Best Data Science Course in Germany in 2021

Data Science in Germany

Germany is one of the countries in the world that is known for its robust education system. According to the OECD/PISA study in 2015, Germany ranked 16th in mathematics and science and 11th in reading. Cultural immersion in Germany is also a rich experience that provides exposure to international education and work practices making it one of the most desirable education destinations in the world. Therefore, candidates who are looking for a promising career can consider studying in Germany. One of the courses in Germany that has been much in demand in recent years is Data Science.

Data Science is a mix of mathematics, algorithms, business acumen, tools, and machine learning techniques that help in finding out the hidden patterns from raw data. These data further help in forming big business decisions. Data Scientists examine the questions that need to be answered. They also identify the source from where the related data can be found. Data Scientists work with businesses to manage and analyze huge amounts of unstructured data.

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Why to pursue Data Science course in Germany?

Germany tops the list of countries that are good for studying data science. Let us discuss why:

  • There are some of the best universities offering data science course in Germany
  • Germany is one of the countries in the world that offers the highest salary to data scientists
  • Data Science is on the rise in Germany as the use of data in companies and organization are increasing
  • Some universities in the country enable candidates to learn data science online
  • German Universities offers a well-rounded curriculum in collecting and processing large statistical data, besides giving a deep insight into the data analytics.

Best Data science course in Germany- Master Degree in Data Science

As the world is moving towards big data, an increasing number of students are looking for a good course in data science in countries like Germany which is popular for offering top-notch data science courses. upGrad is the best foreign higher education platform through which potential candidates can enroll for Master in Data Science in Germany. The duration of the course is 2 years, in which the candidate has to study online with IIIT Bangalore in the first year. However, the candidate will be required to travel to Germany and complete the course from the campus of IU Germany in the second year. The course fee in Germany can be paid quarterly. The candidate needs to deposit a certain amount in the German Bank account, which will serve as proof of funds for living as well as food expenses.

Pursuing the master’s in Data Science from IU Germany is cost-saving and the average salary after completing the course in Germany is equivalent to INR 45 lac. Candidates are also eligible for a Work Visa application after they complete graduation.

Who are eligible?

As the candidates start the program online from IIIT Bangalore, the name of the course will be Executive PG Program in Data Science. The eligibility criterion for this course is a Bachelor’s Degree with at least 50% or equivalent pass marks. There is no coding experience required to enroll in this course.

The course that the candidates will do next year in Germany is Master Degree in Data Science. As the eligibility criterion is concerned, the candidates have to successfully complete the Executive PGP from IIIT Bangalore.

Course structure and duration

The duration for the program in Masters in Data Science in Germany is 2 years. These two years are further divided into two parts, in which the first one can be done from IIIT Bangalore online. In the second year, the candidates have to go to Germany to complete their course at IU Germany.

Read More: Germany – A dream overseas studies destination to many

Let us discuss the course structure:

Executive PG Programme in Data Science: IIIT Bangalore

1.Pre-Programme Preparatory Content (4 weeks)

  • Data Analysis in Excel
  • Analytics Problem Solving

 

2.Data Toolkit (14 weeks)

  • Introduction to Python – I
  • Introduction to Python – II
  • Programming in Python
  • Data Analysis using SQL
  • Python for Data Science
  • Visualization in Python
  • Exploratory Data Analysis
  • IMDb Movie Assignment
  • Maths for Data Science
  • Inferential Statistics
  • Hypothesis Testing
  • Advanced SQL
  • Credit EDA Case Study

 

3.Machine Learning (9 weeks)

  • Introduction to Machine Learning and Linear Regression
  • Linear Regression Assignment – Bike Sharing Systems
  • Logistic Regression
  • Unsupervised Learning: Clustering
  • Business Problem Solving
  • Clustering Assignment (Optional)
  • Case Study: Lead Scoring

 

4.Specialisation- Data Science Generalist (22 weeks)

  • Tree Models + Boosting (Optional)
  • Model Selection & General ML Techniques
  • ML Lab I: Classification
  • Principal Component Analysis
  • Advanced Regression – I
  • Advanced Regression – II and ML Lab II: Regression
  • Text Analytics & Processing + Text-Based Predictive Modelling
  • Basic Visualisation using Tableau
  • Data Storytelling
  • Business Case Study
  • Data Modelling
  • SQL Weeklong Lab
  • Advanced SQL – Week II
  • Algorithm Analysis + Recursion
  • Searching and Sorting (Divide and Conquer included)
  • Data Structures – Sets, Dictionaries, Stacks, Queues
  • Python – OOPS
  • Python Weeklong Lab
  • Capstone Project

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5.Specialisation- Deep Learning (25 weeks)

