No-code AI applications with ChatGPT, OpenAI, Flowise & LLMs

About this course

In a constantly evolving digital world, Artificial Intelligence has ceased to be a futuristic concept to become an essential tool across every industry. This course gives you two paths to build real ChatGPT and LLM-powered applications: a no-code path with Flowise, and an optional code path with LangChain in Python — so you can choose the one that fits you, or master both.

This course is for you if:

• You want to build AI applications without programming, using Flowise's visual interface
• You're a developer who wants to also understand the code-based approach with LangChain

You need to connect LLMs to your own documents and data (RAG, vector databases)You want to explore what's next in AI: Auto-GPT, BabyAGI, and open-source models

What you'll learn:

• The fundamentals of Language Models and how ChatGPT works under the hood
• Build LLM applications with LangChain in Python: Prompts, Chains, Memory, and Agents

Build LLM applications without code using Flowise: every component explained (Modeling, Prompts, Vector Stores, Memory, Chains, Agents and Tools)Work with Vector Databases, especially Pinecone, to give your LLM access to custom knowledge

Use Hugging Face models both from Python and directly inside Flowise

Explore open-source LLMs: Llama, Alpaca, Vicuna, and Falcon (7B and 40B), including running them locally with Docker, LocalAI, and GPT4AllAccess open-source models in the cloud through Replicate

Understand and use Auto-GPT, BabyAGI, and Jarvis — the models pushing beyond ChatGPT's capabilities

Deploy your LLM applications to production through APIsHands-on projects included:

• This course is built

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