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Matthew Purcell
Learn the fundamentals, historical context, and real-world applications of Generative AI in this online course. Explore AI and ML foundations, transformer-based architectures, and ethical deployment. Enroll today!
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Basic Python
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/wdcdy0/introducing
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What's inside
Syllabus
Explore AI's evolution and everyday impact, covering its history, societal prevalence, and industry applications.
Introduction to AI and ML basics, covering their relationship, machine learning models, types, and approaches, plus generative AI.
Read more
Syllabus
Explore AI's evolution and everyday impact, covering its history, societal prevalence, and industry applications.
Introduction to AI and ML basics, covering their relationship, machine learning models, types, and approaches, plus generative AI.
Read more
This lesson covers LLMs, focusing on their evolution, transformer architectures, training methods, prompt engineering, and fine-tuning.
Examine generative AI's societal impact, focusing on creative applications, ethical use, diversity in AI, and policy implications.
In this project, you'll fine-tune a text generation large language foundation model for domain adaptation to be a domain expert using AWS Sagemaker
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the fundamentals of generative AI, which is a rapidly growing field
Explores the historical context and real-world applications of generative AI
Covers AI and ML foundations, transformer-based architectures, and ethical deployment
Provides hands-on experience through a project where learners fine-tune a text generation large language foundation model
Taught by Matthew Purcell, an experienced instructor in the field
Offered through Udacity, a reputable online learning platform
Save this course
Save Introducing Generative AI with AWS to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introducing Generative AI with AWS with these
activities:
Review Deep Learning
Show steps
Reviewing this book will establish a foundational understanding of deep learning and aid in understanding the related concepts explored in the course.
View
Deep Learning
on Amazon
Show steps
-
Read chapters 1-3 and make notes on key concepts such as artificial neural networks, deep learning models, and their applications.
-
Complete the practice exercises provided at the end of each chapter to reinforce your understanding.
-
Summarize the main ideas presented in each chapter and discuss them with a study partner or in an online forum.
Review Machine Learning Fundamentals
Show steps
Refreshing your knowledge of Machine Learning fundamentals will help you build a stronger foundation for understanding Generative AI concepts.
Browse courses on
Machine Learning Fundamentals
Show steps
-
Review key concepts such as supervised and unsupervised learning, model evaluation, and feature engineering.
-
Complete online exercises or tutorials that cover these fundamentals.
-
Discuss these concepts with peers or an instructor to clarify your understanding.
Follow Transformer-Based Architectures Tutorials
Show steps
Exploring tutorials on Transformer-Based Architectures will help you gain a deeper understanding of the underlying mechanisms used in Generative AI.
Browse courses on
Attention Mechanisms
Show steps
-
Identify tutorials that provide clear explanations and hands-on examples.
-
Follow the tutorials step-by-step and implement the concepts in your own code.
-
Experiment with different parameters and observe the effects on model performance.
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Solve AI and ML practice problems
Show steps
Practice solving AI and ML problems to reinforce your understanding of the concepts and algorithms covered in the course.
Show steps
-
Identify a practice problem or exercise.
-
Break down the problem into smaller steps.
-
Develop a solution using AI and ML techniques.
-
Test and evaluate your solution.
Follow tutorials on Transformer-based architectures
Show steps
Explore tutorials that provide step-by-step guidance on building and implementing Transformer-based architectures to strengthen your technical skills.
Browse courses on
Transformer Architectures
Show steps
-
Search for online tutorials or courses on Transformer-based architectures.
-
Choose a tutorial that aligns with your learning style and skill level.
-
Follow the instructions and build a project using Transformer-based techniques.
-
Document your understanding and findings.
Attend a workshop on ethical deployment of Generative AI
Show steps
Participate in a workshop that explores the ethical considerations and best practices for deploying Generative AI systems, ensuring responsible use.
Show steps
-
Research and identify relevant workshops or events.
-
Register and attend the workshop.
-
Engage with speakers and other attendees.
