 

Best 5 Online Data Analytics Courses

 

Rank# 1. Online Data Analytics Courses

1. IIM SKILLS

The Master Data Analytics Course provided by the world-renowned institute IIM SKILLS is the most comprehensive training program that is designed to cater to students who are keen to make a career in data analytics. It is a 6-month course which will take you through the most basic to advanced levels of concepts.

 

They have a complete delivery plan which is scheduled as per the student’s needs and requirements, which makes them feel fulfilled and skilled. Their 24/7 support system is a big help to their student which makes them feel free to reach them and ask their questions.

Why they are called industry leaders is they know what queries the students have. Because of their expertise in data analytics, they cover all of those in the sessions, so in the end, students will be fully satisfied. Still, if you have any queries, you are free to reach them.

 

Online Data Analytics Courses

It is a government-recognized course that lasts up to 6 months during which you are going to learn the core concepts of data analytics and will be working on different projects to get hands-on practice. It is a tool-driven course, and a variety of courses are covered in it.

It is a must-course for anyone who is truly into building skills as the 2 months of internship followed by the course helps to develop advanced skills and build your portfolio to make you ready to crack any job interview. They have a dedicated placement cell which is a great source of help for the students. All you need to do is trust IIM SKILLS and work hard.


Also Read: IIM SKILLS Data Analytics Course Review

Core Modules:

Data Analytics Using Advanced Excel (9 Hours)
Data Analytics Using VBA (15 Hours)
Data Analytics Using SQL (39 Hours)
Data Analytics Using Power BI (24 Hours)
Data Analytics Using Python-1(10 Hours)
Data Analytics Using Python-2 (10 Hours)
Data Analytics Using Tableau (15 Hours)
R For Data Science (20 Hours)
Data Analytics Using Alteryx (18 Hours)

 

Contact Details:

Phone: +91 9580 740 740

Email: [email protected]

 

Rank# 2. Online Data Analytics Courses

2. Google

TechRatingsCourse Fee Level Duration Platform  
Google Sheets and SQL   4.8Free-$ 49/ MonthBeginner6 monthsCoursera

If you are a beginner, this course broadens your knowledge of Data Analytics. The course is highly rated by millions of learners. The entire content of this course is organized and easy to understand. You can actively interact with the active community for any queries that you might have throughout the course. The course will teach you how to use Data Analytical tools like SQL, R, and Tableau by which you will learn the skills to create your projects.

Syllabus of Online Data Analytics Courses:

The course is divided into 8 sub-courses, each focusing on using different statistical tools. If this one sounds interesting, keep on reading its syllabus;

Course 1: Foundations of Data

  • Introduction to Data Analytics and
  • SQL and Sheets

Course 2: Ask Questions to  Make Data-driven Decisions 

  • Problem-solving
  • Asking questions
  • Basics of Spreadsheets
  • Effective communication

Course 3  Preparing Data for Exploration

  • Data Types, Formats, and Models
  • Ethics of Data
  • Using spreadsheets for Databases
  • Introduction to Big Query
  • Data Security

Course 4: Cleansing Data from Dirty to Clean 

  • Data Integrity
  • Using SQL and spreadsheets to clean data
  • Resume/ career info

Course 5: Analyze Data Answer Questions 

  • Format and transform Data
  • Data Aggregation in Sheets and SQL
  • Learn about Tables, functions, and formulas.
  • Intermediate level SQL

Course 6: Art Visualization of Data

  • Introduction to data visualization concepts
  • Creating visualizations with Tableau
  • Develop Data stories
  • Creating presentations

 

Course 7: Data Analysis with R Programming 

  • R language and R Studio
  • Transform Data to R
  • Creating Visualizations with R
  • Making reports and docs from R analyses

Course 8: Google Data Analytics Capstone: Case Study 

Developing your capstone project displaying your portfolio and resume

  • Information on building a compelling portfolio

Though the entire course completion time is 6 months, the contents can be learned in a shorter time.  Many learners completed the entire course in 30 days. It all depends upon your background. Some may finish it in less time while others may take some time.

