Syllabus
- 00 INTRO
- 01 PY1: Python: Introduction
- 02 PY2: Python: Packages
- 03 ML1: Introduction to Machine Learning. Lecture
- 04 ML2: Introduction to Machine Learning. Practice: Supervised Learning
- 05 ML3: Introduction to Machine Learning. Practice: Unsupervised Learning
- 06 DL1: Introduction to Deep Learning. Lecture
- 07 DL2: Introduction to Deep Learning. Practice
- 08 DL3: Introduction to Deep Learning. Practice
- 09 EXAM1: Exam preparation. Baseline overview
- 10 NLP1: Natural Language Processing. Lecture
- 11 NLP2: Natural Language Processing. Practice
- 12 EXAM2: Exam preparation. Recommendations from lecturers.
- 13 CV1: Computer Vision. Lecture
- 14 CV2: Computer Vision. Practice
- 15 MATH: Mathematics of ML/DL (TBD).
- Exam