Source: Microsoft
What it contains:
| No | Lesson | Intro | PyTorch | Lab | Use Cases |
|---|---|---|---|---|---|
| I | Introduction to AI | Understanding AI Concepts | |||
| 1 | Introduction and History of AI | Text | Foundations of AI | ||
| II | Symbolic AI | Problem Solving, Planning | |||
| 2 | Knowledge Representation and Expert Systems | Text | Expert System, Ontology, Concept Graph | Decision Making Systems | |
| III | Introduction to Neural Networks | Neural Network Modeling | |||
| 3 | Perceptron | Text | Notebook | Lab | Binary Classification |
| 4 | Multi-Layered Perceptron and Creating our own Framework | Text | Notebook | Lab | Multi-Class Classification |
| 5 | Intro to Frameworks (PyTorch/TensorFlow) | Overfitting | Text | AI Software Development | |
| IV | Computer Vision | AI Fundamentals: Explore Computer Vision | Image Processing | ||
| 6 | Intro to Computer Vision. OpenCV | Text | Notebook | Lab | Image Analysis |
| 7 | Convolutional Neural Networks | CNN Architectures | Text | Lab | Image Recognition |
| 8 | Pre-trained Networks and Transfer Learning | Training Tricks | Text | Dropout sample, Adversarial Cat | Advanced Image Classification |
| 9 | Autoencoders and VAEs | Text | Dimensionality Reduction | ||
| 10 | Generative Adversarial Networks | Artistic Style Transfer | Text | GAN, Style Transfer | Image Generation |
| 11 | Object Detection | Text | Lab | Real-time Object Tracking | |
| 12 | Semantic Segmentation. U-Net | Text | Pixel-level Image Classification | ||
| V | Natural Language Processing | AI Fundamentals: Explore Natural Language Processing | Text Processing | ||
| 13 | Text Representation. Bow/TF-IDF | Text | Text Classification | ||
| 14 | Semantic word embeddings. Word2Vec and GloVe | Text | Word Similarities | ||
| 15 | Language Modeling. Training your own embeddings | Text | Lab | Text Prediction | |
| 16 | Recurrent Neural Networks | Text | Sequence Prediction | ||
| 17 | Generative Recurrent Networks | Text | Lab | Text Generation | |
| 18 | Transformers. BERT. | Text | Text Summarization, Translation | ||
| 19 | Named Entity Recognition | Text | Lab | Information Extraction | |
| 20 | Large Language Models, Prompt Programming and Few-Shot Tasks | Text | Text Summarization, Question Answering |