-
Reflect on the ethical implications and insights gained.
Coding Mini Projects
Show steps
Completing coding mini-projects will allow you to apply concepts learned in the course to practical scenarios, improving your understanding and coding skills.
Browse courses on
AI Coding
Show steps
-
Choose a beginner-friendly mini-project related to generative AI.
-
Gather the necessary resources and set up your development environment.
-
Break down the project into smaller tasks and implement them step by step.
-
Test and debug your code to ensure it works correctly.
-
Refactor your code to improve its efficiency and maintainability.
Study Group Discussions
Show steps
Participating in study group discussions will provide opportunities to engage with peers, clarify doubts, and strengthen your understanding of course concepts.
Show steps
-
Join or form a study group with fellow learners.
-
Review course materials and identify topics for discussion.
-
Facilitate discussions, ask questions, and share insights.
-
Summarize key points and document any unresolved questions for further research.
Create a presentation on a real-world application of Generative AI
Show steps
Develop a presentation that showcases a specific use case of Generative AI in the real world, demonstrating its potential and impact.
Browse courses on
Generative AI
Show steps
-
Research and identify a specific industry or domain where Generative AI is being applied.
-
Gather data and case studies to support your presentation.
-
Design and create a visually engaging presentation.
-
Practice your presentation and seek feedback from peers or instructors.
Volunteer for a project involving Generative AI
Show steps
Contribute your skills and knowledge to a project that leverages Generative AI for social good or research purposes, expanding your practical experience.
Browse courses on
Generative AI
Show steps
-
Identify organizations or initiatives working with Generative AI.
-
Reach out to inquire about volunteer opportunities.
-
Contribute your time and expertise to the project.
-
Reflect on your contributions and the impact of the project.
Generative AI Project
Show steps
Developing a Generative AI project will allow you to apply the knowledge and skills learned in the course to create a substantial and practical application.
Show steps
-
Define the scope and objectives of your project.
-
Gather and prepare the necessary data.
-
Choose and implement an appropriate generative AI model.
-
Train and evaluate your model.
-
Document your project, including your methodology, results, and any challenges encountered.
Review Deep Learning
Show steps
Reviewing this book will establish a foundational understanding of deep learning and aid in understanding the related concepts explored in the course.
View
Deep Learning
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 and make notes on key concepts such as artificial neural networks, deep learning models, and their applications.
- Complete the practice exercises provided at the end of each chapter to reinforce your understanding.
- Summarize the main ideas presented in each chapter and discuss them with a study partner or in an online forum.
Review Machine Learning Fundamentals
Show steps
Refreshing your knowledge of Machine Learning fundamentals will help you build a stronger foundation for understanding Generative AI concepts.
Browse courses on
Machine Learning Fundamentals
Show steps
Show steps
Show steps
- Review key concepts such as supervised and unsupervised learning, model evaluation, and feature engineering.
- Complete online exercises or tutorials that cover these fundamentals.
- Discuss these concepts with peers or an instructor to clarify your understanding.
Follow Transformer-Based Architectures Tutorials
Show steps
Exploring tutorials on Transformer-Based Architectures will help you gain a deeper understanding of the underlying mechanisms used in Generative AI.
Browse courses on
Attention Mechanisms
Show steps
Show steps
Show steps
- Identify tutorials that provide clear explanations and hands-on examples.
- Follow the tutorials step-by-step and implement the concepts in your own code.
- Experiment with different parameters and observe the effects on model performance.
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Solve AI and ML practice problems
Show steps
Practice solving AI and ML problems to reinforce your understanding of the concepts and algorithms covered in the course.
Show steps
Show steps
Show steps
- Identify a practice problem or exercise.
- Break down the problem into smaller steps.
- Develop a solution using AI and ML techniques.
- Test and evaluate your solution.
Follow tutorials on Transformer-based architectures
Show steps
Explore tutorials that provide step-by-step guidance on building and implementing Transformer-based architectures to strengthen your technical skills.
