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Noah Gift
In this cutting-edge course, you'll discover how to:
- Leverage the power of generative AI to rapidly prototype and iterate on ideas
- Apply prompt engineering techniques to guide AI models towards desired outputs
- Utilize AI pair programming tools to boost developer productivity and creativity
- Integrate generative AI seamlessly into your DevOps workflow for maximum impact
Read more
In this cutting-edge course, you'll discover how to:
- Leverage the power of generative AI to rapidly prototype and iterate on ideas
- Apply prompt engineering techniques to guide AI models towards desired outputs
- Utilize AI pair programming tools to boost developer productivity and creativity
- Integrate generative AI seamlessly into your DevOps workflow for maximum impact
Read more
In this cutting-edge course, you'll discover how to:
- Leverage the power of generative AI to rapidly prototype and iterate on ideas
- Apply prompt engineering techniques to guide AI models towards desired outputs
- Utilize AI pair programming tools to boost developer productivity and creativity
- Integrate generative AI seamlessly into your DevOps workflow for maximum impact
Whether you're a seasoned software engineer or just starting your coding journey, this course will equip you with the skills and knowledge to push the boundaries of what's possible with AI-powered software development. Get ready to transform the way you build software and stay ahead of the curve in this exciting new era of AI-driven innovation.
Register for this course and see more details by visiting:
OpenCourser.com/course/f6fnm6/agile
What's inside
Learning objectives
- Defining generative ai and its software development applications
- Applying prompt engineering to guide ai model outputs
- Understanding few-shot learning for teaching ai models new tasks
- Utilizing ai pair programming tools for enhanced productivity
- Integrating generative ai with devops best practices
- Defining generative ai and its software development applications
- Applying prompt engineering to guide ai model outputs
- Understanding few-shot learning for teaching ai models new tasks
- Utilizing ai pair programming tools for enhanced productivity
- Integrating generative ai with devops best practices
Syllabus
• Module 1: About the Course (Module)
◦ Meet your instructors (Lesson)
‣ Course Introduction (Video, 1m 23s)
‣ Instructor Background: Noah Gift (Reading, 1m)
Read more
Syllabus
• Module 1: About the Course (Module)
◦ Meet your instructors (Lesson)
‣ Course Introduction (Video, 1m 23s)
‣ Instructor Background: Noah Gift (Reading, 1m)
Read more
‣ Connect with your instructors (Reading, 1m)
‣ Course structure and etiquette (Reading, 1m)
‣ Meet and Greet (optional) (Discussion Prompt, 1m)
◦ An Economic Framework for Understanding Artificial Intelligence (Lesson)
‣ Key Terms (Reading, 10m)
‣ White House Framework 2024 for Understanding AI (Reading, 10m)
‣ Quiz-Understanding AI (Assignment, 10m)
‣ Lesson Reflection (Reading, 10m)
• Module 2: Introduction to Agile Concepts (Module)
◦ Historical Origins of Agile-Waterfall Planning (Lesson)
◦ Effective Technical Teamwork (Lesson)
‣ Building a Playground vs Growing a Plant (Video, 1m 58s)
‣ Waterfall Planning (Video, 2m 25s)
‣ Ford Motor Company Long Beach Assembly Plant (Reading, 10m)
‣ Origins of Waterfall-Managing the Development of Large Software Systems (Reading, 10m)
‣ The Mythical Man-Month: Essays on Software Engineering (Reading, 10m)
‣ Design and Acquisition of Software for Defense Systems (Reading, 10m)
◦ Historical Origins of Agile-Toyota Way (Lesson)
‣ Forms of Waste (Muda) with AI (Reading, 10m)
‣ Five Whys (5 Whys) (なぜなぜ分析 - Naze Naze Bunseki) (Video, 4m 7s)
‣ The 14 principles of the Toyota way: An executive summary of the culture behind TPS (Reading, 10m)
‣ Muda: Seven Types of Waste (Muda) (Reading, 10m)
‣ Kaizen- Continuous Improvement (Reading, 10m)
‣ Introduction to Effective Technical Teamwork (Video, 37s)
◦ Foundational Agile Concepts (Lesson)
‣ Pragmatic Agile (Video, 2m 42s)
‣ Productivity Techniques (Video, 4m 32s)
‣ State of Agile Report (Reading, 10m)
‣ Atlassian Agile Project Management: Scrum and Kanban (Reading, 10m)
‣ Coursera: Scrum vs Kanban (Reading, 10m)
‣ Coursera: What is Agile? (Reading, 10m)
‣ Quiz-Agile Concepts (Assignment, 10m)
• Module 3: Developing Effective Technical Communication (Module)
◦ Effective Technical Discussions (Lesson)
