PROGRAM:

B. Eng. Digital Industrial Engineering

MODE:
Full-time, On-site
LEVEL:
Bachelor of Engineering
LANGUAGE :
English
DURATION :
7 semesters
LOCATION:
Munich, Siemens Neuperlach Campus
CREDITS :
210 ECTS
PRICE:
4.800 € / Semester
START DATE:
March 2026
October 2026

Discover the dynamic field of the Digital Industrial Engineering with our specialized Bachelor of Science program. Our program offers a variety of popular specializations, allowing you to customize your education to align with your interests and career goals.

This program is being prepared for launch in October 2026.

Specialisations

Specialisations

Robotics and Automation

Focuses on designing and programming robots to perform tasks autonomously.

Computer Vision

Deals with how computers can be made to gain understanding from digital images or videos.

Natural Language Processing

Concentrates on the interaction between computers and human languages, enabling machines to understand and process natural language.

Big Data Analytics

Involves processing and analyzing large datasets to uncover patterns, trends, and insights.

Machine Learning and AI

Focuses on developing algorithms that enable computers to learn from and make decisions based on data.

Why Digital Industrial Engineering at MUDT:

Holistic curriculum integrating engineering and digital technologies

Project-oriented learning with hands-on applications

Faculty comprising industry experts and seasoned engineers

State-of-the-art labs and collaborative spaces for practical exploration

Emphasis on Industry 4.0, automation, and smart manufacturing

Study plan:B. Eng. Digital Industrial Engineering

Below is a semester-by-semester breakdown of the study plan for the Digital Industrial Engineering program, focusing on foundational knowledge, advanced specialization, and practical experience.

Summary of Total ECTS

Core Modules: 124 ECTS
Elective Modules: 48 ECTS
Internship: 30 ECTS
Bachelor Thesis: 8 ECTS
Semester 1 :
Semester 1:
30 ECTS
  • Mathematics (Calculus & Linear Algebra)
  • Scientific Working
  • Network and Internet Technologies
  • Software Applications and Technology
  • Basics of Programming with Python
  • Personal Development – Intercultural Communication
  • Foreign Languages I
Semester 2 :
Semester 2:
30 ECTS
  • Basics of Database
  • AI and Machine Learning
  • Object-Oriented Programming
  • Operating Systems
  • Managing Projects and Tasks
  • Career Planning
  • Foreign Languages II
Semester 3 :
Semester 3:
30 ECTS
  • Software Engineering Techniques I
  • Probability and Statistics
  • Deep Learning
  • Elective I
  • Elective II
  • Personal Development – Teaming Up
Semester 4 :
Semester 4:
30 ECTS
  • Data Mining & Data Warehouse
  • Natural Language Processing & Large Language Models
  • Big Data Analytics
  • Elective III
  • Elective IV
  • ESG and Sustainability
Semester 5 :
Semester 5:
30 ECTS
  • Computer Vision
  • Cloud Computing
  • Reinforcement Learning
  • Elective V
  • Elective VI
  • Career Planning II
Semester 6 :
Semester 6:
30 ECTS

Internship

Semester 7 :
Semester 7:
30 ECTS
  • Bachelor Thesis
  • B.Sc. Seminar
  • Elective VII
  • Elective VIII
  • Business Ethics and Entrepreneurship

Qualification Goals

01

Develop a strong foundation in engineering principles and practices.

02

Gain proficiency in programming and software development.

03

Acquire the ability to analyze and interpret complex data.

DAI1

Master the core concepts of data science and AI, including machine learning, deep learning, and big data analytics.

DAI2

Develop skills in specialized areas such as NLP, computer vision, and robotics.

DAI3

Apply theoretical knowledge to real-world problems through internships and projects.

P1

Enhance critical thinking and problem-solving skills.

P2

Foster teamwork and collaboration through group projects and activities.

P3

Promote ethical considerations and social responsibility in the application of AI and data science.

Career Paths:

Graduates with a Bachelor of Engineering in Data Science and AI can expect competitive salaries and strong job growth in Germany. Entry-level data scientists typically earn between €50,000 and €60,000 per year, while experienced professionals can earn upwards of €90,000

Explore diverse career paths available to Digital Industrial Engineering graduates, including:
{ Industrial Engineer } { Automation Specialist } { Manufacturing Technologist } { Supply Chain Analyst } { GenAI Systems Engineer }

Industry Cooperation

Faculty Expertise:

Meet our accomplished faculty members, a blend of experienced engineers and digital technology experts. Benefit from their practical insights and industry know-how as you delve into the world of Digital Industrial Engineering.
BIO

Ewa Currie, M.A.

BIO

Dr. Arash Habibi Lashkari

BIO

Hashem Zarafat

BIO

Khaleeq Aziz

BIO

Dr. Amra Abazi

BIO

Dr. Neslihan Ademi

BIO

Dr. Francisco Manuel Rangel Pardo

BIO

Dr. Jose Angel Gonzalez Barba

BIO

Dr. Soma Dutta

BIO

Prof. dr. Jack Mochyla

BIO

Dr. Agnieszka Dziedzic

BIO

Prof. Dr. Pawel Gburzynski

How to apply

1

Submit Your Application:

Create an account, select your study program, and upload the required documents. We’ll confirm once everything is submitted.
2

Pass the Interview:

If your documents are approved, you'll be invited to an online interview. Succeed, and you'll receive a conditional acceptance.
3

Sign and Pay:

Return the signed study contract and complete the enrollment fee and deposit to secure your spot

Receive Your Admission Letter
Congratulations, you’re in!

Ready to shape the future of industry? Join us and embark on a path that combines engineering excellence with digital innovation!

Apply now

Do you have
any questions?

Our study advisory team will be happy to arrange an individual consultation, by:
+49 152 593 597 22 [email protected]
or by completing a form:


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