 

Rank# 3. Online Data Analytics Courses

3. IBM

TechRatingsCourse Fee Level Duration Platform  
SQL, Excel, Python, and Cognos Analytics    4.6$39 /Month

 

Professionals 11 MonthsCoursera

 

If you are a working professional in Data Analytics and want to get job-ready with professional skills then this is your slot. This course consists of 9 courses and is instructed by IBM professionals, and it comes under the top 5 online data analytics courses. The course will teach how to develop data analysis tools for real problems in businesses.

Using  SQL, Python, and Cognos Analytics learners will be able to cleanse, filter, and build advanced data dashboards and develop machine learning models. At the end of the course, learners will be working on a capstone project.

 

Rank# 5. Online Data Analytics Courses

4. Skillshare 

TechRatingsCourse Fee Level Duration Platform  
SQL

 

4.9$13.99 /Month

 

Beginner to Intermediate 5 hours 4 minutesSkillshare

 

Their online data analytics courses are focused on using SQL language to solve analytical problems with databases. Learners will be able to use SQL on projects.

The Online Data Analysis Courses Cover the Following Topics:

  • Introduction to Databases
  • Categories of SQL
  • Aggregate data
  • Entity Relationship Diagrams (ERD)
  • Extract transform and Load Data (ETL)
  • Introduction to Sales projects
  • Creating databases
  • Query flow
  • Kanban Boards
  • Project Management (Agile Methodology)
  • Set up SQL
  • Exporting results
  • Creating a report in Microsoft Excel

 

Rank# 5. Online Data Analytics Courses

5. Data Analyst Nanodegree

TechRatingsCourse Fee Level Duration Platform  
SQL and Python   4.7$399 /Month

 

Beginner to Intermediate 38 hoursUdacity

 

This Data Analysis course from Udacity is for learners having basic knowledge of SQL (Num Py and Pandas) and, Python. It’s a great course to learn how to work on large datasheets by having hands-on projects from around the world. The duration of the course is 4 months, and it covers statistical tools such as R, Python, and Tableau.

 

Online Data Analysis Courses Syllabus 

  • Introduction to Data Analysis
  • Practical Statistics
  • Data Wrangling
  • Data Visualization with Python

 

Every course on this list comes with a certificate after the course. Certificates are a good way to prove to yourself that you have completed a course and gained knowledge on that topic. Learners lacking past job experience should focus on developing their portfolio, knowledge, and aptitude.

 

FAQs

1. Are Data scientists and Data analysts the same?

Answer: Both Data Scientists and Data Analysts work on the same data. The only difference is Data analysts work on already established data to get insights while Data Scientists create new data with the help of scientific tools to solve complex level problems.

2. What is career growth after doing online data analytics courses?

After doing online data analytics courses, you can start working as a professional data analyst. Starting with the position of Data Analyst, you can move to Senior Analyst then Analytics Manager, and then Director of Analytics.

3. Is getting a certificate in Data Analytics worth it?

Ans; Yes, it is. Having a certificate in Data Analytics is a good way to prove to the prospective employer that you have completed a course and gained knowledge on that topic. You can opt for any of the above-mentioned online data analytics courses.

4. Who uses Data Analytics?

Answer; Data Analytics is now used in every industry. Regardless of a company’s size, data analytics is playing a huge part in decision-making processes understanding customer needs, and improving its products in a way that best suits its customers.

Top 11 Data Analytics Courses in Germany With Placement

In recent years, data analytics has emerged as a key source of competitive advantage. And when it comes to commercial digitization, Germany is one of the most advanced countries. German organizations are worldwide-oriented, particularly in the IT business sector. You might make a sensible career choice by enrolling in data analytics courses in Germany if you want to increase your job prospects both domestically and abroad. 

List of best data analytics courses in Germany

Data analysis aids businesses in numerous ways, including decision–making, increasing competition, enhancing customer experience, and streamlining operations. Most colleges that offer data analytics courses demand prospective students to have very strong backgrounds in math and computer science. This article lists the best data analytics courses in Germany with a campus-based learning system.

