What You'll Learn
- 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.
Requirements
- No requirements, you'll learn everything here! Including Python
Who This Course is For
- Software developers and engineers who want to integrate large language models into real-world applications and tools.
- Data scientists and AI enthusiasts looking to build intelligent agents using LangChain, embeddings, and prompt engineering.
- Entrepreneurs and product builders aiming to create AI-powered products like chatbots, assistants, or RAG systems with minimal overhead.
Your Instructor
OCSALY Academy | 500.000+ Students
Join 500,000+ happy students from 165 countries and beyond !
4.2 Instructor Rating
14,896 Reviews
552,310 Students
26 Courses
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