The aim of this course is to provide practical knowledge about how to apply Machine Learning methods in real world settings. The course features lectures given by industry experts from leading companies in the field. The practicals will provide hands-on experience with how to design a product/service featuring ML pipeline.
Lecturers: Tomáš Báča (TB), Jan Brabec (JB), Jan Lukány (JL)
Week | Date | Topic | Materials |
---|---|---|---|
1 | Sep, 23 (TB) | Introduction to Machine Lecture Engineering | lecture_01.pdf lecture_01_notes.pdf |
2 | Sep, 30 (TB) | Classical methods and models in MLE with Scikit Learn | lecture_02.pdf lecture_02_notes.pdf lecture_02_scripts.zip |
3 | Oct, 07 (TB) | Deep learning engineering basics with PyTorch | lecture_03.pdf lecture_03_notes.pdf lecture_03_scripts.zip |
4 | Oct, 14 (JB) | ML System Design and Architecture | lecture_04.pdf lecture_04_notes.pdf |
5 | Oct, 21 (JL) | Data storage frameworks | |
- | Oct, 28 (-) | Canceled - National holiday | |
6 | Nov, 04 (JL) | Machine learning model execution paradigms | |
7 | Nov, 11 (JB+TB) | Ground truth management | |
8 | Nov, 18 (JB) | Production metrics and observability | |
9 | Nov, 25 (JB) | ML and AI technical debt | |
10 | Dec, 02 (TB) | AI engineering, MCP | |
11 | Dec, 09 (TB) | Containerization (Docker, Apptainer) | |
12 | Dec, 16 (TB) | Development workflows (git, CI-CD, BDD) | |
13 | Jan, 06 (TB) | MLE and AI on the “edge” |
Hands-on design, develop, deploy and present a small application/service/product that uses Machine Learning in its core.
Week | Date | Topic | Deadlines | Materials |
---|---|---|---|---|
1 | Sep, 23 | Introduction | HW 01, PRD proposal | lab01_introduction.pdf |
2 | Sep, 30 | GUI + Project setup | HW 02, Readme | |
3 | Oct, 07 | Datasets | HW 03, Dataset | |
4 | Oct, 14 | Reinforcement learning in a virtual environment | ||
5 | Oct, 21 | Machine learning basics | HW 04, 1st progress report | |
- | Oct, 28 | Canceled - National holiday | ||
6 | Nov, 04 | Implementation details | ||
7 | Nov, 11 | Machine learning advanced | ||
8 | Nov, 18 | Deployment | ||
9 | Nov, 25 | Going to market | HW 05, 2nd progress report | |
10 | Dec, 02 | Workshop | ||
11 | Dec, 09 | Workshop | ||
12 | Dec, 16 | Workshop | ||
13 | Jan, 06 | Project presentations | HW 06, Final report |
Lab 1 link TODO
The total amount of points is the summation of
Points | [0,50) | [50,60) | [60,70) | [70,80) | [80,90) | [90,100] |
---|---|---|---|---|---|---|
Mark | F | E | D | C | B | A |
Late submissions will be penalized by -2 points penalty.
Lectures:
Labs: