IntermediateWhat You'll Learn
Go from AI engineering foundations to production-ready multi-agent systems. Learn Python, LLMs, AI agents, CrewAI, tools, memory, MCP, A2A, agent workflows, observability, CI/CD, and enterprise AI applications through a structured, hands-on learning journey.
3-Month Learning Journey
Month 1 — Foundations & AI Agents
Python → APIs → Git → LLMs → Prompt Engineering → AI Agents → Multi-Agent Systems
Build the technical foundation and learn how modern AI agents work.
Month 2 — Build & Integrate
Agent Workflows → Memory → Knowledge → Tools → Guardrails → MCP → Agent Capabilities
Build more capable agents that can use tools, access knowledge, maintain context, and perform complex tasks.
Month 3 — Orchestrate, Deploy & Scale
Collaboration → A2A → CrewAI Flows → Reliability → Observability → CI/CD → Enterprise AI
Learn to design reliable, production-oriented multi-agent systems and understand how agentic AI can be applied in real-world business environments.
Hands-On Projects & Assessments
The program emphasizes practical implementation rather than learning concepts in isolation.
You will work with projects and assessments such as:
- Automatic Code Review Agent
- Enhanced Code Review Crew
- Deep Research Crew
- Deep Research Flow
- Multi-Agent Coordination Systems
- AI Agent Tool Integrations
- Production-Oriented Agent Workflows
Technologies & Concepts
Throughout the program, you will work with modern AI engineering technologies and concepts including:
Python · LLMs · Generative AI · AI Agents · Multi-Agent Systems · CrewAI · CrewAI Flows · Tool Calling · Memory · Knowledge · MCP · A2A · APIs · Git · GitHub · Observability · CI/CD · Agent Orchestration
Who Is This Program For?
This program is designed for learners who want to move into AI engineering and agentic AI development.
It is suitable for:
- Python developers
- Software developers
- Web developers transitioning into AI
- AI/ML developers
- Data professionals
- Automation developers
- Computer science students and graduates
- Freelancers building AI solutions
- Entrepreneurs exploring AI-powered products
- Developers who want to specialize in AI agents and multi-agent systems
Prerequisites
You do not need prior experience building AI agents.
The first 3 weeks of the program are dedicated to Agentic AI Engineering Foundations, covering the Python, API, Git, LLM, prompt engineering, and AI application concepts needed for the core program.
A basic understanding of programming is helpful, but the program is structured to progressively build the required foundation before moving into advanced multi-agent development.
By the End of the Program, You Will Be Able To
- Build AI agents using Python and modern LLMs
- Design effective agent workflows
- Build and orchestrate multi-agent systems
- Develop AI agents with CrewAI
- Create CrewAI Flows for complex workflows
- Give agents access to external tools and APIs
- Implement memory and knowledge into agent systems
- Work with Model Context Protocol (MCP)
- Understand Agent-to-Agent (A2A) communication
- Apply guardrails and execution controls
- Debug and optimize AI agent systems
- Implement monitoring and observability
- Understand CI/CD for AI agents
- Design more reliable multi-agent architectures
- Evaluate AI agent use cases for businesses
- Build practical, production-oriented agentic AI applications
Your Journey
Learn the Foundations → Build AI Agents → Create Multi-Agent Systems → Add Tools & Knowledge → Orchestrate Agents → Build Reliable Workflows → Deploy & Monitor → Scale for Real-World Applications
Become an Agentic AI Engineer
Don't just learn how to use AI tools. Learn how to engineer AI agents and multi-agent systems that can reason, use tools, collaborate, execute workflows, and solve real-world problems.
Start your journey toward becoming an Agentic AI Engineer.
