Course Curriculum
Master Python programming essentials for AI and machine learning development.
- • Python Fundamentals
- • NumPy and Pandas
- • Data Visualization (Matplotlib, Seaborn)
- • Jupyter Notebooks
Learn core ML concepts, algorithms, and model evaluation techniques.
- • Supervised vs Unsupervised Learning
- • Linear & Logistic Regression
- • Decision Trees and Random Forests
- • Model Evaluation Metrics
Build neural networks and deep learning models with TensorFlow.
- • Neural Network Basics
- • TensorFlow and Keras
- • Convolutional Neural Networks (CNNs)
- • Recurrent Neural Networks (RNNs)
Master PyTorch for research and production deep learning applications.
- • PyTorch Fundamentals
- • Building Custom Models
- • Transfer Learning
- • Model Optimization
Work with modern LLMs like GPT, Claude, and open-source alternatives.
- • Understanding Transformers
- • OpenAI API Integration
- • Prompt Engineering
- • Fine-tuning LLMs
- • Text Preprocessing
- • Sentiment Analysis
- • Named Entity Recognition
- • Text Generation
- • Image Classification
- • Object Detection (YOLO, R-CNN)
- • Image Segmentation
- • Face Recognition