From the course: Fundamentals of AI Engineering: Principles and Practical Applications
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Course structure
From the course: Fundamentals of AI Engineering: Principles and Practical Applications
Course structure
- [Instructor] Now that we understand what AI engineering is and why we're focusing on LLMs, let me outline how this course is structured and what you can expect to build. We'll follow a practical building block approach where each concept builds on the previous one. This approach mimics how real world AI systems are developed, starting with basic components and progressively adding complexity as your understanding deepens. Throughout this course, you'll be working in GitHub Codespaces with real production-grade tools. There are no toy examples or oversimplified demos. You'll build components that could be deployed in actual production applications. This hands-on experience is essential for developing the muscle memory and intuition that separates theoretical knowledge from practical AI engineering expertise. You'll also notice that we're using the same tools that professional AI engineers use daily. This means that there might be a slightly steeper learning curve at the beginning…
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