Data Science

Language:	English
Location:	Munich, Garching near Munich
Duration:	6 days in 4 weeks
Start:	30.06.2025
Cost:	3,500 EUR
ECTS:	2

Apply now

Given the massive growth of available information, processing and analyzing data to make strategic decisions is crucial for companies and organizations. Well-trained data scientists play a central role in this task.

Our certificate program offers a unique opportunity to learn modern computational methods for data analysis, statistical prediction, and visualization. Developed in close collaboration with renowned professors from TUM’s Department of Mathematics and experts from the field, our program offers a comprehensive curriculum that combines theoretical knowledge with practical application. With a strong focus on current research findings and real-world challenges, our learning objectives are designed to equip you with the necessary skills to succeed in the fast-paced world of data analytics. Our aim is to provide you with substantial background knowledge about the main idea, technical background, and use cases of modern machine learning techniques.

3 ECTS Points.

Quick Info

Here you will find all the information you need for this course.

Navigation

Benefits

01

1

Introduction to Data Science and Machine Learning fundamentals

Gain a solid foundation in data science and machine learning, equipping you with essential skills to analyze data and develop predictive models.

02

2

Motivation, technical explanations, and case studies by experienced instructors

Benefit from expert-led sessions that combine theoretical insights with real-world applications, ensuring a comprehensive and engaging learning experience.

03

3

Professional networking with participants from various industries

Expand your professional network by connecting with peers from diverse backgrounds, fostering collaboration and new career opportunities.

04

3

Exclusive TUM certification

Receive a prestigious TUM certification that validates your expertise in data science and machine learning.

Program Overview

You can find all the important information about the certificate program here. Below you can find out the objectives of the program, the exact details of the process, what you will learn and which lecturers will teach you the content.

Learning Objective
Here you will find information on the aims of this course and its content.

The certificate program is designed to provide you with a solid understanding of modern computational methods for analyzing, predicting, and visualizing data. You will learn fundamental statistical principles, broadly applicable statistical methods, modern prediction methods from machine learning, and optimization and randomization tools through a combination of theoretical concepts and practical application. The program aims to equip you with the skills to solve big data analytical problems and make informed decisions based on data.

Details
Here you will find information on dates, requirements and other general conditions for the certificate program.

Program:

Data Science

Graduation:

Participants receive a certificate from the Technical University of Munich after successfully passing the final exam.

Academic Responsibility:

Prof. Dr. Matthias Scherer, Chair of Risk and Insurance, TUM
Prof. Dr. Mathias Drton, Chair of Mathematical Statistics, TUM

Target group:

Experts who want to expand or deepen their expertise in data science, e.g., because they currently hold or aspire to a position as a data scientist/analyst in consulting, finance, insurance, or technology.

Program fee:

3,500 Euro*

Language:

English

Discounts:

10% discount for TUM Alumni and members or employees of our strategic cooperation partners (see below).

Dates:

30.06 – 01.07.2025 + 11-12.07.2025 + 25-26.07.2025

Application deadline:

May 30, 2025

Study location:

Munich, Garching near Munich

Format & Timing:

Part-time, presence, 6 days in 4 weeks

Admission requirements:

Participants should have a sound mathematics and computer science education or a closely related field.

Credibility:

3 ECTS Points

* In our experience, tax benefits in Germany help many of our program participants to finance their education, as they can declare up to 50% of tuition fees and program-related travel expenses in their tax return. Please speak to your tax advisor for an assessment of your situation. This may also apply to participants of our programs who reside outside of Germany; please clarify the situation with the local tax authorities.es in your country of residence.

Lecturers
Get to know our experienced lecturers who will teach you the certificate content and with whom you will work.

Prof. Ph.D. Claudia Czado,
Chair of Applied Mathematical Statistics/ MDSI, TUM

Prof. Dr. Mathias Drton,
Chair of Mathematical Statistics/ MDSI, TUM

Dr. Stephan Haug,
Chair of Mathematical Statistics, TUM

Prof. Dr. Blanka Horvath,
Chair of Mathematical Finance/ MDSI, TUM

Prof. Dr. Oliver Junge,
Chair of Numerics of Complex Systems, TUM

Prof. Dr. Felix Krahmer,
Chair of Applied Numerical Analysis/ MDSI, TUM

Prof. Dr. Christina Kuttler,
Chair of Mathematics in Life Sciences, TUM

Cláudio Mayrink Verdun,
Chair of Applied Numerical Analysis, TUM

Prof. Dr. Matthias Scherer,
Chair of Risk and Insurance, TUM

Prof. Dr. Elisabeth Ullmann,
Chair of Scientific Computing and Uncertainty Quantification, TUM

Prof. Dr. Michael M. Wolf,
Chair of Mathematical Physics, TUM

Structure
Find out here how the course is structured and what the individual modules of the certificate program contain.

Modul 1: Computing with Data

An introduction to R, R Studio, and tidyverse
Data management
Data visualization
Creating reports with markdown toolsR interfaces with other languages (julia, python)

Modul 2: Statistical Foundations of Data Science

Designing experiments and modeling data
Linear regression
Likelihood and Bayesian inference
High-dimensional regression

Modul 3: Teil I: Basics of Supervised Learning

Generative and discriminative approaches to classification and regression
Logistic regression
Generalized linear models
Classification with logistic regression and discriminant analysis

Modul 3: Teil II: Basics of Unsupervised Learning

Unsupervised Learning
Clustering with k-means/k-medians, mixture models, stochastic block/ball models
Dimension reduction with PCA/SVD
Manifold Learning
Autoencoders

Modul 4, Teil I: Predictive Approaches in ML

Kernel methods:

support vector machines,
Gaussian processes
Decision trees

Ensemble methods:

boosting and random forests

Modul 4, Teil II: Predictive Approaches in ML

Neural networks and deep learning:

Training neural nets
Approximation theory
Network architectures

Reinforcement learning:

Markov decision processes
deep RL

Modul 4, Teil II: Predictive Approaches in ML

Neural networks and deep learning:

Training neural nets
Approximation theory
Network architectures

Reinforcement learning:

Markov decision processes
deep RL

Modul 5: Optimization and Randomization for Large-Scale Data Analysis

Non-linear optimization
Convex optimization
Stochastic gradient methods
Randomization and sketching

Modul 6: Case Studies & Final Exam

Presentation of case studies that exemplify applications in selected areas:

Financial and Actuarial Math
Examples from TUM Data Innovation Lab
BioTech.

Assessment of your participation in the program in a pass/fail exam

Apply now

Partners

The program was created in collaboration with the Faculty of Mathematics at the TUM School of Computation, Information and Technology, Technical University of Munich. Learn more here.

Your contact

Franziska Sennebogen

Program Manager

Phone: +49 89 289 26761

Get in touch

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Data Science

Quick Info

Benefits

01

1

Introduction to Data Science and Machine Learning fundamentals

02

2

Motivation, technical explanations, and case studies by experienced instructors

03

3

Professional networking with participants from various industries

04

3

Exclusive TUM certification

Program Overview

Partners

Application for Data Science

Your contact

Other programs that might also interest you

Executive MBA in Business & IT

Digital Transformation & Entrepreneurship

Quantum Technologies Course – Overview for Managers and Leaders