Look for the other best courses in Germany:

 

Why Should I Learn Data Analysis Courses in Germany

To begin with, let’s start by knowing what data analytics is. It’s the process of collecting, managing, and analyzing data to find patterns and other sorts of information. The information derived from these patterns acts like gold mines for businesses to make crucial decisions and study customer behavior toward their products and services. 

Based on those results, they modify or introduce new products to the market. The amount of money being invested in data science has skyrocketed with some high-profile companies around the world. Analytics is the way of the future, but they are also the way of the present, without a question! 

After being adopted by a wide range of industries, analytics are now utilized for anything from manufacturing plant predictive, and maintenance monitoring to airline route planning. Even sectors like retail, which you might not often identify with big data are joining in.  

Must check out here the best:

 

 

Top 11 Data Analytics Courses in Germany

 

Rank #1. Data Analytics Courses in Germany

1. IIM SKILLS

Beginning with their very first course in content writing back in the year 2015, IIM SKILLS is now in the top position in the world for offering a wide range of skill development & professional courses. Among their top-rated courses, the Data Analytics Course is highly recommended.

IIM SKILLS believes in reaching all learners who are willing to grow and achieve their professional goals.  Hence they chose an online platform so that they are not limited to a particular location. They also have the most budget-friendly cost for their courses with a zero-interest fee EMI payment option.

 

IIM SKILLS aims to reach the maximum number of students helping them achieve their professional goals, which is why they have 24*7 helpline services that not only handle course-related queries but also provide full assistance and career-bulging guidance.

These helplines are active and have a trained and dedicated team who are capable of dealing with every query. The pillar of every educational company to run successfully is their team of highly efficient mentors.

 

IIM SKILLS has the best team of faculty who are not only professionally experienced but are also domain experts. They constantly strive to train their student focusing more on practical teachings with assignments so that they already make their pass-outs career-ready.

Also Read: IIM SKILLS Data Analytics Course Review

The Types of Tools Covered with Data Analytics Course in Germany by IIM SKILLS:

  • Python 1 & 2
  • R
  • Basic & Advance Excel
  • VBA
  • Tableau
  • Alteryx
  • SQL
  • Power BI


Other Professional Courses from IIM SKILLS

Contact Details:

+919580740740, [email protected]

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Rank #2. Data Analytics Courses in Germany

2. Knowledge Hut. Munich, Germany

Course Name: Big Data Analytics Course Training

This course from Knowledge Hut exposes participants to how data analytics is used in organizations and the concepts of Hadoop Distributed File System (HDFS), understand customer needs make wise decisions, and analyze sentiments and techniques to find profitable company strategies. 

By better-comprehending market conditions, businesses can outperform their competitors. It helps organizations identify current trends and offer goods and services. 

Core Concepts of the Data Analysis Courses in Germany:  

  • Learning core concepts of Hadoop, HDFS (Hadoop Distributed File System), and MR  (Map Reduce )
  • Learn the components of HIVE, PIG, SCOOP, and FLUME 
  • Creation of batch analytics for UK news channels with the integration of Clickstream and Sentimental Analytics  

Course Syllabus:  

Module 1: Introduction to Big Data, Data Analytics, Challenges, and New Technologies  

  • Introduction to Hadoop, HDFS, Breakthroughs, and its Distributions  
  • Anatomy of the Hadoop Cluster  
  • Horton Network of Hadoop 
  • Cloudera DNA  MapR of Hadoop  

Participants also get hands-on experience in installing a virtual machine through a VM player and working on basic Hadoop commands.  

Module: 2 Different types and processes of Hadoop 

  • Name and Data node 
  • Secondary Node. 
  • Job and Task Tracker

Perks After Completing This Module: 

Participants can create a Unix Shell script to run each daemon at once and launch HDFS and MR independently.  

