The excitement generated by the success of generative AI services such as ChatGPT, Midjourney, Stable Diffusion or Bard has fueled an infinite variety of training at all levels of expertise. Many aim to help developers create AI applications. Others focus more on business users looking to apply new technology across the enterprise.
While it is helpful to learn what new technology can do, it is equally important to discover the challenges of AI and limitations, such as prejudices, AI hallucinationsdata leak and new security failures. “The key is to help business users understand what AI can and cannot do, to avoid being oversold or starting projects with low chances 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 training models. “That’s where truly innovative and differentiated applications will come from,” he said.
Training framework for business users
“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 real-world examples, including practical situations where AI has had a real impact on solving business problems. These resources can also feature success stories directly related to different sectors, as real-life scenarios can help drive home understanding. benefits of adopting AI.
It’s also helpful to look at resources from a problem-solving perspective. These could present AI as a solution to the specific challenges that business users often face. Sri believes that visuals are essential and that the best programs use diagrams and interactive demos to help professionals see how AI works and its value.
Companies may also want to provide training and support to employees through workshops that help them become familiar with using AI tools and platforms. “Interactive lectures presented by industry experts can lead to enriching group discussions and learning materials that users can explore at their own pace,” Sri said.
Taking a Balanced Approach to AI Generative Learning
AArete, a global management and technology consulting firm, uses the acronym FOCUS to balance all aspects of generative AI learning, according to Priya Iragavarapu, vice president of data delivery and analytics. The acronym FOCUS means the following:
- Fundamentals. Users must understand the basic concepts of AI, terminologies and types, and where these technologies can be used.
- Operational integration. Business users must learn how to integrate AI into existing workflows, processes, and decision-making structures within the company.
- Compliance and ethics. Business users don’t need to be AI experts, but they do need enough information about data privacy, ethical considerations and responsible use of AI to operate within best practice guidelines.
- User-centric applications. Professional users should consider how AI can improve customer experience, improve employee productivity and solve specific business challenges. They need to have enough context to exploit AI opportunities while keeping users in mind.
- Sustained development. AI training is an ongoing need. Look for bite-sized training snippets to learn the same concept in multiple ways to improve understanding.
Various generative AI training methods
It is important to consider the different 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 allow users to choose when and where to study, but they require self-discipline and may lack personal interaction.
Additionally, video tutorials and webinars allow users to 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 get a well-rounded experience, such as an online course paired with an in-person workshop.
Here are 10 of the best generative AI courses and training resources recommended by AI leaders.
1. Central class
Class Central is a learning content aggregation directory with course numerous universities and institutions, as well as more than 80 service providers. It currently includes over 2,700 free courses on generative AI and another 1,900 paid courses that come with a certificate at the end. This is a good place to start when looking for advice on tools like ChatGPT, Midjourney, and Stable Diffusion. There are also longer programs that allow users to develop a broader understanding of the capabilities, opportunities, use cases and responsible use of generative AI within the enterprise.
La Coursera platform offers hundreds of generative AI training courses for free or for 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, Rapid Engineering for ChatGPT, Advanced Data Analytics ChatGPT, and GenAI for Everyone.
The EdX platform is Iragavarapu’s favorite and offers many free resources. It offers many generative AI options at all levels of technical familiarity. Course cover generative AI for business leaders, rapid engineering, ethics, and industry use cases. Many classes offer a free audit option, but they can provide professional certification for a small fee.
4. Google Cloud Introduction to Generative AI Learning Path
This is a free introductory course to generative AI and how to use it. Modules cover the fundamentals of generative AI, LLMs and responsible AI. A subscription option allows users to take classes with live training and also work collaboratively with a lab to practice new concepts.
5. Generative AI for business leaders
This of short time by Tomer Cohen, LinkedIn Chief Product Officer, covers the basics of getting started with generative AI, business implications, pitfalls, and future trends. There is a one-month free trial; A subscription to LinkedIn Learning services starts at $19.99 per month per year for users who want a certificate of completion and ongoing access to other platform resources.
6. Learn to invite
This free and open source software study programme explains how to use ChatGPT and other tools to achieve your goals. It has over 60 content modules to support skill levels ranging from business user to developer, analyst, and data scientist. Modules cover the basics of rapid engineering, applied prompts, reliability, image prompts, rapid hacking, tools, and rapid tuning. Learn Prompting also sponsors a speed hacking competition to improve AI safety and education.
7. Towards AI
This AI community and content platform — with more than 2,000 contributing authors and 270,000 subscribers — strives to make AI accessible to everyone. Sri considers it a useful resource for finding news and opinions, discovering tutorials and exploring 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 place to start learning more about generative AI. It has more than 80 courses that offer learning tutorials for users without programming experience. Some of the most popular courses cover ChatGPT basics, content generation automation, AI in marketing, time management, code completion, and cybersecurity.
9. Visually AI
This site, curated by Heather Cooper, focuses heavily on AI image generation tools and techniques. Sri said it’s a great resource for great tips on how to find the right tool by product category, tool type, or most popular application. There are also suggestions on how to improve the 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 the basics of generative AI and following trends. There is a lot of short videos for a quick summary of the field, such as TechTarget’s “Ultimate Guide to Generative AI for Business.” There are also thousands of deep dives on select topics, including the practicalities of using generative AI for data science, mastering new tools, and discovering new business use cases.
The future of training resources
The technologies and the uses of generative AI are evolving rapidly. Sri expects different training modes, interactivity and content to evolve as technology becomes more accessible. Tutorials will become more interactive and provide step-by-step guidance and feedback in real time. Companies will increasingly create virtual environments, called sandboxes, in which users can experiment with generative AI models without risk of affecting real-world systems. This will provide a safe space where users can hone their skills and test various scenarios.
Sri believes that the training content will incorporate more real-world use cases relevant to various industries as generative AI evolves. Education on ethics and bias will also be more important. Businesses will need to focus on raise awareness among users about responsible use of AI, 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 match users’ learning goals and skill levels.