Data Science

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

Quick Info

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

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.
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.

Program:

Data Science

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.

Academic responsibility:

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

Format & Timing:

Part-time, presence, 6 days in 4 weeks

Study location:

Munich, Garching near Munich

Language:

English

Dates:

TBA

Admission requirements:

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

Graduation:

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

ECTS:

3 ECTS

Program fee:

3,500 EUR*

Discounts:

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

* 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.  
Prof. Dr. Mathias Drton,
Chair of Mathematical Statistics/ MDSI, TUM
Dr. Stephan Haug,
Chair of Mathematical Statistics, TUM
Prof. Dr. Oliver Junge,
Chair of Numerics of Complex Systems, TUM
Prof. Dr. Matthias Scherer,
Chair of Risk and Insurance, TUM
Prof. Marie-Christine Düker,
Department of Statistics and Data Science, Friedrich-Alexander University
Marco Rauscher,
Chair of Mathematical Finance, TUM
Prof. Dr. Elisabeth Ullmann,
Chair of Scientific Computing and Uncertainty Quantification, TUM
Prof. Dr. Michael M. Wolf,
Chair of Mathematical Physics, TUM
Prof. Dr. Christoph Knochenhauer,
Financial Mathematics, TUM School of Computation, Information and Technology
Module 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)
Module 2: Statistical Foundations of Data Science
  • Designing experiments and modeling data
  • Linear regression
  • Likelihood and Bayesian inference
  • High-dimensional regression
Module 3: Part 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: Part 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
Module 4, Part I: Predictive Approaches in ML
Kernel methods:
  • support vector machines,
  • Gaussian processes
  • Decision trees
Ensemble methods:
  • boosting and random forests
Module 4, Part II: Predictive Approaches in ML
Neural networks and deep learning:
  • Training neural nets
  • Approximation theory
  • Network architectures
Reinforcement learning:
  • Markov decision processes
  • deep RL
Module 4, Part II: Predictive Approaches in ML
Neural networks and deep learning:
  • Training neural nets
  • Approximation theory
  • Network architectures
Reinforcement learning:
  • Markov decision processes
  • deep RL
Module 5: Optimization and Randomization for Large-Scale Data Analysis
  • Non-linear optimization
  • Convex optimization
  • Stochastic gradient methods
  • Randomization and sketching
Module 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

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.

What Our Students Say

  • The Data Science program was an excellent refresher that reconnected me with the close relationship between computer science and mathematics. In just six days, an impressively broad spectrum was covered – from R fundamentals and statistical foundations to advanced machine learning methods and deep learning architectures. I particularly valued the well-balanced combination of theoretical concepts like Bayesian inference with practical applications in reinforcement learning and optimization methods. An intensive program that provides comprehensive insights into modern data-driven approaches.

    Ing. Valmir Bekiri
    BSc, MSc

Info Sessions

Learn more about our certificate program Data Science. The info session takes place once a year, a few months before the program starts. The dates will be announced in due time.

Request form for certificate programs Executive & Professional Education

"*" indicates required fields

Title
Form of address*
Newsletter
Declaration of Consent*

  • Your contact

    Berk Baltaci
    Program Manager
    Phone: +49 (0) 89 289 26752
    GET IN TOUCH

    Request form for certificate programs Executive & Professional Education

    "*" indicates required fields

    Title
    Form of address*
    Newsletter
    Declaration of Consent*

Other programs that might also interest you

  • Digital Twins for Cities

    A great advantage is the simple and clearly understandable visualisation of complex calculation results in the models. In this way, they provide reliable support for citizen participation and decisions on improving mobility flows, meeting climate targets, developing new construction areas or implementing security concepts.

  • Digitalization in Aeronautics and Space

    Digitalization is changing our society and the working world, creating new processes and radically altering existing workflows.The three-part MOOC series “Digitalisation in Aeronautics and Space” is thus devoted to examining the transformations that have already occurred and forthcoming likely changes.

  • Digital Transformation & Entrepreneurship

    Discover how to lead in today’s digital landscape with our “Digital Transformation & Entrepreneurship” certificate program. Gain a profound understanding of digital business models and processes, equipping you with the skills to navigate and drive successful transformations.