Learn modern AI development by building agents, workflows, and real AI applications.

What you'll learn
✓ Design and architect end-to-end AI systems, including UI, backend logic, memory, tools, and automation workflows.
✓ Build and deploy AI agents that can reason, execute actions, and integrate with external tools and APIs.
✓ Implement structured outputs, validation guardrails, and safety checks to make AI systems reliable and production-ready.
✓ Develop stateful AI applications with multi-turn memory and persistent session handling.
✓ Create and automate multi-step AI workflows that chain reasoning, extraction, decision logic, and action execution.
✓ Deploy AI applications securely to the cloud using environment variables and production best practices.
✓ Document, demo, and package AI projects into portfolio-ready assets suitable for job applications or client work.
✓ Apply prompt engineering, evaluation strategies, and regression testing to improve AI system performance over time.

Requirements
Basic familiarity with Python (variables, functions, and installing packages with pip).
Basic familiarity with Python (variables, functions, and installing packages with pip).
Ability to run commands in a terminal (basic command-line usage).
Ability to run commands in a terminal (basic command-line usage).
An internet connection for accessing AI APIs and cloud deployment platforms.
An internet connection for accessing AI APIs and cloud deployment platforms.

Description
"This course contains the use of artificial intelligence"

14 Days to Building AI Systems & Agents is a hands-on, implementation-focused program designed to teach you how to build real, production-ready AI applications from the ground up. This is not a theory-heavy course. It is a practical, structured journey into AI system architecture, LLM integration, AI agents, and automation workflows.

Over 14 days, you will move beyond simple prompt experimentation and learn how modern AI development actually works. You will design full-stack AI systems that combine frontend interfaces, backend APIs, multi-turn memory, tool execution, and validation guardrails. Instead of building isolated scripts, you will build cohesive AI products.

The course begins with core foundations: understanding how AI systems, machine learning models, and large language models (LLMs) fit together. You will learn how to work with LLM APIs, manage tokens and temperature, and implement structured prompts that produce reliable outputs. From there, you will progress into building stateful systems with persistent memory, enabling your AI applications to handle multi-turn conversations and maintain context.

As the course advances, you will implement structured JSON outputs, enforce schema validation, and apply AI safety guardrails to make your systems dependable. You will also build practical AI agents that can execute tools, interact with files, and perform multi-step reasoning. These agents will not just respond—they will act.

You will then learn how to design and implement automation workflows, chaining multiple AI steps into deterministic pipelines. By combining reasoning, tools, and validation, you will create end-to-end AI workflows capable of solving real operational tasks.

Deployment is a core focus. You will package your system, configure environment variables securely, and deploy your AI application to the cloud. You will learn how to move from a local prototype to a live, shareable product.

Finally, you will transform your capstone into a portfolio-ready AI project. You will write professional documentation, create architecture diagrams, record a demo, and polish your GitHub repository. By the end of the course, you will have a complete AI product demonstrating skills in AI system design, agent architecture, workflow automation, API integration, and cloud deployment.

This course is ideal for developers, product builders, and technical professionals who want practical experience building modern AI systems. No advanced math is required. You only need basic Python knowledge and a willingness to build.

If you want to go beyond prompts and learn how to engineer real AI-powered applications, integrate AI agents, and deploy reliable AI workflows, this 14-day program gives you the structure, clarity, and hands-on experience to do exactly that.

Build. Integrate. Deploy. Ship real AI systems.

Who this course is for
Developers who want to move beyond basic prompts and learn how to build complete AI systems and agents.
Software engineers interested in integrating LLMs, memory, tools, and automation into real-world applications.
Product builders and startup founders who want to prototype and launch AI-powered applications quickly.
Technical professionals looking to transition into AI engineering or agent-based system development.
Backend or full-stack developers who want hands-on experience deploying production-ready AI applications.
AI enthusiasts who have experimented with ChatGPT or APIs and now want to understand system architecture and integration.
Freelancers and consultants who want to offer AI automation and agent-building services to clients.
Students and career switchers aiming to build a strong AI portfolio with deployable projects.