The Generosity of Giants: Free Generative AI Courses from Tech Titans

Originally published on Medium: The Generosity of Giants: Free Generative AI Courses from Tech Titans | by Sam Bobo | May, 2024 | Medium

Newly out of college and starting my career inside of IBM Watson, I thrived on continuous learning fueled by intellectual curiosity! IBM, a technology giant, held a wealth of knowledge from decades of experience in the industry spanning any sector I was passionate about. Immediately once I got access to the company intranet, I milled through the troves of courseware available at my fingertips. Quickly I delved into technical trainings about natural language processing, learning about n-grams and nuances in the English language that made modeling difficult and expanded onward thereafter. I embarked on a side-quest through IBM’s big data university and found myself studying data lakes, Hadoop processes, and noSQL structures. At the time, IBM’s themes were centered around CAMSS — Cloud, Analytics, Mobile, Social, Security — and every Friday, CEO Ginni Rometty hosted a webinar for “THINK Friday” where she would introduce a theme, invite guest speakers from those parts of the company, and share IBM’s unique perspective on the space. I was hungry for knowledge and I certainly consumed it!

IBM issued digital badges for achievements in training, from Design Thinking to low-code programming on NodeRED, all through the Aclaim program. I wrote about Open Badging and organizational adoption in a retro post: “Badge Tagging and Developing Distinction:”

Recently, many organizations such as IBM and Microsoft , are buying into Open Badging. Open Badging was developed by Mozilla in 2011 in an initiative to recognize learning regardless of the platform. Badges are metadata linked images containing competencies achieved by the recipient and set by standards to adhere to specific technical specifications.

Over time, organizations such as IBM, Microsoft, Google, and Amazon have taken to educating the masses with free courseware and digital badges; and that effort has yet to subside, rather, bolstered in the advent of Generative AI.

Google: Democratizing AI Education

Google, in collaboration with MIT RAISE, has launched a free course titled Generative AI for Educators. This two-hour, self-paced course is designed to help middle and high school teachers integrate generative AI tools into their instruction, thereby personalizing education and enhancing lessons. Google also offers AI Essentials, a course that teaches how to use generative AI tools to speed up daily tasks, make informed decisions, and develop new ideas. Some of the topics in the courseware include:

• Use generative AI tools to save time on everyday tasks like drafting emails and other correspondence.
• Personalize instruction for different learning styles and abilities.
• Enhance lessons and activities in creative ways.
• Use generative AI tools to speed up daily tasks.
• Make more informed decisions.
• Develop new ideas and content.

IBM: Empowering Learners

IBM Learning has published a new page on their learning portal, Generative AI With IBM, offering a set of free courses. They also offer a course on Coursera titled Generative AI for Executives and Business Leaders. These courses aim to build awareness at various levels about the capabilities of AI, thereby fostering an AI-savvy workforce. The courses focus on:

• Understanding what generative AI is and how to leverage it.
• Learning how to answer questions about generative AI.
• Understanding how to apply generative AI in the modern world.
• Understanding the history and impact of generative AI for business.
• Learning about the importance of data in relation to business AI.
• Knowing the importance of trust, transparency, and governance.
• Applying generative AI to key use cases like customer service and application modernization.

Microsoft: Bridging the AI Gap

Microsoft has launched a free course called Generative AI for Beginners, which now includes 18 lessons. They also offer a learning path titled Microsoft Azure AI Fundamentals: Generative AI. These courses are designed to help beginners understand the concepts of generative models, large language models (LLMs), and prompt engineering. Skills gained include:

• Understanding the history and impact of generative AI for business.
• Learning about the importance of data in relation to business AI.
• Knowing the importance of trust, transparency, and governance.
• Applying generative AI to key use cases like customer service and application modernization.
• Understanding the concepts of generative models.
• Learning about large language models (LLMs).
• Understanding prompt engineering.

