Build intelligent apps with LLMs using Python, LangChain, and prompt engineering—hands-on and practical.
What you will learn
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Build intelligent applications using large language models (LLMs) like GPT and Mistral.
Design effective prompts to guide LLM behavior using advanced prompt engineering techniques.
Compare and evaluate popular LLMs for different application scenarios.
Implement retrieval-augmented generation (RAG) with embeddings and vector databases.
Use LangChain to create dynamic, modular AI-powered workflows.
Create conversational agents and assistants capable of natural, context-aware dialogue.
Embed custom data into LLM pipelines using semantic chunking and indexing.
Apply few-shot learning strategies to improve response quality in LLM outputs.
Integrate external tools and APIs with LLM agents for enhanced functionality.
Deploy Python-based AI applications with real-world usability and scalability.
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