Module 3 Learn about HDFS (Hadoop Distributed File System):

  • Read and write files on HDFS  
  • Recognize functions of Name, Data, and Secondary Node in the HDFS structure.  
  • Methods to access HDFS  
  • Input Splits and Block  
  • Replication of Data  
  • Hadoop Rack  
  • What are Cluster Architecture and Block Placement? 

 

Perks You Get After Completing This Module: 

Participants create a shell script that can write and read HDFS files and replicate data on three levels.  

Module 4:  

  • How to Install HDFS Modes?  
  • Types of Mode: Local, Pseudo-distributed, and fully distributed mode.  
  • Installation and configuration of Pseudo mode 
  • Basic operations of HDFS files.  

Perks You Get After Completing This Module:  

After completing this module, participants will be installing a Virtual Box Manager to run in pseudo-distributed mode and various other configuration files.

Recommended Reads:

 

Module 5: Learn About Developer Tasks and Different Phases of Hadoop:  

  • The understanding of the life cycle of MR ion yarn and the cache concept  
  • API Concepts and different classes such as Driver, Mapper, Reducer, combiner, and practitioner class.  

Perks You Get After Completing This Module:  

Discover how to create MT jobs from scratch and create various mapper and reducer logic and 

  • Learn how to calculate an employee’s average salary if they fulfill particular criteria.  

Module 6 Ecosystem of Hadoop  

  • Significance of Pig in the World of Data 
  • Structure and Latin commands of Pig  
  • Functions of Pig UDF and Piggy Bank Library  
  • Learn to write flexible inputs to Pig scripts.  
  • Installation and configuration of pig in a cluster 
  • Difference between PIG, SQL, and MapReduce  
  • UDFs of Pig
  • Perks  
  • Hands-on training on how to access Pig commands using the Grunt Shell and other execution modes.  
  • Register with UDF operations in front of Shell.  

Module 6.2 Importance of HIVE 

  • Concepts, Architecture, and Installation  
  • Learn about external tables and Managed tables  
  • Adding Data to the HIVE  
  • Function of HIVE  
  • What is Bee UDF?  

Perks You Get After Completing This Module:  

  • Carry out HIVES queries in various modes.  
  • Create tables for internal and external use  
  • Run user-defined functions – Windows and Explode.  

Module 6.3 

  • Learn SQOOP  

Module 6. 4 HBASE  

Module 6.5 Learn OOZIE  

6.6 What is FLUME? 

  • Concepts, Architecture, Installation, and Configuration and execution.  

Module 7 Use of Pentaho as ETL Tool  

Perks You Get After Completing This Module:  

Practical assignment on how to use the Pentaho tool for Data Analytics  

Module 8 Integration of Hadoop’s Ecosystem into Data Engineering.  

Perks You Get After Completing This Module:  

  • Integration of MapReduce with HIVE and HBASE 
  • Integration of Java with Hive and HIVE with HBASE.  
  • Practical assignment on the integration of HIVE with PIG and HBASE.

This course is best for Data Architects, Project Managers, Data Scientists, Data Analysts, BI Analysts, and BI Developers.  

Phone: +442033320846   

Email: [email protected] 

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Rank #3. Data Analytics Courses in Germany

3. Technical University of Munich  

Course Name:  Data Engineering and Analytics, Munich Germany  

The course offered by TUM is one of the top training in Germany. It was founded in 1868 and provides Data Analysis, Data Engineering, and Analytics as three parts of the course. The course is designed to enable students to design and plan solutions for the industry grade and build a strong foundation for research.  

Prerequisites for This Course: 

  • The applicant must hold a bachelor’s degree in informatics or similar.  
  • Knowledge of foundations of informatics, programming, algorithms, and databases. 
  • Knowledge of the English language is a must.  

The course has Mandatory, Elective, and Elective Interdisciplinary Modules. We have mentioned key topics of the Mandatory module. 

