Master artificial intelligence through hands-on, step-by-step tutorials. From fundamental concepts to advanced implementations, learn AI at your own pace with practical examples and real-world applications.
Start your AI journey by understanding what artificial intelligence is, how it works, and its real-world applications. No prior experience required.
Learn the core concepts of machine learning: supervised, unsupervised, and reinforcement learning. Understand how algorithms learn from data.
Get started with Python, the most popular programming language for AI. Learn syntax, data structures, and essential libraries for machine learning.
Deep dive into LLMs like GPT, Claude, and Gemini. Understand transformers, attention mechanisms, and how these models generate human-like text.
Learn how AI creates images, videos, and audio. Explore diffusion models, GANs, and tools like DALL-E, Midjourney, and Stable Diffusion.
Build a practical AI application that analyzes PDF documents, extracts information, and answers questions using NLP and embeddings.
Build autonomous AI agents that can plan, reason, use tools, and collaborate. Learn about multi-agent systems and production deployment.
Deploy machine learning models to production with Docker, Kubernetes, monitoring, CI/CD pipelines, and scalable infrastructure.
Customize pre-trained LLMs for specific tasks using fine-tuning, LoRA, and RLHF techniques. Optimize for performance and cost.
Understand bias, fairness, transparency, and governance in AI systems. Learn how to build ethical and responsible AI applications.
Explore the environmental impact of AI training and inference. Learn about green AI, optimization techniques, and sustainability challenges.
Create time-series forecasting models for stock prices, cryptocurrency, and market predictions using LSTM, Prophet, and modern techniques.