Introduction to Python
Certificate Course - Financial Engineering - FE.1.4.I26
| Date | Nov 24-25, 2026 |
| Duration | 2 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | Upon request |
| Cost | 1,550 € |
Fundamentals
Learn Python basics, including syntax, variables, functions, and objects, building a strong foundation in programming concepts.
Technology
Develop practical coding skills in Python, creating routines and working with data from sources such as Excel files and webpages.
Applications
Apply Python to real tasks in data handling and analysis, using its flexibility for problems in statistics and computer science.
What you´ll explore
- Explore the fundamentals of Python programming, including syntax, variables, functions, and objects.
- Understand how to structure code and build reusable routines for efficient problem solving.
- Learn how to read and process data from external sources such as Excel files and webpages.
- Discover how Python is used in statistics and computer science for data analysis and automation.
Your key takeaways
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Understanding of core Python programming concepts and syntax
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Ability to declare variables, functions, and objects in Python
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Skills to write structured and reusable code
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Knowledge of how to import and handle data from Excel and web sources
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Practical experience in applying Python to data-related tasks
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Foundation for further study in data analysis, statistics, and software development
Taught by recognized experts in Introduction to Python
Benefit from the knowledge of leading specialists with extensive experience in research and industry. Their deep expertise guarantees a course of outstanding academic and practical quality.
Prof. Dr. Maxim Ulrich
Prof. Dr. Maxim Ulrich is Professor of Risk Management and Financial Economics at KIT and has built an international academic career, including serving as Tenure-Track Assistant Professor at Columbia Business School from 2008. His work focuses on quantitative finance, asset pricing, and financial machine learning, making him a recognized expert in the field.
He brings extensive experience from academia and practice, including fintech ventures and collaborations with institutions such as the ECB and Eurex.
Who should attend
This module is designed for professionals seeking a structured introduction to machine learning and its applications in decision-making, finance, and advanced analytical modeling.
- Decision-makers and managers interested in understanding machine learning concepts and methods
- Finance professionals seeking data-driven approaches to market analysis and forecasting
- Analysts and researchers looking to strengthen their knowledge of applied and advanced machine learning techniques
- Professionals who want a coherent learning path from foundational to specialized topics
Advance your career with KIT-level expertise
Benefit from the reputation of the Karlsruhe Institute of Technology (KIT) while gaining practical skills, flexible learning opportunities, and a recognized certificate to support your long-term professional growth.
Flexibility
Gain focused expertise in a specific field without committing to a full degree program, allowing you to build relevant knowledge efficiently and integrate learning seamlessly into your professional routine.
Relevance
Benefit from high-quality academic content combined with practical insights, delivered by experienced experts, supporting continuous, lifelong learning while ensuring direct applicability in real-world scenarios.
Advancement
Enhance your professional profile with a recognized certificate, demonstrating your commitment to ongoing development and supporting your career with tangible, verifiable credentials.