Artificial Intelligence leer- en beoordelingsmateriaalpakket

├─ Learning Unit 1Foundations of Artificial Intelligence.
│├ Lesson 1 – Scope of AI (documentslides).
│├ Lesson 2 – Problem Solving (documentslides).
│├ Lesson 3 – Knowledge Representation (documentslides).
│├ Lesson 4 – Machine Learning (documentslides).
│├ Lesson 5 – Applications (documentslides).
│└ Lesson 6 – Ethical Implications (documentslides).

├─ Learning Unit 2 Machine Learning.
│├ Lesson 1 – Introduction to Machine Learning (documentslides).
│├ Lesson 2 – Languages and Resources (documentslides).
│├ Lesson 3 – Data Transformation and Visualization (documentslides).
│├ Lesson 4 – Supervised Linear Machine Learning (documentslides).
│├ Lesson 5 – Supervised non linear Machine Learning (documentslides).
│└ Lesson 6 – Unsupervised Machine Learning (documentslides).

├─ Learning Unit 3Neural Networks and Deep Learning.
│├ Lesson 1 – Brain Origins and Elements of Artificial Neural Networks (documentslides).
│├ Lesson 2 – Simple Perceptrons and Supervised Learning (documentslides).
│├ Lesson 3 – Multilayer Perceptron and Keras (documentslides).
│├ Lesson 4 – Deep Learning for Image Classification, Convolutive Neural Networks (document, slides). 
 Lesson 5 – Different CNNs for Image Classification (document, slides).
│└ Lesson 6 – Real Time Objects Locatization with YOLO (document, slides).

└─Learning Unit 4AI for Solving real-life problems.
   ├ Lesson 1 – Natural Language Processing Introduction, Embeddings Classification (document, slides).
   ├ Lesson 2 – Neural Networks for NLP and Libraries (document, slides).
   ├ Lesson 3 – New Approaches, Applications and Open Problems (document, slides).
   ├ Lesson 4 – BigData Problems, Core Techniques and Introduction to Problems, Hadoop Spark (document, slides).
   ├ Lesson 5 – Spark for Big Data Processing (document, slides).
   └ Lesson 6 – Cloud Computing and ML with PySpark (document, slides).