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Building ML/AI Applications
Last Updated: 2026-06-01 11:30:45
Abstract
This course provides fundamental training in areas of machine learning. The course is intended for managers and leaders who want to understand the basics of the technologies that are likely to change almost every aspect of our lives. We explain technical concepts in simple terms and no previous experience with ML is expected.
Objective
Participants learn ... - how machine learning works. - popular models for machine learning. - how to implement neural networks for image processing. - the basics of natural language processing. - how large language models, like chatGPT, work. - current pitfalls and challenges when working with machine learning.
Content
We will cover the following topics: • Introduction to Machine Learning: Understand the essentials of ML and its core tools like decision trees, neural networks, and cross-validation. • Deep Learning: Discover the transformative role of neural networks, with an emphasis on natural language processing. We study applications like machine translation and ChatGPT. • Applications: Learn how ML is revolutionizing sectors like finance, insurance, retail, and services. • Challenges & Considerations: Recognize the potential pitfalls, threats, and ethical considerations in deploying ML. • The Future of AI: Engage in discussions on the societal impacts and future prospects of AI.
General Information
- Language
- English
- Levels
- NDS , WBZ
- Frequency
- Semesterly recurring
Examination
- Type
- ungraded semester performance
Registration & Places
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Building ML/AI Applications
Block course
|
|
36 h semesterly |