Module A Mandatory: 

  • Foundations of Data Engineering  
  • Foundations in Data Analytics  
  • Seminars and Practical Courses  

Module B Electives:  

  • Data Engineering  
  • Advanced Topics in Data Engineering  
  • Data Analytics  
  • Algorithms for Uncertainty and Quantification  
  • Data Analysis, Computational Statistics, and graphical Models 
  • High dimensional Statistics  
  • Probability theory 
  • Liner and  Non-Linear optimization  

Module C – Electives:  

  • Master Informatics of Area and Algorithm  (ALG) 
  • Computer Graphics and Vision  (CGV) 
  • Databases and Information Systems (DBI) 
  • Digital Biology and Digital Medicine (DBM) 
  • Engineering Software-intensive systems  ( SE) 
  • Formal Methods Applications  (FMA) 
  • What is Machine Learning and Analytics (MLA)  
  • What is computer architecture?  And Computer Networks and Distributed Systems (RRV) 

Phone:  +498928922245 

Email[email protected]

 

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Rank #4. Data Analytics Courses in Germany

4. Excelr Training  

Course Name:  Data Analytics Course in Collaboration with IBM, Germany    

This course offered by ExcelR and tech conglomerate IBM is designed to give students high-quality up-skilling opportunities. The course meets the needs of the market as well as individuals looking to advance their careers in the digital field where just coding is not the norm. At the end of the course, participants get certified in IBM-powered Data Analytics. 

Data Analysis Courses in Germany Syllabus:

The course covers technologies of Excel, Tableau, SQL, and the Basics of Python & R. Students also get a hands-on assignment to work on projects and apply those concepts.  

  • Business Statistics  
  • Basic to Advanced Excel
  • My SQL  
  • Tableau  
  • Basic Python and R  
  • Power BI  

Phone  +1 281 971 3065 (USA)

 

Rank #5. Data Analytics Courses in Germany

5. Berlin School of Business and Innovation  

Course Name:  MSc in Data Analytics  

In collaboration with the University of Creative Arts, the Berlin School of Business and Innovation aims to provide MSc in Data Analytics. The course is an 18-month post-graduate program that gives students the fundamental information to work in data analytics.

The course is offered on campus with full access to cutting–edge amenities. The course is ideal for students who want to learn the principles of data Analytics to pursue a career in computer science or data analytics.  

Data Analysis Courses in Germany Syllabus:

Module 1 

  • Fundamentals of Data Analytics  
  • Machine Learning  
  • Python 
  • Predictive Analysis  

Module 2  

  • Database Management Systems 
  • Enterprise Data Warehouse  
  • What is Big Data Analytics?  

Module 3  

  • Tableau 
  • Visualization And Story-Telling  

Module 4

  • Caps stone Project  

Phone:  493058840959 

Email[email protected] 

 

Rank #6. Data Analytics Courses in Germany

6. Keystone Master Studies  

Course Name: MSc Data Analytics and Information System  

In this course, you’ll develop the capabilities you need to grasp the opportunities that big data offers. By gaining this knowledge, you will be able to apply data-handling strategies to inform businesses and guarantee that the information systems at your workplace align with your goals and strategies.  

Passionate IT managers looking to establish a career in data analytics can take advantage of big data opportunities with this course. The knowledge gained from this course can give them an advantage over other IT professionals and competitors.   

Prerequisite of This Course:

  • A 2:2 UK honors degree or GPA of above 60% for a 4-year bachelor’s degree from Pakistan  
  • IELTS score of 6.5 or above 

Awarding body: Arden University of Berlin 

Data Analysis Courses in Germany Syllabus:

  • Data Designing  
  • Decision-Making and Data Handling  
  • Aligning IS and Business Strategy
  • Monitoring Trends and Technology  
  • Research Project 

 Phone:  +498005895337 

Email[email protected] 

 

Rank #7. Data Analytics Courses in Germany

7. Ludwig Maximilians University (LMU) 

Course Name: Machine Learning and Data Analytics in Finance and Accounting    

This course aims to enable you to leverage basic machine learning methodologies and data analytics methods for your professional advancement. Participants will discover how to automate time-consuming operations including the classification of analyst conference calls into economically significant information. There is no prerequisite for this course, and all essential programming abilities are taught in this course.  

