The excitement stirred by the success of generative AI services such as ChatGPT, Midjourney, Stable Diffusion and Bard has fueled an endless variety of training courses at all levels of expertise. Many are aimed at helping developers create AI applications. Others focus more on business users looking to apply the new technology across the enterprise.
Although it's helpful to learn what the new technology can do, it's equally important to learn about AI's challenges and limitations, such as bias, AI hallucinations, data leakage and new security vulnerabilities. "The key is helping business users understand what AI can and cannot do so they can avoid being oversold or starting projects with a low likelihood of success," said Josh Koenig, co-founder and chief strategy officer at Pantheon.
As new tools emerge, Koenig expects to see training expand from learning how to use prompts to how to train models. "That's where truly innovative and differentiated applications are going to come from," he said.
Framing training for business users
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"The best training resources drive adoption and understanding," said Dwarak Sri, global head of AI at BlueCloud, an AI and cloud consultancy. One option is to look for training resources that provide concrete examples, including practical situations where AI has made a real impact in solving business problems. These resources might also showcase success stories directly related to different industries, as real-world scenarios can help drive home the benefits of adopting AI.
It's also helpful to investigate resources with a problem-solving angle. These might present AI as a solution to specific challenges that business users often face. Sri finds that visuals are critical, and the best programs use diagrams and interactive demos to help business professionals see how AI operates and its value.
Enterprises might also want to provide training and support to employees through workshops that help them get the hang of using AI tools and platforms. "Interactive lectures presented by industry experts can lead to insightful group discussions and learning materials that users can explore at their own pace," Sri said.
Taking a balanced approach to generative AI learning
AArete, a global management and technology consulting firm, uses the acronym FOCUS to balance all aspects of learning about generative AI, according to Priya Iragavarapu, vice president of data and analytics delivery. The FOCUS acronym stands for the following:
- Fundamentals. Users need to understand basic AI concepts, terminologies and types, and where those technologies can be used.
- Operational integration. Business users must learn how to incorporate AI into existing workflows, processes and decision-making structures within the business.
- Compliance and ethics. Business users don't need to be AI experts, but they do need enough information on data privacy, ethical considerations and responsible AI use to operate within best practice guidelines.
- User-centric applications. Business users must consider how AI can improve customer experience, enhance employee productivity and solve specific business challenges. They need to have enough context to pursue AI opportunities while keeping users in mind.
- Sustained development. AI training is a continuous need. Look for bite-sized training snippets to learn the same concept in multiple ways to boost understanding.
Various methods of generative AI training
It's important to consider the various modalities of generative AI training resources. Sri said the most common training methods include in-person workshops and seminars, which are highly interactive and provide immediate feedback and networking opportunities. Online courses let users choose when and where to study, but they require self-discipline and might lack personal interaction.
In addition, video tutorials and webinars let users pause, rewind and review material as often as needed. "However, video tutorials are only sometimes up to date and lack real-time feedback," Sri said. He recommends a blended learning approach that combines various techniques to achieve a well-rounded experience, such as an online course paired with an in-person workshop.
Here are 10 of the top generative AI courses and training resources recommended by AI leaders.
1. Class Central
Class Central is a learning content aggregation directory with courses from numerous universities and institutions, as well as more than 80 providers. It currently includes more than 2,700 free courses on generative AI and another 1,900 paid courses that come with a certificate upon completion. It's a good place to start when seeking guidance on tools such as ChatGPT, Midjourney and Stable Diffusion. There are also longer programs that let users develop a broader understanding of generative AI capabilities, opportunities, use cases and responsible use within the enterprise.
The Coursera platform provides hundreds of generative AI training courses for free or a small fee. Some courses even provide a shareable certificate that can be added to a LinkedIn profile. Some popular courses include Generative AI with Large Language Models, Prompt Engineering for ChatGPT, ChatGPT Advanced Data Analysis and GenAI for Everyone.
The EdX platform is Iragavarapu's personal favorite and has plenty of free resources. It provides numerous generative AI options at every level of technical familiarity. Lessons cover generative AI for business leaders, prompt engineering, ethics and industry use cases. Many classes have a free audit option, but they can provide professional certification for a nominal fee.
4. Google Cloud Introduction to Generative AI Learning Path
This is a free introductory course about generative AI and how it is used. Modules cover generative AI fundamentals, LLMs and responsible AI. A subscription option lets users take courses with live training and also work in conjunction with a lab to put new concepts into practice.
5. Generative AI for Business Leaders
This short course by LinkedIn Chief Product Officer Tomer Cohen covers the basics of getting started with generative AI, business implications, pitfalls and future trends. There's a free one-month trial; a LinkedIn Learning services subscription starts at $19.99 per month annually for users who want a certificate of completion and ongoing access to other resources on the platform.
6. Learn Prompting
This free and open source curriculum explains how to use ChatGPT and other tools to accomplish your goals. It has more than 60 content modules to support skill levels ranging from business user to developer, analyst and data scientist. Modules cover prompt engineering basics, applied prompting, reliability, image prompting, prompt hacking, tooling and prompt tuning. Learn Prompting also sponsors a prompt hacking competition to enhance AI safety and education.
7. Towards AI
This AI community and content platform -- with more than 2,000 contributing writers and 270,000 followers -- focuses on making AI accessible to everyone. Sri considers it a useful resource to find news and opinions, discover tutorials, and explore the latest newsletters and articles on trending topics. Access to the service is free, although some content exists behind a Medium paywall.
Udemy is another great starting point to learn about generative AI. It has more than 80 courses that offer learning tutorials for users with no programming experience. Some of the most popular courses cover ChatGPT basics, automating content generation, AI in marketing, time management, code completion and cybersecurity.
9. Visually AI
This site, curated by Heather Cooper, has a strong focus on AI image-generation tools and techniques. Sri said this is a great resource for interesting tips on how to find the right tool by product category, type of tool or the most popular app. There are also suggestions on how to improve prompts and recommendations for plugins. Much of the content is free, although several premium courses are available.
Iragavarapu said YouTube is another great resource for learning generative AI basics and keeping up with trends. There are many short-form videos for a quick summary of the field, such as TechTarget's "Ultimate Guide to Generative AI for Businesses." There are also thousands of deeper dives into select topics, including the practical aspects of using generative AI for data science, mastering new tools and discovering new business use cases.
The future of training resources
The technologies and uses of generative AI are rapidly evolving. Sri expects that different training modes, interactivity and content will evolve as the technology becomes more accessible. Tutorials will become more interactive and provide step-by-step guidance and feedback in real time. Businesses will increasingly create virtual environments, known as sandboxes, where users can experiment with generative AI models without the risk of affecting real-world systems. This will provide a safe space where users can refine their skills and test various scenarios.
Sri believes that training content will incorporate more real-world use cases relevant to various industries as generative AI evolves. Ethics and bias education will also be more significant. Businesses will need to focus on educating users about responsible AI usage, data privacy and ways to mitigate unintended consequences. Generative AI will also lead to more dynamic content generation of personalized examples, exercises and scenarios that align with users' learning objectives and skill levels.