Building and managing AI models is now becoming the key competency for application developers and software engineers. Collaborating with data scientists and ML engineers, the application and DevOps teams are gaining skills and becoming active participants for the AI lifecycle management. Powered by AutoAI from Watson AI technology, you can build models with Watson Studio, run models with Watson Machine Learning and measure models with Watson OpenScale.
- Watson Studio Documentation
- Watson Machine Learning
- Weekly IBM Data and AI Innovation Exchange - Every Thursday from May 14 to June 25: AMA (Ask Me Anything) with data science and AI experts
- OpenScale on IBM Demos
- Scenario - Mortgage default
- AutoAI for Data Scientists: From beginner to expert
- AutoAI overview
- Learn about ModelOps
- Learn about Decision Optimization
- Covid Notebook
- Machine Learning with Python
- Deep Learning
- https://www.coursera.org/professional-certificates/ai-engineer
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The video is paused for me, what do I do?
You have to hit the play button in some browsers as the video does not auto play.
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Is this webinar being recorded?
Yes, the webinar is being recorded, you can view the replay on the same link once the event ends.
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Where are the slides?
See the links above for workshops and resources for each of the sessions.
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Do you have study materials or courses available?
See additional links above for additional reading materials
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Do you have a certification ?
There is no certification provided at this point, but IBM offers a number of courses and certifications on Coursera and Cognitive.ai. See the section above for a listing.
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How do I access the replays of the individual sessions?
You can access the individual sessions by using the drop down in the top left corner as shown in the screenshot below.
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Who can attend these sessions?
Developers, data scientists and architects. Anyone interested in building and deploying AI models.
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What will I learn?
In this 3-part Watson AI technology series, you will learn: - AI app use case patterns using prediction and optimization - Basics of machine learning and decision optimization - Monitoring AI models for fairness, accuracy, and drift - Automating AI lifecycle management
April 10 - Nerav Doshi
May 1 - Eric Martens
May 15 - Jacques Roy
Upkar Lidder, IBM Data Science and AI Developer Advocate, https://www.linkedin.com/in/lidderupk/