Check the Course Syllabus  

Courses 1 and 2  

Python  

  • Basic concepts of Python and Data Analysis   
  • Learn how to import and clean data  
  • Process Natural languages in Python  

Course 3 

Machine Learning  

  • Learn what supervised and unsupervised machine learning  
  • Evaluate the prediction model  

Course 4  

Data Analytics  

  • Learn Data Visualization 
  • What is Data description 
  • Statistical Analysis   

For Registration:  

Phone  +498921800 

Email: [email protected]

 

Rank #8. Data Analytics Courses in Germany

8. Frankfurt School of Finance and Management  

Course Name: Master’s in Data Analytics and Management  

This course from the Frankfurt School of Finance and Management equips you with the expertise and abilities to steer data-driven organizations through periods of digital transformations.

This course is best for managers who encourage goal-driven innovation and inspire organizational change using disruptive technologies to manage digital transformation in a world that is always changing. You will learn how to use data to change a company model into a data-driven organization.

Prerequisites of This Course  

  • AN Undergraduate degree, or Diploma
  • IELTS 7.0 or TOEFL IBT 90   
  • Candidates who have earned an English language degree and spent more than a year in an English-speaking nation are eligible for language competency waivers.  

Data Analysis Courses in Germany Syllabus:

  • Week 1 Data Boot Camp  
  • Week 2   Machine Learning Boot Camp   
  • Week 3 Business Model: Disruptive    
  • Week 4 Business Model:  Optimization   
  • Week 5 Organizational Transformation  
  • Week 6 Experiential Learning and Digital Learning  
  • Week 7 Blockchain in Business 

Phone:  069154008565

 

Rank #9. Data Analytics Courses in Germany

9. 8 RWTH Aachen University 

Course Name: MSc. Data Analytics and Decision Science   

This master’s degree program is designed to learn how to combine machine learning and deep learning techniques with mathematical optimization, algorithms, and simulation techniques to create value in different application areas.

The course comes into a schedule of core courses supplemented by a selection of elective courses for in-depth studies. Seven essential building elements make up the two-year degree program which can be altered to fit your requirements.

Requirements: 12 months of professional experience.

This course also lets you sign up for a free German language course. 

Course Syllabus  

Semester 1  

DDS Essentials  

  • Learn the essentials of Statistics and Mathematics   
  • Algorithms and Data Structures  
  • Data Analytics – Learn about Predictive Modeling and Machine Learning  

Semester 2 

Decision Science  

  • Learn how to optimize models, Linear, and Integers
  • Design and Analysis of Algorithms  
  • Heuristic Optimization  

Analytics Project  

  • Practical Assignments on machine learning and optimization techniques.  
  • Report presentation to practice and scientific audience.  

Semester 3 

Application of Skills  

  • Applying learned skills for Digital Operations and Supply Chain Management (SCM) 
  • Optimization of Logistics Systems and to economically model Energy and Climate Systems. 

Semester 4 

  • Master Thesis  
  • German language Course  

To enroll, contact their Team Leader – MMsMandy Bollinger  

Phone:  +49 241 8020010

 

Rank #10. Data Analytics Courses in Germany

10. Steinbeis University, School of Management and Innovation

Course Name: MaMasterf Science in Data Analytics & Artificial Intelligence  

Location: Berlin, Germany  

This Master’s program focuses on how to integrate data with relevant business insights. You will develop in-depth knowledge of data technologies, data applications, strategies, and data-driven decision-making in a corporate environment both operationally and strategically. You will learn how to optimize company operations and how to use a variety of statistical tools to solve complex challenges faced by businesses. 

