AI Engineering Buildcamp – From RAG to Agents by Alexey Grigorev
Build production-ready AI systems, master LLMs, and create intelligent agents with real-world applications.
AI Engineering Buildcamp – From RAG to Agents by Alexey Grigorev is a hands-on, project-based training designed to take you from foundational AI concepts to building scalable, real-world AI applications.
This program focuses on practical implementation using modern technologies such as LLMs, RAG pipelines, and agent-based systems—helping you move beyond tutorials and develop industry-ready skills.
Instead of learning theory alone, you’ll build complete AI systems capable of retrieving data, reasoning, and taking actions.
What’s Included
- 8+ hands-on AI projects
- Step-by-step implementation guides
- Real-world use cases and examples
- Live sessions and recorded content
- Community collaboration and support
- Capstone project for portfolio development
- Modern AI tools and frameworks training
Modules & Sessions
LLMs & RAG Foundations
Build intelligent systems:
- Understanding Large Language Models
- Building RAG pipelines with real data
- Conversational AI assistants
- API integration and structured outputs
Agentic Systems & Tool Calling
Create advanced AI agents:
- Function calling and agent workflows
- Tool-enabled AI systems
- Multi-step reasoning systems
- Frameworks like PydanticAI and Agents SDK
Testing & Evaluation
Ensure quality and performance:
- Evaluating AI outputs with metrics
- Prompt comparison and optimization
- Using LLMs as evaluators
- Improving system reliability
Monitoring & Guardrails
Build production-ready systems:
- Tracking performance and costs
- Observability and debugging
- Implementing safety layers
- Guardrails for reliable AI behavior
Use Cases & Real Projects
Apply your knowledge:
- FAQ assistants
- AI coding assistants
- Research agents
- Documentation systems
- Multi-agent workflows
Capstone & Hackathon
Build a full AI system:
- End-to-end application development
- Real datasets and scenarios
- Collaboration and project review
- Portfolio-ready final project
Why This Course Stands Out
- Focuses on real-world AI system development
- Covers full lifecycle from idea to deployment
- Includes hands-on projects and portfolio work
- Uses modern industry tools and frameworks
- Designed for production-level implementation
Who This Course Is For
- Software engineers entering AI development
- Data scientists building real applications
- Developers moving beyond tutorials
- AI enthusiasts creating production systems
Prerequisites
- Basic programming knowledge
- Familiarity with Python and Git
- Understanding of APIs (recommended)
- Access to an AI API (OpenAI or alternatives)
About the Instructor
Alexey Grigorev is known for teaching practical AI engineering skills, helping developers build real-world systems using modern tools and scalable architectures.
Sales page : https://maven.com/alexey-grigorev/from-rag-to-agents
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