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From AI fundamentals to production RAG systems — master prompt engineering, LangChain, agents, and cost-effective AI architecture.
What you learn
Machine learning basics, neural networks, transformers, LLM concepts
Outcome
Understand how large language models work and their capabilities
Milestones
What you learn
Prompt design, few-shot learning, chain-of-thought, prompt optimization
Outcome
Craft effective prompts for various LLM tasks and use cases
Milestones
What you learn
OpenAI API, LangChain, vector databases, embeddings, semantic search
Outcome
Build applications that integrate LLMs and handle context
Milestones
What you learn
Retrieval-augmented generation, chunking strategies, vector stores, reranking
Outcome
Build knowledge-grounded AI systems with custom data
Milestones
What you learn
Fine-tuning, evaluation, monitoring, cost optimization, safety
Outcome
Deploy and maintain production-grade GenAI applications
Milestones
Each phase builds on the previous. Work through them in order for the best results.
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