AWS Academy Educator Building the Future of AI-Machine Learning Higher Education & Practices with AWS for Workforce Development

This is a < 1% Sampler of the Course Content of 100-400 slides 2x every-week for each of 14-weeks for each of the two courses.

Over the Fall Semester of 2023, as AWS Academy Educator, we designed, built and delivered our latest College of Engineering Graduate and Undergraduate Computer Science courses on "post-Generative AI" Artificial Intelligence (AI) and Machine Learning (ML) built and delivered in alignment with contemporaneously released AWS Practices and Services. As Lumen Circles Fellow "post-Generative AI" Faculty Mentor at the largest comprehensive university system in the United States, we advanced beyond Stanford University's globally popular Artificial Intelligence (AI) and Machine Learning (ML) curriculum Machine Learning Specialization focus built on the legacy of the "neural networks" to the 'post Generative AI' Future of AI and ML. In doing so, we continued our progress building the Future of University and Higher Education and Workforce Development Practices in AI-Machine Learning, Information Systems and Computer Science to align with the most critical needs of today's and future 'post Generative AI' era workforce practices.

We designed, built, taught, and delivered Graduate and Undergraduate College of Engineering-Computer Science courses on the Future of Artificial Intelligence (AI) and Machine Learning (ML) with particular emphasis on our Global Risk Management Network, LLC practices leading AI-ML as well as Risk Management R&D and practices, networks, ventures, and technologies for last 30-years.

• First, we advanced beyond the AI-ML Stanford Computer Science & Engineering Machine Learning and Deep Learning Specializations curricular focus on the legacy of 'Neural Networks' to address large-scale real-world failures of such systems as global experts with R&D ranked and recognized for impact among AI and Quant-Finance Nobel laureates on those themes.

• Second, we analyzed and built upon the latest cutting-edge Generative AI and Machine Learning practices being built and released contemporaneously by the world-leading AI-ML-Engineering technology companies such as Amazon-AWS to address Quantum Uncertainty, Dynamic Uncertainty and Adversarial Uncertainty Risk Management focus on which our practices have documented lead on the global Risk Management standards such as ISO31000 by over 25-years as published in recent research journal articles.

• Third, we continued our thrust on Computer Science & Systems Engineering advancement of ‘Data-Driven’ AI-ML to ‘Network-Centric’ Management of Dynamic Change, Quantum Uncertainty and Complexity as Self-Adaptive Complex Systems & Chaos Engineering pioneer recognized in the global press such as The New York Times and The Wall Street Journal.

AWS Academy Educator Building the Future of AI-Machine Learning Higher Education & Practices with AWS for Workforce Development

Enumerated below are AWS cloud-based resources, available as readily feasible and available solutions to key Students’ Success and Academic Excellence issues posed by our students, faculty, and external partners. These can be offered as: (a) modules integrated within our courses as I did over Fall building and delivering graduate and undergraduate Engineering-Computer Science AI-ML projects-focused courses with associated ‘skill certificates’ as tangible evidence of our mission of workforce development; (b) as standalone ‘skill certificate’ projects-focused courses, labs and practicums for our workforce development; and/or, (c) as separate real-world industrial-applied practitioner projects-focused hands-on workshops and labs for workforce development: as conducive to all of our offered courses across all of our colleges taught by all of our faculty, as well as independently by all of our faculty and students.

