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Developing Generative AI Solutions

In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes the following:

- Defining a business use case

- Selecting a foundation model (FM)

- Improving the performance of an FM

- Evaluating the performance of an FM

- Deployment and its impact on business objectives

This course is a primer to generative AI courses, which dive deeper into concepts related to customizing an FM using prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning.

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What's inside

Syllabus

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Taught by AWS Instructor, recognized for their work with AWS

Examines generative AI, which could have applications in various industries and solve complex business problems

Provides a foundation for generative AI courses that explore advanced concepts in the field

Requires a basic understanding of generative AI concepts and applications

Emphasizes business use cases and potential impacts on business objectives, which may be beneficial for professionals seeking to apply generative AI in their organizations

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Reviews summary

Generative ai lifecycle on aws

According to learners, this course offers a largely positive and well-structured introduction to the generative AI application lifecycle, particularly within the AWS ecosystem. Students highlight its practical relevance and the value of hands-on labs for understanding model selection, evaluation, and deployment. While praised for its clear explanations and suitability for working professionals new to the domain, some note its nature as a primer course, suggesting it provides a high-level overview rather than deep technical dives. It's ideal for those seeking to connect AI solutions with business use cases.

Provides a foundational, high-level overview of Generative AI.

"This course is truly a primer, so set your expectations accordingly; it's an overview."

"It covers the lifecycle well, but I felt some parts... could have gone a bit deeper."

"I was hoping for more coding examples or advanced techniques, but it's a good starting point."

Stays current with the rapidly evolving field of Generative AI.

"The course content is highly relevant and updated regularly, which is impressive given how fast Generative AI is evolving."

"I appreciate that the course seems to be kept current, which is vital in this field."

"It addresses current trends in generative AI solutions effectively."

Presents complex concepts in an easy-to-understand manner.

"The lectures are clear and the course is very well-structured."

"The instructors explained complex concepts in a way that was easy to grasp."

"I found the explanations demystified the generative AI application process effectively."

Provides valuable practical experience using AWS services.

"The hands-on labs are incredibly helpful for understanding how to select and evaluate foundation models."

"The practical examples using AWS services were strong and gave me invaluable experience."

"I found the practical exercises useful for applying the concepts taught in the lectures."

Connects AI concepts to real-world business use cases.

"I particularly appreciated the focus on defining a business use case, which is crucial for real-world application."

"The practical relevance of this course is outstanding. It helps connect the dots between business needs and AI solutions."

"I learned to identify business use cases and select foundation models, which is directly applicable to my work."

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 Developing Generative AI Solutions with these activities:

Review the fundamentals of Generative AI

Show steps

Solidify understanding of the core concepts behind Generative AI and its applications.

Browse courses on Generative AI

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Read articles and watch videos on Generative AI
Review your notes or textbooks from previous courses on AI or machine learning
Take an online course or tutorial on Generative AI

Explore OpenAI's GPT-3 Examples

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Review foundational concepts of GPT-3's language generation capabilities to better understand generative AI's potential.

Browse courses on GPT-3

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Visit OpenAI's GPT-3 playground
Experiment with different prompts and settings
Analyze the generated text for quality and relevance

Join a Generative AI study group or discussion forum

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Connect with other learners, share knowledge, and get support in your Generative AI journey.

Browse courses on Generative AI

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Join a Generative AI study group or online discussion forum
Participate in discussions, ask questions, and share your insights
Collaborate with other members on projects or learning exercises

Six other activities

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Practice Prompt Engineering

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Deepen understanding of how to effectively use prompts to guide Generative AI models.

Browse courses on Prompt Engineering

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Experiment with different prompts to see how they affect the output of a Generative AI model
Create a set of prompts for a specific task or use case
Share your prompts with others and get feedback

Follow advanced tutorials on Generative AI techniques

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Expand knowledge of cutting-edge Generative AI techniques and methodologies.

Browse courses on Generative AI

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Identify specific areas of Generative AI you want to learn more about
Search for and select high-quality tutorials on those topics
Follow the tutorials step-by-step and implement the techniques in your own projects

Contribute to an open-source Generative AI project

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Gain practical experience while contributing to the Generative AI community.

Browse courses on Generative AI

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Find an open-source Generative AI project that aligns with your interests
Review the project documentation and contribute to discussions
Make code contributions or help with documentation and testing

Build a Generative AI application

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Gain hands-on experience in developing and deploying Generative AI applications.

Browse courses on Generative AI

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Choose a specific task or use case for your application
Select a suitable Generative AI model and API
Develop the front-end and back-end of your application
Test and deploy your application

Write a white paper or blog post on a specific Generative AI topic

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Deepen understanding of a chosen Generative AI topic and share knowledge with others.

Browse courses on Generative AI

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Choose a specific Generative AI topic that you are interested in and knowledgeable about
Research the topic thoroughly and gather relevant information
Organize your thoughts and write a well-structured white paper or blog post
Publish your white paper or blog post and share it with others

Participate in a Generative AI hackathon or competition

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Test skills and push boundaries in a practical and competitive environment.

Browse courses on Generative AI

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Find a relevant Generative AI hackathon or competition
Form a team or work on your own
Develop a creative and innovative Generative AI solution
Submit your solution and get feedback from experts

Career center

Learners who complete Developing Generative AI Solutions will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 45 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 Developing Generative AI Solutions.

Prompt Engineering for Generative AI

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Provides a comprehensive guide to prompt engineering, covering techniques for crafting effective inputs to generative AI models. It's particularly useful for understanding how to obtain reliable and predictable results, which is crucial for both beginners and those looking to deepen their practical skills. This book is valuable as a current reference for anyone working with generative AI.

Prompt Engineering for Generative AI

Kindle Edition

Natural Language Processing with Transformers,...

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Transformers are the architecture powering most modern Foundation Models, particularly LLMs. dives specifically into the Transformer architecture and its applications in NLP, offering practical guidance and examples using the Hugging Face Transformers library. It's highly relevant for understanding the core technology behind contemporary Foundation Models and is valuable as a hands-on guide.

Developing Generative AI Solutions

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What's inside

Syllabus

Traffic lights

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Reviews summary

Generative ai lifecycle on aws

Activities

Career center

Reading list

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