البداية

البداية: هندسة الذكاء الاصطناعي | AI Engineering Masterclass

  • Slides From All Lectures & Access to Our Discussion Group
  • 1 Access to Our Exclusive Q&A and Discussion Group
  • 2 Slides From All Lectures
  • 3 Lecture 1: Terms, Features, Classes & Matrix Operations
  • Machine Learning Foundations
  • 4 Lecture 2: Statistics and Probability for Machine Leaning
  • 5 Practice Notebook 1: Introduction to Python for Machine and Deep learning
  • 6 Introduction to Python
  • 7 Lecture 3: Linear and Polynomial Regression and solving general problems
  • 8 Lecture 4: Gradient Descent variations & other optimizers (Momentum, RMS Prop & ADAM)
  • Machine Learning Terms and Algorithms
  • 9 Practice Notebook 2: NumPy, Vectorization, Data Visualization & OOP
  • 10 Vectorization, Data Visualization and OOP Walkthrough
  • 11 Lecture 5: Perceptron and Adaline
  • 12 Lecture 6: Logistic Regression, Multilayer perceptron (MLP), Deep Nets
  • 13 Practice Notebook 3: Regression on real data (+20,000 houses information) and Optimizers
  • 14 Lecture 7: Pre-processing (handling missing values, outliers, z-scoring) & Cross validation
  • 15 Lecture 8: Overfitting, Covariate shifts, Multicollinearity, Regularization, LR schedulers
  • 16 Practice Notebook 4: Classification with Perceptron, Adaline, logistic & DeepNNs on real data
  • Building a Solid Machine Learning Pipeline
  • 17 Lecture 9: Evaluation Metrics(MSE, Confusion matrix etc.) & Hypothesis Testing(ttest, etc.)
  • 18 Lecture 10: Dimensionality Reduction (PCA etc.), Feature Selection (SFS), Autoencoders
  • 19 Practice Notebook 5: Pre-processing, Multicollinearity, Cross-validation, Covariate shifts, LR schedulers
  • 20 VS Code واستخدام Notebooks الخروج من الـ
  • 21 Full Pipeline: من مشكلة واقعية في شركة إلى حل بإستخدام التعلم العميق
  • 22 Lecture 11: Probability, Bayesian thinking, the probabilistic approach to machine learning
  • 23 Lecture 12: Probabilistic Machine Learning, How to create cost functions, Entropy
  • 24 Practice Notebook 6: Probabilistic Machine Learning
  • 25 Lecture 13: Sequential Data, Recurrent Neural Networks (RNNs), Next Word Prediction
  • The probabilistic approach to Machine and Deep Learning
  • 26 Lecture 14: GRU, LSTM, Bidirectional RNN, Word Embedding
  • 27 Lecture 15: Learning Embeddings, Word2vec, Skip Gram, Negative Sampling, GloVe
  • 28 Practice Notebook 7: Sequence Models on text data: Spam Classification, NER (Vanilla RNN → GRU → LSTM → BiLSTM)
  • 29 Lecture 16: The Attention Mechanism, Transformers, BERT, GPT
  • Natural Language Processing (NLP)
  • 30 Practice Notebook 8: Attention, Tranformers (News classification and Person NER, Many-to-One and Many-to-Many )
  • 31 Lecture 17: Diffusion Models
  • 32 Lecture 18: Research papers: DDPM, Improved DDPM, Stable Diffusion, Contrastive Learning
  • 33 Practice Notebook 9: Diffusion Models Projects (Super-resolution to enhance image quality, colouring black & white images)
  • 34 Lecture 19: Image Processing To CNNs: CNN Architectures (LeNet-5, AlexNet, VGG, Inception)
  • 35 Lecture 20: YOLO, Object Tracking, U-Net, ResNets, Augmentation
  • 36 Practice Notebook 10: CNNs, Transfer Learning, Augmentation, YOLO on custom data
  • 37 Lecture 21: Building And Serving Machine Learning Systems
  • 38 Lecture 22, part 1: AI-powered Chatbot Website And Mobile App on Custom Data (RAG)
  • 39 Lecture 22, part 2: AI-powered Chatbot Website And Mobile App on Custom Data (Fine-tuning)
  • Computer Vision
  • 40 Building and Deploying AI Projects (Slides)
  • 41 Flask Code
  • 42 Code for: AI Chatbot (Mobile App and Website) with Gemini API
  • 43 Code for: Shawkat, Our AI Chatbot on custom data (Mobile App and Website)
  • Building and Deploying AI Projects
  • 44 Custom Phi3 Model on Custom data (people info extraction)
  • 45 RAG Example and Our Custom Course Assistant Chatbot
  • 46 Fine-Tuning with Our Custom Course Assistant Chatbot
  • 47 AI Engineering Kaggle Competition مسابقة هندسة الذكاء الاصطناعي
  • 48 Open Discussion about the Competition

Lecture 1: Terms, Features, Classes & Matrix Operations

  1. البداية: هندسة الذكاء الاصطناعي | AI Engineering Masterclass
  2. Lecture 1: Terms, Features, Classes & Matrix Operations
Previous Lesson
Back to Course
Next Lesson

© 2026 البداية