Browse courses on
Transformer Architectures
Show steps
Show steps
Show steps
- Search for online tutorials or courses on Transformer-based architectures.
- Choose a tutorial that aligns with your learning style and skill level.
- Follow the instructions and build a project using Transformer-based techniques.
- Document your understanding and findings.
Attend a workshop on ethical deployment of Generative AI
Show steps
Participate in a workshop that explores the ethical considerations and best practices for deploying Generative AI systems, ensuring responsible use.
Show steps
Show steps
Show steps
- Research and identify relevant workshops or events.
- Register and attend the workshop.
- Engage with speakers and other attendees.
- Reflect on the ethical implications and insights gained.
Coding Mini Projects
Show steps
Completing coding mini-projects will allow you to apply concepts learned in the course to practical scenarios, improving your understanding and coding skills.
Browse courses on
AI Coding
Show steps
Show steps
Show steps
- Choose a beginner-friendly mini-project related to generative AI.
- Gather the necessary resources and set up your development environment.
- Break down the project into smaller tasks and implement them step by step.
- Test and debug your code to ensure it works correctly.
- Refactor your code to improve its efficiency and maintainability.
Study Group Discussions
Show steps
Participating in study group discussions will provide opportunities to engage with peers, clarify doubts, and strengthen your understanding of course concepts.
Show steps
Show steps
Show steps
- Join or form a study group with fellow learners.
- Review course materials and identify topics for discussion.
- Facilitate discussions, ask questions, and share insights.
- Summarize key points and document any unresolved questions for further research.
Create a presentation on a real-world application of Generative AI
Show steps
Develop a presentation that showcases a specific use case of Generative AI in the real world, demonstrating its potential and impact.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Research and identify a specific industry or domain where Generative AI is being applied.
- Gather data and case studies to support your presentation.
- Design and create a visually engaging presentation.
- Practice your presentation and seek feedback from peers or instructors.
Volunteer for a project involving Generative AI
Show steps
Contribute your skills and knowledge to a project that leverages Generative AI for social good or research purposes, expanding your practical experience.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify organizations or initiatives working with Generative AI.
- Reach out to inquire about volunteer opportunities.
- Contribute your time and expertise to the project.
- Reflect on your contributions and the impact of the project.
Generative AI Project
Show steps
Developing a Generative AI project will allow you to apply the knowledge and skills learned in the course to create a substantial and practical application.
Show steps
Show steps
Show steps
- Define the scope and objectives of your project.
- Gather and prepare the necessary data.
- Choose and implement an appropriate generative AI model.
- Train and evaluate your model.
- Document your project, including your methodology, results, and any challenges encountered.
Career center
Learners who complete Introducing Generative AI with AWS will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer collects, analyzes, and interprets data to train machine learning models. This course may help someone building a foundation for a career as a Machine Learning Engineer. It helps build a foundation in AI and ML fundamentals, transformer-based architectures, and ethical deployment. This course may be particularly useful for engineers who wish to enter the AI field, or for AI professionals who wish to advance their careers.
AI Engineer
AI Engineer
An AI Engineer designs and develops artificial intelligence systems. This course may help someone building a foundation for a career as an AI Engineer. It helps build a foundation in AI and ML fundamentals, transformer-based architectures, and ethical deployment. This course may be particularly useful for engineers who wish to enter the AI field, or for AI professionals who wish to advance their careers.
Data Scientist
Data Scientist
A Data Scientist collects, analyzes, and interprets data to solve business problems. This course may help someone building a foundation for a career as a Data Scientist. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the data science field, or for data science professionals who wish to advance their careers.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may help someone building a foundation for a career as a Software Engineer. It helps build a foundation in transformer-based architectures and ethical deployment. This course may be particularly useful for those who wish to enter the software engineering field, or for software engineers who wish to advance their careers.
Product Manager
Product Manager
A Product Manager plans, develops, and launches products. This course may help someone building a foundation for a career as a Product Manager. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the product management field, or for product managers who wish to advance their careers.
