Learn modern AI development by building agents, workflows, and real AI applications.
Sub Category
- Data Science
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Objectives
- 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.
Pre Requisites
- 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.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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