Ankündigung “Applied Artificial Intelligence” im Wintersemester 2023/24
12 Credits with weekly:
- flipped classroom lecture
- discussion round
- shared hands-on programming exercise
- homework submission
AI and the application of machine learning is becoming more and more popular to solve relevant business challenges. However, it is not only essential to be familiar with precise algorithms but rather a general understanding of the necessary steps with a holistic view—from real-world challenges to the successful, scalable deployment of an AI-based solution. As part of this course, we teach the complete lifecycle of an AI project focusing on supervised machine learning challenges. Apart from the technical aspects necessary when developing AI within complex systems, we also shed light on the collaboration of humans and AI in such systems (e.g., with the support of explainable AI), topics of ethics and bias in AI, as well as AI’s capabilities on being generative and creative.
Students of this course will be able to understand and implement the complete lifecycle of a typical Artificial Intelligence (AI) use case with supervised machine learning in Python. Furthermore, they understand the importance and the means of applying AI in general and machine learning within real-world settings in industry and practice. Besides technical aspects, they will gain an understanding of the broader challenges and aspects when dealing with AI.
Have questions? Reach out to us at firstname.lastname@example.org
Week 42: Motivation, Terminology, Overview
Week 43: AI Lifecycle: Initiation
Week 44: AI Lifecycle: Modeling & Evaluation
Week 45: AI Lifecycle: Deployment
Week 46: AI Lifecycle: Concept drift
Week 47: AI in Systems: Large Language Models
Week 48: AI in Systems: System-wide learning
Week 49: AI in Systems: Human-AI Collaboration
Week 50: Creative AI
Week 51: Ethics of AI
Concept: Flipped Classroom
You have until Tuesday noon to asynchronously watch the recording — at your convenience.
Each Tuesday we will spend the first few minutes discussing the contents of the lecture in-person. This includes your questions and remarks.
Then, we will practice the content of the lecture in the immediately following exercise slot
Exercise and Exam Admission:
Complete several Python exercises (jupyter notebooks).
Your admission remains valid for future exams.
Don't miss this chance to be at the forefront of AI! Enroll today and shape the future of Applied AI.