{"id":12848,"date":"2026-08-10T10:51:06","date_gmt":"2026-08-10T10:51:06","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-building-a-simple-data-analyst-ai-agent-with-llama-and-flask-2025-4\/"},"modified":"2026-08-10T10:51:06","modified_gmt":"2026-08-10T10:51:06","slug":"udemy-building-a-simple-data-analyst-ai-agent-with-llama-and-flask-2025-4","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-building-a-simple-data-analyst-ai-agent-with-llama-and-flask-2025-4\/","title":{"rendered":"Udemy \u2013 Building a Simple Data Analyst AI Agent with Llama and Flask 2025-4"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Building a Simple Data Analyst AI Agent with Llama and Flask. This hands-on course teaches you how to build a simple data analyst AI agent using the open-source Llama language model and the Flask framework. Without the need for expensive APIs or advanced programming knowledge, participants will learn how to run the Llama model locally and create a lightweight application with Flask. The application will be able to answer user questions based on data stored in a Postgres database, providing functionality similar to a simple retrieval-based production system. The course begins by teaching the principles of prompt engineering and covers basic techniques such as in-text learning, thought chains, and thought trees. Next, learners will set up a Flask server, connect it to a Postgres database, and create an endpoint that receives and processes user queries and returns AI-generated answers from the database data. This course provides a direct and practical path to applying large language models to small, real-world projects, and builds a solid foundation in prompt engineering and AI application development by teaching you how to build a working prototype.<\/span><\/p>\n

What you will learn<\/span><\/h3>\n