No-code AI applications with ChatGPT, OpenAI, Flowise & LLMs (Udemy.com)

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 GPT4All

• Access 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 APIs

Hands-on projects included:
This course is built around practical projects, not just theory: you'll design a customized AI wizard, build a chatbot assistant end-to-end, create and query vector indexes in Pinecone, deploy a custom LLM to production, and complete a full start-to-finish project combining web scraping, Pinecone, and a Conversational Retrieval QA Chain — while actively working to reduce hallucinations.

Why this course:

• Two development paths in one course: no-code (Flowise) and code (LangChain) — pick what fits you

• Real hands-on labs and solutions throughout, not just lectures

• Covers the full stack: from prompting to vector databases to production deployment

• Stay current with cutting-edge developments like Auto-GPT and BabyAGI

There are no longer any barriers between you and next-generation AI applications — whether or not you know how to code. Start your journey today!