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AI & Machine Learning
Build intelligent applications with AI and machine learning. From fundamentals to advanced topics including LLMs, neural networks, and practical AI integration.
16 Modules
Video Tutorials
AI Projects
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