Course Includes:
- Price: FREE
- Enrolled: 892 students
- Language: English
- Certificate: Yes
- Difficulty: Beginner
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Course Folder
What You'll Learn
- Build a complete AI Operating System by combining agents
- memory
- and automation into one unified system
- Design and deploy intelligent AI agents using structured prompts
- reasoning
- and multi-step workflows
- Create and manage multi-agent systems with supervisor-worker architectures and task orchestration
- Implement memory-driven AI systems using vector databases
- embeddings
- and context injection techniques
- Develop tool-calling and automation pipelines to connect AI with real-world APIs
- workflows
- and data systems
- Build long-running autonomous AI systems with event-driven execution
- scheduling
- and feedback loops
- Optimize AI systems for performance
- cost
- and scalability including token efficiency and latency reduction
- Apply skills through real-world projects like personal AI assistants
- business automation systems
- and research agents
Requirements
- Basic understanding of programming concepts (Python or JavaScript is helpful but not mandatory)
- Familiarity with using web applications and APIs is a plus
- but everything will be explained step-by-step
- No prior experience in AI or machine learning is required — this course starts from fundamentals
- A computer or laptop with a stable internet connection
- Willingness to learn by building real-world projects and experimenting with AI systems
Description
This course contains the use of artificial intelligence.
Are you ready to go beyond using AI tools and start building complete AI systems?
This course is your step-by-step guide to designing and building a full AI Operating System using Claude, multi-agent architectures, memory systems, and automation pipelines. Instead of learning isolated tools, you will learn how to combine them into scalable, real-world systems.
You will start by understanding the foundations of Agentic AI, including how modern systems evolve from simple prompts to intelligent, autonomous workflows. Then, you’ll dive deep into building intelligent agents, designing multi-step reasoning systems, and implementing multi-agent orchestration.
One of the most powerful aspects of this course is learning how to build memory-driven AI systems, enabling your agents to retain context, learn from interactions, and make better decisions over time. You will also learn how to connect AI with real-world tools through function calling, APIs, and automation pipelines.
As you progress, you will build long-running autonomous systems, implement feedback loops, and optimize performance for cost, latency, and scalability.
Finally, you’ll apply everything through high-value capstone projects, including:
A personal AI operating system
A business automation pipeline
An autonomous research agent
By the end of this course, you won’t just understand AI — you’ll be able to design, build, and deploy real-world AI systems like an AI Architect.
Who this course is for:
- Developers who want to transition into AI Engineering and learn how to build real-world AI systems
- not just use tools
- Students and beginners who want a structured path into AI
- starting from fundamentals to advanced system design
- Professionals looking to automate workflows and increase productivity using intelligent AI systems
- Founders and entrepreneurs who want to build AI-powered products
- SaaS tools
- or automation businesses
- Anyone curious about how modern AI systems work and wants to go from prompt user → system builder
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