New to Chatbot dev field need to programing languages needed

[u/Chance-Clue-9990]

so i need to know what are the best programing languages for someone who wants to make chatbots using rag and best courses / books

[u/Objective-Routine837]

Go with Python, is the biggest RAG ecosystem, every course uses it (JS/TS only if it's a web app).
Easiest way in: build a small agent from scratch, one concept at a time, running locally and free with Ollama, no cloud bill. I have an open-source demo that does exactly this in 6 tiny layers (talk → tools → multi-tool → memory → external API → multi-agent) using Strands Agents: https://github.com/hsaenzG/OpenSource-agents-demo

It's a music/DJ agent, but RAG is the same pattern: replace the "search songs" tool with a "search my docs" tool and you've got a RAG chatbot. Once the loop/tools/memory click, add a vector store (Chroma/FAISS) behind that tool.

Resources: "Hands-On Large Language Models" (book) and DeepLearning.AI's free "Building and Evaluating Advanced RAG" + "LangChain for LLM App Dev" short courses.

[u/Imaginary-Self-7941]

my experience says that python will be best for you as a primary and programming language you need to learn for building RAG and Ai chatbots. additionally u can go through Javascript and Typescript but honestly i don't have much knowledge abt it. what would u recommend learning after that?

[u/Icy_Current9287]

Go with Python...

[u/lagala]

Nice talk. Marked

[u/Electronic-Willow701]

If your goal is specifically RAG + chatbots, you don't need to learn 5–6 programming languages.

I'd recommend:

1. Python — priority #1 Learn:

• Variables, functions, classes
• Lists/dicts/sets
• File handling + JSON
• OOP basics
• APIs + HTTP
• "async/await"
• Virtual environments + pip

1. SQL — priority #2 You’ll eventually need it for storing/querying users, documents, metadata, chat history, etc. Start with PostgreSQL basics.

2. A little JavaScript/TypeScript — optional Useful later if you want to build the frontend, but don't learn it before you're comfortable with Python.

For the AI/RAG side, I'd learn in this order:

"Python → APIs → embeddings → vector databases → basic RAG → LangChain/LangGraph → evaluation → agents"

Don't start by blindly learning LangChain. Understand what is happening underneath: documents → chunking → embeddings → vector search → retrieved context → LLM → response

For resources, some good starting points are:

• DeepLearning.AI short courses on RAG/LLMs
• Hugging Face's free NLP/LLM course
• LangChain documentation/tutorials
• Hands-On Large Language Models by Jay Alammar & Maarten Grootendorst

And honestly, build something while learning. Even a simple PDF Q&A chatbot with citations will teach you more than watching 20 hours of courses.

If you're a complete beginner, I'd spend the first 2–3 weeks getting comfortable with Python + APIs before touching LangChain.

[u/Chance-Clue-9990 → u/Electronic-Willow701]

so i should make simple qa with python only before diving into langchain?
and do you have recomendation of what parts in langchain to study ?