Operations Manager
Operations Manager
An Operations Manager plans, executes, and delivers operational activities. This course may help someone building a foundation for a career as an Operations Manager. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the operations management field, or for operations managers who wish to advance their careers.
Consultant
Consultant
A Consultant provides advice and guidance to businesses. This course may help someone building a foundation for a career as a Consultant. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the consulting field, or for consultants who wish to advance their careers.
Risk Manager
Risk Manager
A Risk Manager plans, executes, and delivers risk management activities. This course may help someone building a foundation for a career as a Risk Manager. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the risk management field, or for risk managers who wish to advance their careers.
Quality Assurance Analyst
Quality Assurance Analyst
A Quality Assurance Analyst plans, executes, and delivers quality assurance activities. This course may help someone building a foundation for a career as a Quality Assurance Analyst. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the quality assurance field, or for quality assurance analysts who wish to advance their careers.
Marketing Manager
Marketing Manager
A Marketing Manager plans, develops, and executes marketing campaigns. This course may help someone building a foundation for a career as a Marketing Manager. It helps build a foundation in the societal impact of generative AI. This course may be particularly useful for those who wish to enter the marketing field, or for marketing managers who wish to advance their careers.
Compliance Manager
Compliance Manager
A Compliance Manager plans, executes, and delivers compliance activities. This course may help someone building a foundation for a career as a Compliance Manager. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the compliance field, or for compliance managers who wish to advance their careers.
Project Manager
Project Manager
A Project Manager plans, executes, and delivers projects. This course may help someone building a foundation for a career as a Project Manager. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the project management field, or for project managers who wish to advance their careers.
Sales Manager
Sales Manager
A Sales Manager plans, develops, and executes sales strategies. This course may help someone building a foundation for a career as a Sales Manager. It helps build a foundation in the societal impact of generative AI. This course may be particularly useful for those who wish to enter the sales field, or for sales managers who wish to advance their careers.
Business Analyst
Business Analyst
A Business Analyst analyzes business needs and develops solutions to improve business processes. This course may help someone building a foundation for a career as a Business Analyst. It helps build a foundation in the societal impact of generative AI. This course may be particularly useful for those who wish to enter the business analysis field, or for business analysts who wish to advance their careers.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to solve business problems. This course may help someone building a foundation for a career as a Data Analyst. It helps build a foundation in transformer-based architectures, the societal impact of generative AI, and ethical deployment. This course may be particularly useful for those who wish to enter the data analysis field, or for data analysts who wish to advance their careers.
For more career information including salaries, visit:
OpenCourser.com/course/wdcdy0/introducing
Reading list
We've selected five books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introducing Generative AI with AWS.
Provides a comprehensive overview of deep learning techniques for natural language processing, including generative models such as language models and text generators. It serves as a good reference for additional reading.
Introduces the TensorFlow 2.0 framework, which is commonly used for developing and deploying generative AI models. It is recommended for those who want to gain practical experience in implementing generative AI projects.
This classic textbook in speech and language processing provides a comprehensive overview of fundamental concepts and techniques, including those used in generative AI models for natural language generation. It is suitable as a reference or for background reading.
Save
Focuses on generative adversarial networks (GANs), which are a type of generative AI model. It provides a detailed explanation of GAN architectures, training methods, and applications.
Save
Provides a comprehensive overview of AI, including the use of generative AI. It valuable resource for anyone who wants to learn more about the potential benefits and challenges of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wdcdy0/introducing
Share
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Effort
4 weeks
Via
Udacity
Instructor
Matthew Purcell
Language
English
Good to know
Teaches the fundamentals of generative AI, which is a rapidly growing field
Explores the historical context and real-world applications of generative AI
Covers AI and ML foundations, transformer-based architectures, and ethical deployment
Provides hands-on experience through a project where learners fine-tune a text generation large language foundation model
Taught by Matthew Purcell, an experienced instructor in the field
Offered through Udacity, a reputable online learning platform
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