A representative small sample from the adoption, application, and advancement upon Amazon and AWS Services and Resources is provided below broadly categorized under four separate categories:

1. Amazon-AWS SkillBuilder Courses, Hands-On Labs, Workshops and Projects
2. AWS Machine Learning University Courses, Hands-On Labs, Workshops and Projects
3. Amazon-AWS Immersion Labs and Workshops on Real Practices and AWS Practitioner Projects
4. AWS Academy Courses, Hands-On Labs, Workshops and Projects

AWS-SAGEMAKER STUDIO LAB – d2l.ai – Notebooks Guide: How to Run d2l.ai Notebooks in Your AWS-SAGEMAKER STUDIO LAB A/c:

Amazon-AWS SkillBuilder Courses, Hands-On Labs, Workshops and Projects: I have used these integrated into the AI-Machine Learning courses built and delivered over recent Fall from more than 600 free hands-on, latest cloud, digital and tech skills-focused courses for workforce development delivered online with digital training by AWS experts. Many of them come with respective skilled competencies certificates asked for by our students, faculty, and external partners. The portfolio of hands-on skills-building applied and experiential project-focused AWS courses can help our students and faculty learn cloud computing based skills for workforce development. Built on related AI-ML, analytics, data science and other hands-on labs-projects skills, these can be put into practice by applying related knowledge for industry-leading certifications as industry credentials demonstrating workforce development. In addition, we can choose from more cloud infrastructure-intensive projects-based labs-workshops at a fraction of the cost compared to on-prem infrastructures with minimal fees for all-you-can-learn individual subscriptions.

AWS Machine Learning University Courses, Hands-On Labs, Workshops and Projects: I also used the AWS Machine Learning University (MLU) Developer courses for building and delivering the Computer Science graduate and undergraduate AI-ML courses over Fall. AWS uses these to train their own developers on the same AWS cloud platforms. Many of them come with respective skilled competencies certificates asked for by our students, faculty, and external partners. I had many of our AI-ML undergraduate and graduate students apply and use these on freely available AI-Machine Learning cloud infrastructure platform Amazon SageMaker StudioLab. SageMaker is the AI-ML ‘workhorse’ for all of AWS AI-Machine Learning as well as all of integrated Data Science and Analytics Could Computing technologies providing the world-class cloud computing scale and turnkey resources for the most heavy-duty industrial and applied projects.

Amazon-AWS Immersion Labs and Workshops on Real Practices and AWS Practitioner Projects: I had integrated these real-world hands-on real practitioner project-based scheduled experiential and applied learning workshops on the latest developments in AI-ML including Generative AI, Large Language Models (LLMs), AIOps, MLOps besides others in our recent AI-ML courses as well. These are scheduled-event based free hands-on workshops for engineers and developers including hard-core engineering skills for building world-leading technologies and technology enabled ventures with offerings also for executives, sales, cloud finance and economics. As an AWS Accredited-Certified Partner, prior to building and teaching AI-ML courses as AWS Academy Educator for the current program, I had achieved AWS Certifications in AI-Machine Learning, Security, Cloud Computing, Cloud Practitioner skills having availed of over 2,000 hours of above AWS Partner training while collaborating with trainers in day-long training sessions as AI-ML expert. These are complemented by substantive industrial-applied large-scale computing and data analytics hands-on labs and workshops, many of them with respective skilled competencies certificates asked for by our students, faculty, and external partners.

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AWS Academy Courses, Hands-On Labs, Workshops and Projects: As shared above, I had the current higher education institution activated in Fall to enable us to join our peers among both public and private universities. We are ready to launch our AWS Academy offerings to enable Success and Academic Excellence of our students by building skilled competencies for workforce development. AWS Academy provides higher education institutions with a free, ready-to-teach cloud computing curriculum that prepares students to pursue industry-recognized credentials for workforce development and in-demand skilled jobs such as expected by our external partners. Its curriculum will help our educators stay at the forefront of cloud, AI-ML and related technologies so that we can equip our students with the skills they need to get hired as demanded by our external partners. We also have the available marketing, branding, and promotional collateral for the specific purpose that can be used to promote the institution among the hundreds of world-leading institutions already executing their Digital Futures on these world-scale AWS Academy platforms. As soon as we are ready to deliver our available and continuously upgraded AWS Academy Courses on all key aspects of Cloud Computing, Data Science, AI-Machine Learning, Data Engineering, and other skills, we can also be listed among the other Active AWS Academy Member Institutions.