‣ AI Pair Programming Paradigm Shift (Video, 3m 5s)
‣ Introduction to Technical Discussions (Video, 1m 46s)
‣ Technical Discussions with Markdown, GitHub and Jupyter/Colab (Video, 10m 50s)
‣ Creating Technical Demo Videos (Video, 1m 41s)
‣ Effective Critical Thinking (Video, 5m 10s)
‣ Effective Technical Triple Threat (Video, 2m 47s)
‣ Effective Technical Discussions (Reading, 10m)
‣ Create Markdown in Jupyter (Ungraded Lab, 1h)
‣ Reproducible Technical Discussion (Discussion Prompt, 10m)
‣ Effective Technical Teamwork (Video, 6m 3s)
‣ Team Performance Analysis (Discussion Prompt, 10m)
◦ Effective Technical Project Management (Lesson)
‣ Diagram Prompt Engineering (Video, 3m 47s)
‣ Introduction to Technical Project Management (Video, 2m 3s)
‣ Effective Technical Project Management (Video, 5m 29s)
‣ Ticket Tracking with Trello (Video, 4m 31s)
‣ Project Planning with Spreadsheets (Video, 5m 1s)
‣ Project Management Anti-Patterns (Video, 5m)
‣ Effective Technical Project Management (Reading, 10m)
‣ Agile vs. Waterfall Planning (Discussion Prompt, 10m)
‣ Unit Testing (Ungraded Lab, 1h)
◦ Applied Practice: Developing a Project Plan (Lesson)
‣ Project Plan for Course 1 Project (Reading, 10m)
‣ Course 1 Project Plan (Discussion Prompt, 1h)
◦ Graded Quiz (Lesson)
‣ Graded Quiz - Technical Communication (Assignment, 3h)
• Module 4: Developing Effective AI Automation (Module)
◦ Untitled Lesson (Lesson)
‣ Course Reflection (Reading, 10m)
‣ AIOps (Video, 1m 53s)
‣ Generative AI Use Cases (Reading, 10m)
‣ Use CodeWhisperer (Amazon Q) for Rust (Video, 7m 47s)
‣ Summarize Old Man and the Sea (Video, 5m 28s)
‣ Building Blocks of GenAI with Whisper.cpp (Video, 2m 51s)
‣ Untitled (Assignment, 3h)
• Module 5: Conclusion and Next Steps (Module)
‣ Cargo Cult Science (Reading, 10m)
‣ Cargo Cult Agile (Reading, 10m)
‣ The Perils of Cargo Cult Procedure Compliance (Reading, 10m)
‣ Real World Management (Reading, 10m)
‣ Next Steps (Reading, 1m)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills and knowledge useful for software development that employers seek today
Taught by recognized instructors in the AI field
Builds on existing foundation for intermediate learners
May require students to come in with extensive background knowledge
Save this course
Save Agile with AI to your list so you can find it easily later:
Save
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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 Agile with AI with these
activities:
Review Agile Concepts
Show steps
Refresher the core concepts of Agile methodologies, such as Scrum and Kanban, to better understand their application in the course.
Browse courses on
Agile
Show steps
-
Read through the syllabus and skim the assigned Agile readings.
-
Review the Agile Manifesto and its principles.
-
Create a mind map or diagram outlining the key concepts of Agile development.
-
Share your understanding with other students in a discussion forum.
Build a Personal Code Snippet Library
Show steps
Kickstart your coding journey by creating a repository of code snippets that align with the concepts and techniques covered in the course, fostering a strong foundation.
Browse courses on
Software Engineering
Show steps
-
Create a new repository or notebook for your code snippets.
-
Identify common coding patterns and algorithms relevant to the course.
-
Write clear and concise code snippets demonstrating these patterns.
-
Document your code with comments and explanations.
-
Test your code snippets and troubleshoot any errors.
Participate in Code Review Sessions
Show steps
Sharpen your coding skills and foster a collaborative learning environment by engaging in regular code review sessions with peers, providing valuable feedback and improving code quality.
Browse courses on
Coding
Show steps
-
Form a study group or connect with other students online.
-
Establish guidelines for code review, including feedback criteria and communication protocols.
-
Take turns submitting code for review and providing constructive feedback.
-
Discuss alternative solutions and best practices.
-
Reflect on the feedback received and incorporate it into your own code.
Three other activities
Expand to see all activities and additional details
Show all six activities
Develop an AI Resource Collection
Show steps
Create a comprehensive collection of valuable resources related to AI, including articles, tutorials, videos, and tools, to enhance your understanding and stay updated with industry advancements.
