Agile Practices Using AI

Focused View

Noah Gift

1:35:59

22 View

01 - Course introduction.mp4

01:23

02 - Waterfall model.mp4

02:25

03 - Playground plant.mp4

01:58

04 - Five Whys technique.mp4

04:06

05 - Productivity techniques.mp4

04:32

06 - Pragmatic Agile.mp4

02:42

07 - Effective technical discussions Introduction.mp4

01:39

08 - Trello.mp4

04:23

09 - Planning with spreadsheets.mp4

04:52

10 - Anti-patterns.mp4

04:52

11 - Effective technical discussions Technical demo.mp4

10:41

12 - Demo videos.mp4

01:33

13 - Effective critical thinking.mp4

05:02

14 - Effective triple threat.mp4

02:42

15 - Effective technical teamwork Introduction.mp4

00:29

16 - Effective technical teamwork.mp4

05:56

17 - Introduction effective technical project management.mp4

01:56

18 - Developing effective technical project management.mp4

05:23

19 - AIOps.mp4

01:53

20 - Diagram Prompt engineering.mp4

03:47

21 - Summarizing text with Claude.mp4

05:28

22 - AI pair programming Paradigm shift.mp4

03:05

23 - AWS CodeWhisperer for Rust.mp4

07:47

24 - Serverless Bedrock diagram.mp4

02:28

25 - Bedrock knowledge agent with RAG.mp4

02:06

26 - Building blocks for generative AI with WhisperCPP (RAW).mp4

02:51

Description

In this course, MLOps expert Noah Gift explores the integration of Agile practices with Artificial Intelligence (AI) to streamline software development processes and improve productivity. Learn about the Five Whys technique, pragmatic Agile, and incorporating Trello into your workflows. Explore anti-patterns, as well as effective critical thinking, triple threat, and technical teamwork. Dive into AIOps, prompt engineering, pair programming, and much more. By combining the principles of Agile and the capabilities of AI, you can unlock new levels of efficiency and innovation.

This course was created by Noah Gift. We are pleased to host this training in our library.

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Artificial Intelligence

Agile

Noah Gift

Instructor's Courses

Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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