Overview

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.

Syllabus

Introduction

In this module, we will introduce the course’s objectives and lay out the structure that will guide you through mastering AI and LLM engineering. You'll gain an overview of the course journey, including a demo of what you’ll be building and strategies for getting the most out of your learning experience.

Development Environment Setup

In this module, we will guide you through setting up your development environment, including installing Python and Visual Studio Code, ensuring you’re ready for hands-on programming in the AI and LLM space. You will be equipped to start coding immediately with proper setup and configuration.

Optional: Python Deep Dive—Master Python Fundamentals

In this module, we will provide an in-depth exploration of Python, covering essential topics such as variables, data types, control structures, functions, and object-oriented programming. Whether you're new to Python or need a refresher, this section will ensure you're proficient in the language for AI development.

Understanding Deep and Machine Learning

In this module, we will take a comprehensive look at deep learning and machine learning, breaking down their core components and how they relate to AI. You’ll gain clarity on the essential elements of neural networks and how they differ from traditional machine learning techniques.

Generative AI: Architecture and Core Technologies

In this module, we will delve into the world of Generative AI, discussing its architecture, key technologies, and the challenges it faces. By the end, you’ll have a solid understanding of how GenAI systems function and the components that make them work.

LLMs: Concepts, Architecture, and Hands-On Development

In this module, we will introduce you to Large Language Models (LLMs), including the transformer architecture and the self-attention mechanism. You’ll also engage in hands-on development, building and enhancing your own LLM with the popular Hugging Face library.

OpenAI Models and Setup

In this module, we will walk you through setting up an OpenAI account, generating your API key, and using the API to make your first call to an OpenAI model. You'll gain practical skills in integrating OpenAI’s models into your own AI applications.