Agentic AI Engineering with Claude Code
Data Science Academy
AI Systems & Agentic AI Educator
Build AI systems that act—not just respond
Most people today are learning AI the wrong way.
They rely on prompts, tools, and shortcuts—without understanding how to build real systems. This creates a major gap between using AI and engineering AI solutions that work in real-world environments.
Companies are no longer looking for people who can just “use ChatGPT.”
They need professionals who can design autonomous AI systems that can plan, reason, use tools, and execute workflows independently.
That’s exactly the gap this course solves.
This course teaches you how to move from isolated AI usage to building agentic AI systems—systems that can make decisions, handle multi-step tasks, integrate with APIs, and improve over time.
You’ll learn how to design intelligent agents, implement memory and context, connect to real systems, and build multi-agent architectures that reflect how modern AI products are built.
If you’ve ever felt stuck watching tutorials without knowing how to apply AI in real scenarios—this course gives you the structure, systems thinking, and hands-on experience to change that.
This is not about learning tools.
This is about learning how to build the future of AI.
What you’ll learn
Go from using AI tools to building autonomous AI systems that plan, act, and solve real-world problems
Learn agent architecture (brain, tools, memory, environment)
Build planning + reasoning workflows step by step
Implement goal-driven execution systems
Convert skills into callable tools
Connect agents with APIs, databases, workflows
Build multi-step tool execution pipelines
Implement short-term and long-term memory
Use context injection and summarization techniques
Optimize token usage and context selection
Design supervisor-worker architectures
Implement task delegation and coordination
Enable agent communication and synchronization
Build observe → evaluate → improve cycles
Apply iterative refinement strategies
Implement basic reinforcement patterns
Improve performance and reduce cost
Design scalable agent architectures
Build your own AI operating system
Learn directly from Data
Data Science Academy
Building real-world AI systems and agentic architectures
Who this course is for
Developers who want to move from using AI tools to building real AI systems and autonomous agents
Data professionals exploring AI engineering, automation, and building intelligent workflows
Builders and founders looking to create AI-powered products, tools, or SaaS systems
What's included
Live sessions
Learn directly from Data Science Academy in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
Week 1
Day 1 - What is Agentic AI?
Day 2 - From Skills to Agents
Day 3 - Agent Components Deep Dive
Day 4 - Planning & Reasoning Systems
Day 5 - Decision Making in Agents
Day 6 - Short-Term vs Long-Term Memory
Day 7 - Building Context-Aware Agents
Week 2
Day 8 - Tool Calling & Skill Execution
Day 9 - External Integrations
Day 10 -Single Agent → Multi-Agent Systems
Day 11 - Agent Orchestration Patterns
Day 12 - Communication Between Agents
Day 13 - Feedback Loops & Self-Improvement
Day 14 - Debugging & Safety
Schedule
Live sessions
1 hr / week
Projects
4 hrs / week
Async content
6 hrs / week
Frequently asked questions
$100
USD