AI and Machine Learning – Spring 2021

Course No: 0907451
Course Name: AI and Machine Learning

Microsoft Team: Link

Handouts:
Course Syllabus (pdf)
Slides:

  • Course Introduction (pptx)
  • Python
  • Python Introduction (pdf)
  • Python Basics (pdf)
  • Important Python Packages (pdf)
  • Advanced Python (pdf)
  • AI
  • Artificial Intelligence and Machine Learning Applications (pdf)
  • Introduction to AI (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