Note: M3 - Final Assignment Deadline: on Friday, 07-03-2025, at 12:00
This course provides a practical and applied introduction to deep learning, specifically focusing on LLMs. It covers the fundamentals of deep learning, including foundational concepts, tensors, typical architectures, and applications in different contexts. The course will also delve into various training paradigms and tools prevalent in deep learning.
Initially, the course focuses on traditional neural network architectures such as ANNs, CNNs, RNNs, and LSTMs, exploring their utility in addressing economic challenges like forecasting. As the course progresses, students will delve into advanced topics such as GNNs, Transformer models, and GPT models, focusing on the attention mechanism and its role in enhancing model performance. Practical insights will be shared on tools within the GNN, Transformer, and GPT ecosystems and their applications in real-world scenarios.
Real-world examples from economics and other fields will be used to illustrate the concepts and techniques taught throughout the course. By the end, students will have a robust understanding of deep learning and its applications in the real world, having collaborated on four mini-projects to apply these concepts to real-world research scenarios, ultimately curating a portfolio to showcase their skills.
| Session | Date | Time | Location | Teacher | Group Assignment Deadline |
|---|---|---|---|---|---|
| 💡 Session 1: Intro to Traditional Deep Learning | Monday, 3rd Feb | 08:15 - 12:00 | Room 41, Fib 11 | Hamid | 10th Feb at 12:00 |
| 💡 Workshop 1: Traditional DL | Friday, 7th Feb | 08:15 - 12:00 | Room 41, Fib 11 | Hamid | - |
| 💡 Session 2: Introduction to Transformer Models | Monday, 10th Feb | 08:15 - 12:00 | Room 41, Fib 11 | Hamid | 17th Feb at 12:00 |
| 💡 Session 3: Introduction to GPTs | Monday, 17th Feb | 08:15 - 12:00 | Room 41, Fib 11 | Hamid | 24th Feb at 12:00 |
| 💡 Workshop 2: Agentic Systems & GPT Applications | Friday, 21st Feb | 12:30 - 15:00 | Room 41, Fib 11 | Eskil | - |
| 💡 Session 4: Advanced Topics in Deep Learning | Monday, 24th Feb | 08:15 - 12:00 | Room 41, Fib 11 | Hamid | 7th Mar at 12:00 |
| 💡 Workshop 3: Advanced DL Applications | Friday, 28th Feb | 12:30 - 15:00 | Room 41, Fib 11 | Christian | - |
The exam in Applied Deep Learning and Artificial Intelligence is a group exam based on a submitted assignment portfolio. It is an internal examination with a 7-point grading scale and takes place in Week 11.