Prerequisites for Admission 

  • Bachelor’s degree 
  • IELTS 6.0 or PTE 56 or Duo lingo 100 
  • TOEFL 80 or Cambridge Advanced 

Course Syllabus  

  • Management and Entrepreneurship 
  • Project Management
  • Understanding Market and Consumer Behaviour  
  • Research Methods  
  • Statistics  

Specialization Courses 

  • Data Economics and Ethics 
  • Data Technology  
  • Data Applications, Methods, and Processes 

Besides this, the university offers the Launch Pad Program, where they train learners in analyzing profiles, personal branding, teaching German cultural codes, preparing a resume, and interviews for job placements with salary negotiations and invitations to networking events.   

Students who prove academic achievement and exceptional interpersonal skills can earn up to 25% off their entire tuition fees through the Steinbeis Foundation Scholarship Fund.  

 

Rank #11. Data Analytics Courses in Germany

11. Stiftung Univetsität Hildesheim

Course Name:  International Master’s Program in Data Analytics  

The International Master’s Program in Data Analytics combines a comprehensive introduction to cutting-edge research in machine learning, big data analytics, and analytical technologies. These techniques are designed for students to build their knowledge for modeling and analyzing complex systems in businesses.  

Course Syllabus: 

Semester 1  

  • Machine Learning  
  • Techniques for Optimization  
  • Programming of Machine Learning  
  • Data Analytics Seminars  

Semester 2  

  • What is Big Data Analytics  
  • Advanced Processes of Machine Learning  
  • Data Protection  
  • Seminars for Data Analytics (Part 2)  
  • Project 1  

Semester 3  

  • Optimal controlling and Planning  
  • Methodological Specialization  
  • Data Analytics Seminars (Part III)
  • Project- 2 

Semester 4 

  • Master Thesis on projects. 

 

Application Modules (AM) 

  • Computer software Engineering  
  • Media Systems  
  • Advanced Marketing and Logistics  
  • Seminars on Business Studies  
  • Processing Natural Languages 
  • Lab Courses  
  • Geographic Info Systems  

Course Structure:

 2-year master’s Program, structured as 65% methodological, 10% application, and 25% master thesis.  

Prerequisites:   

  • Bachelor’s Degree in Computer Science, IT, Math, or related fields.
  • TOEFL certificate with a test score of 61 or above or German Abitur  

Students completing this course will become highly competent to work as research scientists, Data engineers, machine learning scientists, and analysts for Business intelligence. 

Phone: +49512188340388 

Email[email protected]

Data Scientist or Data Analyst: Which One is For You?   

Businesses are generating massive profitability and growth from the results and insights gained from data available within the firm. This is the major reason that the number of jobs for data engineers has increased dramatically in every company.  

Data Science has evolved into the most important component of any business, it helps us in identifying meaningful insights by studying raw and unstructured data. This field focuses on seeking answers to questions that companies are asking to grow and make profits.  

Data Analysts process the given datasets and carry out various statistical analyses to get actionable insights. In other words, Data Analysts work on solving existing business challenges with the use of data that is available by presenting the facts in a visual context that everyone can understand.  

Frequently Asked Questions    

Q1. Is Germany good for Data Analytics? 

When it comes to commercial digitalization and digital public services, Germany is one of the most advanced countries, even though Big Data and Data Science are still relatively young academic fields, there is a huge demand for competent Data Analysts in Germany.

Q2. Is it possible for a Data Analyst to work as a Data Scientist? 

Since both fields work on data, a bachelor’s degree is required for both disciplines.  After becoming a data analyst, you can advance to become a data scientist by upgrading your mathematical and programming skills and getting an advanced degree to get started as a Data Scientist.

Q3. What are the most in-demand jobs for Data Analysts in Germany?  

Data Analysis, machine learning, Python, deep learning, research, and related careers are the most in-demand jobs in Germany.

Conclusion 

Data Analytics has a long and illustrious history in Germany. The nation is home to some of the top data science researchers, teachers, and students in the world and its universities provide some of the top data analytics courses in Germany. If you want to work in this industry, Germany is a wonderful place to consider enrolling in data analytics courses. Since data science ecosystem in the nation is booming and offers many prospects for professional advancement.