Browse courses on
Artificial Intelligence
Show steps
-
Identify and gather high-quality resources relevant to the course material.
-
Organize and categorize the resources into a logical structure.
-
Provide annotations or summaries for each resource to highlight its key takeaways.
-
Share your resource collection with other students or make it publicly available.
Join AI Hackathons or Competitions
Show steps
Put your skills to the test and gain practical experience by participating in AI hackathons or competitions, pushing the boundaries of your knowledge and problem-solving abilities.
Browse courses on
Generative AI
Show steps
-
Research upcoming AI hackathons or competitions relevant to the course topics.
-
Form a team or work individually.
-
Develop an innovative AI solution that addresses the competition's challenge.
-
Present your solution to a panel of judges.
-
Receive feedback and learn from other participants.
Contribute to Generative AI Open-Source Projects
Show steps
Gain hands-on experience with generative AI by contributing to open-source projects, collaborating with a global community of developers, and pushing the boundaries of AI innovation.
Browse courses on
Generative AI
Show steps
-
Identify open-source projects related to generative AI that align with your interests.
-
Review the project's documentation and codebase.
-
Identify an area where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
-
Fork the project, make your changes, and submit a pull request.
-
Collaborate with the project maintainers to ensure your contributions meet the project's standards.
Review Agile Concepts
Show steps
Refresher the core concepts of Agile methodologies, such as Scrum and Kanban, to better understand their application in the course.
Browse courses on
Agile
Show steps
Show steps
Show steps
- Read through the syllabus and skim the assigned Agile readings.
- Review the Agile Manifesto and its principles.
- Create a mind map or diagram outlining the key concepts of Agile development.
- Share your understanding with other students in a discussion forum.
Build a Personal Code Snippet Library
Show steps
Kickstart your coding journey by creating a repository of code snippets that align with the concepts and techniques covered in the course, fostering a strong foundation.
Browse courses on
Software Engineering
Show steps
Show steps
Show steps
- Create a new repository or notebook for your code snippets.
- Identify common coding patterns and algorithms relevant to the course.
- Write clear and concise code snippets demonstrating these patterns.
- Document your code with comments and explanations.
- Test your code snippets and troubleshoot any errors.
Participate in Code Review Sessions
Show steps
Sharpen your coding skills and foster a collaborative learning environment by engaging in regular code review sessions with peers, providing valuable feedback and improving code quality.
Browse courses on
Coding
Show steps
Show steps
Show steps
- Form a study group or connect with other students online.
- Establish guidelines for code review, including feedback criteria and communication protocols.
- Take turns submitting code for review and providing constructive feedback.
- Discuss alternative solutions and best practices.
- Reflect on the feedback received and incorporate it into your own code.
Three other activities
Expand to see all activities and additional details
Show all six activities
Develop an AI Resource Collection
Show steps
Create a comprehensive collection of valuable resources related to AI, including articles, tutorials, videos, and tools, to enhance your understanding and stay updated with industry advancements.
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Identify and gather high-quality resources relevant to the course material.
- Organize and categorize the resources into a logical structure.
- Provide annotations or summaries for each resource to highlight its key takeaways.
- Share your resource collection with other students or make it publicly available.
Join AI Hackathons or Competitions
Show steps
Put your skills to the test and gain practical experience by participating in AI hackathons or competitions, pushing the boundaries of your knowledge and problem-solving abilities.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Research upcoming AI hackathons or competitions relevant to the course topics.
- Form a team or work individually.
- Develop an innovative AI solution that addresses the competition's challenge.
- Present your solution to a panel of judges.
- Receive feedback and learn from other participants.
Contribute to Generative AI Open-Source Projects
Show steps
Gain hands-on experience with generative AI by contributing to open-source projects, collaborating with a global community of developers, and pushing the boundaries of AI innovation.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify open-source projects related to generative AI that align with your interests.
- Review the project's documentation and codebase.
- Identify an area where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
- Fork the project, make your changes, and submit a pull request.
- Collaborate with the project maintainers to ensure your contributions meet the project's standards.
Career center
Learners who complete Agile with AI will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/f6fnm6/agile
Reading list
We haven't picked any books for this reading list yet.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/f6fnm6/agile
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Effort
3 to 6 hours per week for 4 weeks
Level
Introductory
Via
edX
Institution
Pragmatic AI Labs
Instructor
Noah Gift
Session
May 20, 2024
- May 20, 2025
Language
English
Transcript
English
Good to know
Develops skills and knowledge useful for software development that employers seek today
Taught by recognized instructors in the AI field
Builds on existing foundation for intermediate learners
May require students to come in with extensive background knowledge
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