Course Summary: End-to-End AI Engineering Bootcamp
This 8-week bootcamp is designed to equip technical specialists with the skills to become full-stack AI engineers. Participants will learn to design, develop, and implement production-ready AI systems, focusing on practical applications of Retrieval-Augmented Generation (RAG), agent systems, and scaling AI applications.
Instructor: Aurimas Gryciunas, a recognized voice in AI and a former CPO of Neptune.ai.
Course Highlights:
- Transition from prototyping to building functional AI products.
- Gain hands-on experience with advanced AI technologies and tools, such as LLM APIs, vector databases, Docker, and cloud deployments.
- Develop a thorough understanding of when and how to use RAG and AI agents, alongside learning about the scalability of different architectures.
Learning Outcomes:
- Create a demonstrable AI product.
- Acquire skills in AI system design, architecture, and deployment.
- Gain confidence in working with RAG, agents, and LLM infrastructure.
- Learn systematic approaches to managing AI projects within teams.
- Access to course materials for future cohorts.
Target Audience: Data scientists, ML engineers, data engineers, and technical analysts with a basic understanding of Python and machine learning.
Key Skills Acquired:
- Building RAG systems for context-aware AI solutions.
- Implementing AI agents capable of tool integration and autonomous decision-making.
- Mastering prompt engineering automation.
- Deploying scalable AI applications using containerization and cloud infrastructure.
- Incorporating LLMOps practices, including monitoring and continuous testing.
- Ensuring security and compliance in AI solutions.
This course prepares professionals for the increasing demand for skilled engineers who can take AI from concept to implementation in a business environment.