Gain hands-on, job-ready experience in artificial intelligence and machine learning.
From cloud computing to AI, the tech landscape continues to evolve at an exhilarating pace. And when it comes to the fields of Generative AI and machine learning, few tech giants are making a more consistent impact than Amazon. With the release and refinement of products like Sagemaker, Eliza Chatbot, Alexa, and Bedrock, Amazon has made a habit of innovation. That’s why we’re thrilled to introduce Udacity’s latest collaboration with AWS: a new in-depth course on all things Generative AI.
We’ve co-created a comprehensive program together that will empower learners with the knowledge needed to harness the potential of Generative AI. Whether you’re a seasoned developer looking to enhance your toolkit or an aspiring machine learning enthusiast, this course will equip you with the skills required to innovate, create, and transform the future of whatever it is you do using the power of this groundbreaking technology. Here’s what you’ll learn.
What Will I Learn in Introducing Generative AI with AWS?
Lesson 1: Artificial intelligence in context
This lesson aims to provide a top-level understanding of how artificial intelligence fits into broader societal and historical contexts. It explores the evolution of artificial intelligence from its early stages through to modern developments – and how we interact with AI on a daily basis, often without knowing it.
Lesson 2: The fundamentals of artificial intelligence and machine learning
This lesson serves as an introduction to the key concepts and principles that underpin artificial intelligence and machine learning. It starts with a definition of machine learning followed by an explanation of its three different types (supervised learning, unsupervised learning, and reinforcement learning). You’ll also dive into the two approaches of machine learning (traditional ML and deep learning) along with the problems each is capable of solving. We’ll wrap this lesson up by covering the two categories of machine learning, one of which is Generative AI.
Lesson 3: Understanding and using Large Language Models (LLMs)
This lesson explores Large Language Models (LLMs), particularly their evolution over time and the underlying architectures they use. The lesson focuses on modern transformer-based architectures, looking at how these models are trained with reference to artificial neural networks discussed in the previous lesson. We’ll then explore these concepts further through a variety of prompting methods and model fine-tuning.
Lesson 4: Generative AI in real-world applications
This final lesson fuses the foundational technical knowledge explored in the previous lesson with how Generative AI can be responsibly and inclusively used within society. You’ll learn more about all things ethical use, creative application, diversity, and policy implications when it comes to GenAI.
The Capstone Project: Building a Domain Expert Model
In the course’s final project, you will be tasked with fine-tuning a foundation model for domain adaptation to become a domain expert using AWS Sagemaker and unstructured text. Then, you will evaluate your model using prompt engineering skills learned in the course.
What will I be able to do after this course?
After this course, learners will gain a comprehensive understanding of AI’s historical and societal context, exploring its evolution and impact. You’ll also learn how to differentiate between AI and ML, while being introduced to primary ML types, LLMs, and more. Participants will gain an understanding of the ethical, societal, and economic implications of Generative AI, emphasizing responsible and inclusive deployment practices. Throughout your learning experience, engaging exercises such as AI-driven case studies and hands-on coding challenges will reinforce your understanding of Generative AI.
Who should take this course?
The short answer is any tech professional curious to learn more about the many applications of GenAI! The long answer gets more specific. This course caters to beginners at a foundational level who are interested in Generative AI. Prior knowledge of basic Python and elementary algebra is recommended before enrolling. No matter if you’re looking to dive into the fundamentals of AI or seeking to apply these teachings on the job right away, this course offers a structured approach to understanding GenAI concepts and applications.
About the Instructor
Matthew Purcell is a Senior Technical Trainer at AWS specializing in artificial intelligence and machine learning. Prior to joining AWS, Matt was a high school teacher and head of department for 14 years, integrating AWS AI/ML cloud technologies into high school digital technologies curriculum. His passion is making advanced technologies approachable for everyone, which he has continued doing at AWS through developing educational content for AWS DeepRacer, AI/ML workshops for AWS Summits and AWS re:Invent.
Ready to learn GenAI from the most trusted names in tech?
When it comes to staying relevant in the tech industry, being ahead of the curve is essential for your career growth and standing. With our new Generative AI course co-created with AWS, you have the opportunity to gain hands-on AI & ML experience from the practitioners shaping the future of the space. Curious to learn more? Visit the course page today.
