Text Mining and Natural Language Processing
Certificate Course - Financial Engineering - FE.5.1.I26
| Date | Oct 26 - Nov 03, 2026 |
| Duration | 7 days |
| Location | On campus - Karlsruhe |
| Language | English |
| ECTS | Upon request |
| Cost | 3,110 € |
Fundamentals
Understand how text data can be processed and analyzed to extract meaningful financial information using natural language processing techniques.
Technology
Apply natural language processing methods to automatically extract and structure information from large volumes of financial text data.
Applications
Use textual analysis to solve financial problems by extracting insights from news, reports, and other unstructured data sources.
What you´ll explore
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Explore the fundamentals of financial textual analysis and natural language processing.
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Understand how information can be extracted automatically from unstructured text data.
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Learn about recent developments in natural language processing techniques.
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Analyze how text data is used in financial decision-making and forecasting.
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Discover applications of NLP in processing news, reports, and financial documents.
Your key takeaways
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Understanding of natural language processing concepts and methods
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Ability to extract information from financial text data
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Knowledge of modern techniques in financial textual analysis
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Skills to apply NLP tools to real-world financial problems
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Competence in handling and structuring unstructured data
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Practical insight into using text data for financial decision-making
Taught by Recognized Experts in Text Mining and Natural Language Processing
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. Alexander Hillert
Prof. Dr. Alexander Hillert is Co-Director of Financial Intermediation and Professor for Finance and Data Science at SAFE. He previously held the Professorship of Sustainable Asset Management at Goethe University Frankfurt. He earned his PhD from the University of Mannheim. His research focuses on empirical asset pricing and corporate finance, especially how investors process information.
He applies computational linguistics to study text effects on capital markets, with publications in journals such as the Journal of Financial Economics and the Review of Financial Studies.
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.