AI Engineering Bootcamp: LangChain, LLMs & Modern AI Systems https://takzenai.pl

This project involves creating a website for an AI Engineering Bootcamp focused on LangChain, Large Language Models (LLMs), and modern AI systems. The site is built with Next.js and serves as an interactive platform for students to engage with course materials, watch instructional videos, complete exercises, and work on a mini-project.

Throughout the bootcamp, learners will dive into various tools like LangChain, LangFlow, LangGraph, and LangSmith, gaining hands-on experience in building cutting-edge AI applications. The course covers essential topics such as Retrieval-Augmented Generation (RAG), PostgreSQL integration, and deploying applications in Docker. Furthermore, participants will utilize Pydantic to manage data schemas and validate inputs, ensuring data integrity throughout their projects.

Project Highlights:

• The website is built using Next.js, offering a fast and user-friendly experience.
• Comprehensive course content, including video tutorials, exercises, and a final mini-project.
• Practical learning with a focus on coding and creating AI-driven applications.
• Integration of LangChain, LangFlow, LangGraph, LangSmith, and Docker to teach real-world AI development skills.

This project is designed to give developers the tools and knowledge to build modern, AI-powered applications, with a particular focus on Large Language Models (LLMs). Whether you're looking to expand your AI expertise or get hands-on experience with the latest tools and technologies, this bootcamp offers a structured, practical approach to learning.

The website is fully responsive and designed to provide an engaging experience for learners. From easy navigation of course materials to clear access to all learning resources, the platform supports students throughout their AI development journey.

Technologies Used:

• Next.js for building a modern, dynamic website.
• LangChain, LangFlow, LangGraph, LangSmith for building AI applications.
• PostgreSQL for integrating databases into AI-driven systems.
• Docker for deploying the applications in a containerized environment.
• Pydantic for managing and validating data schemas.

By the end of this bootcamp, participants will have gained valuable skills in AI engineering, with the confidence to build their own AI-powered applications. This hands-on approach, combined with a solid project-based curriculum, ensures that students can apply their knowledge to real-world scenarios.