Foundations of AI, LLMs, and Development Environments

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will gain a comprehensive understanding of AI, Large Language Models (LLMs), and their development environments. You'll start by learning the foundational principles of AI and LLMs, followed by hands-on demonstrations of the projects you'll build, giving you practical experience. The course is structured progressively, from environment setup to deep dives into Python programming, culminating in the construction of LLMs using libraries like Hugging Face’s Transformers. As you work through each section, you'll be guided step-by-step with tutorials and practice exercises that reinforce key concepts. The journey includes setting up your development environment, mastering Python fundamentals, exploring deep learning and machine learning, and diving into the complexities of Generative AI. Key concepts such as the transformer architecture, self-attention mechanism, and using OpenAI APIs will be explored in detail. By completing each module, you will build your coding and problem-solving skills, progressively building toward more advanced techniques in AI development. This course is ideal for those wanting to break into AI and machine learning development. The target audience includes beginners with some basic understanding of programming, specifically those interested in AI applications. No prior experience in AI is required, though familiarity with Python will be beneficial. By the end of the course, you will be able to set up your development environment for AI projects, understand and implement LLMs using transformer architecture, create and deploy AI models, and integrate OpenAI’s models through API calls.