# Learning Path: LLM Application Development With Python

DevFeed: [Learning Path: LLM Application Development With Python](<https://devfeed.tech/articles/learning-path-llm-application-development-with-python-4380.md>)

Original publisher: [Read original article](<https://realpython.com/learning-paths/llm-application-development-python/>)

Author: Real Python

Published: 2026-03-19T12:00:00Z

Content type: tutorial

Language: en

Sources: [Real Python](<https://devfeed.tech/sources/real-python.md>)

Topics: [Language models](<https://devfeed.tech/topics/language-models.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>)

Tags: [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [apis](<https://devfeed.tech/tags/apis.md>), [application-development](<https://devfeed.tech/tags/application-development.md>), [langchain](<https://devfeed.tech/tags/langchain.md>), [llm](<https://devfeed.tech/tags/llm.md>), [mcp](<https://devfeed.tech/tags/mcp.md>), [openai](<https://devfeed.tech/tags/openai.md>), [prompt-engineering](<https://devfeed.tech/tags/prompt-engineering.md>), [python](<https://devfeed.tech/tags/python.md>), [rag](<https://devfeed.tech/tags/rag.md>)

## AI overview

A Python learning path for building LLM-powered applications with model APIs, prompt engineering, RAG pipelines, AI agents, and MCP integrations.

## Source excerpt

Build LLM-powered applications in Python. Call model APIs, craft prompts, add retrieval-augmented generation, create AI agents, and connect via MCP.