Amazon: Pioneering AI Readiness

Amazon, under its ‘AI Ready’ commitment, aims to provide free AI skills training to 2 million people globally by 2025. They offer eight new, free AI and generative AI courses open to anyone and aligned to in-demand jobs. Amazon also provides a course on Udacity titled Generative AI Foundations on AWS. Amazon focuses on:

• Understanding the importance of generative AI and its potential risks and benefits.
• Identifying business value from generative AI use cases.
• Discussing the technical foundations and key terminology for generative AI.
• Identifying which prompt-techniques are best-suited for specific models.
• Identifying potential prompt misuses.
• Describing architecture patterns that can be implemented with Amazon Bedrock for building generative AI applications.
• Understanding the conceptual fundamentals of generative AI.
• Learning practical advice and hands-on guidance to pre-train, fine-tune, and deploy state-of-the-art foundation models on AWS and beyond.

When analyzed broadly, these courses offer boilerplate templates — tech the general populus about Generative AI and underlying componentry (LLMs, prompts, etc) in a rudimentary level, preach the importance of Responsible AI and transparency, provide common use cases, and speak to the value gained for customers and enterprises all whilst promoting their own solutions and use thereof (the latter for advanced, more engineering-focused courseware).

So why create courses in Generative AI or other technical topics?

1. Democratizing AI Education: By offering these courses for free, they are making high-quality education in this advanced field accessible to a wider audience. This helps in spreading knowledge and skills in AI across the globe, irrespective of the learners’ financial capabilities. While organizations such as MIT and UT Autin are pioneers in AI-focused degrees and other universities are quickly ramping up similar specializations, learners do not have access financially to obtain those degrees, and that financial divide is only growing. MOOCs
2. Fostering Innovation and Inspiration: When more people have access to this kind of education, it leads to more ideas, more innovation, and more advancements in the field of AI. This can lead to the development of new tools, applications, and solutions that can benefit these companies as well as the broader tech industry.
3. Creating a Talent Pool: These courses help in creating a pool of individuals skilled in AI. These individuals could potentially be future employees, contributing to the AI endeavors of these companies, participate in open source code bases, join hackathons, and online competitions and more. Furthermore, these individuals can spread to other organizations that use the target company’s platform or AI services and thus continue fostering the Generative AI ecosystem.
4. Brand Image and Leadership: Offering free courses also helps these companies in positioning themselves as thought leaders in the field of AI. It enhances their brand image and showcases their commitment to advancing AI technology. These brand images are like stocks, that fluctuate based on company reputation and performance, however, badge holders whom hold a badge from a company could warrant a higher skillset attribution regardless of the actual skills demonstrated. Furthermore, demonstrating leadership in a space, per my opening anecdote, can help skew people towards their platforms. Which brings me to…
5. Driving Adoption of Their Platforms: These courses often use the company’s own platforms and tools for teaching and hands-on exercises. This can lead to increased adoption and usage of their platforms. Once a learner has mastary and a project in a paricular platform, they are more likely to continue using said platform our of familiarity. Similar to the mobile phone market penetrating the enterprise and evolving into a “bring your own device” paradigm, leaners may bring they preferred platforms into the enterprise or their own lines of work which can quickly diffuse through the organization and driving further adoption and revenue.
6. Long-term Business Value: In the long run, advancements in AI can lead to the development of new products, services, or improvements in existing offerings. This can drive business growth and provide a competitive edge for these companies.

Many of these organizations, by partnering with Massive Open Online Courseware (MOOC) providers such as Coursera, EdX, Udacity perpetuate the aforementioned drivers but on a deeper level than simply a web page hosted training material as they provide access to lab environments to run code, typically include office hours, provide a badge and certificate that hold higher weight outside of the immediate issuing company, and can sometimes fulfill credits as part of a larger “degree” track.

Yes, courseware is inherently marketing, there is no doubt about that, however, I am an extreme proponent of educating the masses and sparking inspiration for the next generation of developers. Taking to online courseware for coding and technical projects is targeting a demographic eager to learn without a formal degree, as I explained earlier and through other self-coding platforms such as Dataquest and Codecademy. I encourage everyone to checkout the catalogs of these tech titans, learn more about Generative AI (as well as read my blog!) and share about which classes you’ve taken and thoughts about the subject matter!