Deep dive into generative AI, transformers, LLMs, and agentic systems. Build applications with GPT, Claude, and open-source models.
Master the transformer architecture: self-attention, multi-head attention, positional encoding, and layer normalization.
Learn advanced prompting techniques: chain-of-thought, few-shot, role prompting, and structured output formats.
Fine-tune open-source models with LoRA, QLoRA, and full fine-tuning. Understand data preparation and hyperparameter tuning.
Build retrieval-augmented generation systems with vector databases, chunking strategies, and reranking.
Work with vision-language models, audio models, and multimodal agents. Understand CLIP, LLaVA, and Whisper.
Build autonomous AI agents with tool use, memory, planning, and multi-agent collaboration.
Understand hallucination, bias, copyright, and safety in generative AI. Implement guardrails and content moderation.
Deploy generative AI at scale: caching, streaming, batching, and cost optimization strategies.