  • Tree Models
  • Model Selection & General ML Techniques
  • Principal Component Analysis
  • Advanced Regression
  • Advanced Regression Assignment
  • Bagging and Boosting
  • Time Series Analysis
  • Telecom Churn Case Study
  • Introduction to Neural Networks
  • Neural Networks Assignment
  • Convolutional Neural Networks – Introduction and Industry Applications
  • Recurrent Neural Networks
  • Gesture Recognition
  • Capstone Project

 

6.Specialisation- Natural Learning Processing (25 weeks)

  • Data Modelling
  • SQL Best Practices
  • SQL Assignment: IMDb Movies
  • Advanced Excel
  • NoSQL Databases and Best Practices
  • Introduction to Big Data and Cloud
  • Hive and Querying
  • Hive Case Study
  • Visualisation using Tableau
  • Sports Analytics – IPL Visualisation Assignment
  • Visualisation using PowerBI
  • Visualisation using Plotly
  • Data Storytelling
  • Plotly Case Study
  • Capstone Project

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7.Specialisation- Business Analytics (25 weeks)

  • Tree Models
  • Time Series Forecasting
  • Retail-Giant Sales Forecasting Assignment
  • Model Selection & General ML Techniques
  • SQL Best Practices
  • Advanced Excel
  • Telecom Churn Case Study
  • Structured Problem Solving using Frameworks
  • Structured Problem Solving Assignment
  • Operations Research
  • Data Storytelling
  • Operations Research Case Study
  • Capstone Project

 

8.Specialisation- Data Engineering (27 weeks)

  • Introduction to Big Data(Optional)
  • Introduction to Cloud and AWS Setup
  • Introduction to Hadoop and MapReduce Programming
  • MapReduce Programming Assignment (optional)
  • Data Management and Relational Database Modeling
  • NoSQL Databases and Apache HBase and NoSQL Databases and MongoDB(Optional)
  • Data Warehousing (Optional)
  • Data Ingestion with Apache Sqoop and Apache Flume
  • Hive & Querying
  • Hive Assignment (optional)
  • Amazon Redshift
  • Introduction to Apache Spark
  • NYC Parking Assignment (Optional)
  • Project: ETL Data Pipline
  • Optimizing Spark for Large Scale Data Processing
  • Apache Flink(Optional)
  • Real-Time Data Streaming with Apache Kafka
  • Real-Time Data Processing using Spark Streaming
  • Stock data Analysis Assignment (Optional)
  • Building Automated Data Pipelines with Airflow
  • Analytics using PySpark
  • Classification Assignment (Optional)
  • Project: Real Time data processing
  • Capstone Project

 

9.Specialization- Business Intelligence/Data Analytics (25 weeks) 

  • Data Modeling
  • SQL Best Practices
  • SQL Assignment: IMDb Movies
  • Advanced Excel
  • NoSQL Databases and Best Practices
  • Introduction to Big Data and Cloud
  • Hive and Querying
  • Hive Case Study
  • Visualization using Tableau
  • Sports Analytics – IPL Visualization Assignment
  • Visualization using PowerBI
  • Visualisation using Plotly
  • Data Storytelling
  • Plotly Case Study
  • Capstone Project

 

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Master Degree in Data Science: IU Germany

1.Semester  3 (30 weeks)

  • Cyber Security and Data Protection
  • Case Study: Model Engineering
  • Software Engineering for Data Intensive Sciences
  • Elective B
  • Seminar: Current Topics in Data Science

 

2.Semester 4  (30 weeks)

  • Master Thesis & Colloquium

Career opportunities

Learning Data Science can be a great way to boost the career of many candidates and even facilitate career track changes. Here are some career venues that become available after the successful completion of data science courses.

  • Machine Learning Engineer
  • Data Architect
  • Statistical Analysis
  • Data Engineer
  • Data Scientist
  • Data Analyst
  • Python Engineer

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While pursuing the course through upGrad, the candidates will get access to more than 400 hours of recorded content, over 7 case studies, and projects. They can also attend more than 10 live sessions and use over 6 tools and software. On completion of this course, the candidates will receive dual certification, which includes an Executive PGP from IIITB and a Master degree from IU, Germany. Many opportunities are present for the students who want to build their career in the field of data sciences, through the upGrad Abroad program. The best part about the Data Science course in Germany is that the students can gain international exposure and that also reflects positively in their resume.

Many exclusive job opportunities in Germany are available for the students who will complete their education in Germany. The German education system is well known for the STEM disciplines and that is why the students from India have great prospects pursuing their education in these fields. As data sciences are one of the most up-and-coming fields of work, the students can make a valuable contribution in this field making their mark in the world.

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