Course No: 0907743
Course Name: Advanced AI and Machine Learning
Microsoft Team: Link
Handouts:
Course Syllabus (pdf)
Slides:
- 1. Course Introduction (pptx)
- Python
- Python Introduction (pdf)
- Python Basics (pdf)
- Important Python Packages (pdf)
- Advanced Python (pdf)
- ML
- Machine Learning Introduction (pdf)
- End-to-End Machine Learning Project (pdf)
- Classification (pdf)
- Information about the term project (pdf)
- Training Models and Regression (pdf)
- Classical Techniques (pdf)
- Unsupervised Learning and Clustering (pdf)
- Neural Networks (pdf)
- Artificial Neural Networks with Keras (pdf)
- Deep Neural Networks (pdf)
- Deep Computer Vision Using Convolutional Neural Networks (pdf)
- Recurrent Neural Networks (pdf)
- Reinforcement Learning (pdf)
- Recommender Systems (pdf)
Videos:
- Python
- Python Introduction (YouTube) by M. Abdel-Majeed
- Python Basics (YouTube: Part 1, Part 2, Part 3) by G. Abandah
- Important Python Packages (YouTube) by M. Abdel-Majeed
- Training Models (YouTube)
- Classical Techniques 1: k-nearest neighbors (YouTube)
- Classical Techniques 2: Support Vector Machines (YouTube)
- Classical Techniques 3: Decision Trees (YouTube)
- Classical Techniques 4: Ensemble Learning and Random Forests (YouTube)
- Neural Networks (YouTube)
- Artificial Neural Networks with Keras (YouTube: Part 1, Part 2, Part 3)
- 13. Deep Neural Networks (YouTube: Part 1, Part 2, Part 3)
- 14. Deep Computer Vision Using Convolutional Neural Networks (YouTube: Part 1, Part 2, Part 3)
- 15. Recurrent Neural Networks (YouTube)
- 16. Reinforcement Learning (YouTube: Part 1, Part 2)
- 17. Recommender Systems (YouTube)
Solutions:
- Midterm exam (TBA), Final Exam (TBA)
Grades: Project and final exam marks (TBA)
Last update on 20/5/2021