Learn AI: Best Artificial Intelligence Courses and Websites

Nvidia Deep Learning Institute

Nvidia, a global technology company known for its knowledge of AI, offers a variety of AI courses on its website. These courses range from beginner to advanced levels, covering various aspects of AI, such as deep learning, machine learning, and data science. The paths are designed with a hands-on approach, helping learners gain practical experience in AI.

Databricks Training: Generative AI Fundamentals

Databricks provides a specific course on Generative AI fundamentals. This course is ideal for those who want to delve deeper into the AI world and understand the underlying principles of AI technologies. The course offers both theoretical knowledge and practical applications, making it a complete learning package.

Google Cloud: Platform for AI Courses

Google Cloud is another excellent platform for learning AI. It offers a variety of AI courses, including AI engineering, data engineering, and machine learning engineering. The courses are comprehensive and designed to provide in-depth knowledge of AI. With Google's robust cloud infrastructure, learners get hands-on experience working with real-world AI scenarios.

AWS SkillBuilder

AWS SkillBuilder offers a wide range of AI courses that cover different learning needs. From machine learning to AI development, AWS has courses that cover all aspects of AI. With AWS's vast resources and top-notch instructors, learners can expect to gain a strong foundation in AI.

Harvard's PLL: Academic Approach to AI Courses

Harvard's Professional Learning offers academic-style AI courses. The courses are rigorous and research-oriented, offering an in-depth understanding of AI. Harvard's PLL is ideal for learners who prefer a scholarly approach to learning AI.

Our recommended ones

1. Google Path (Google Cloud Skill Boost):

• Introduction to Generative AI: Provides a foundational understanding of Gen AI, its applications, and how it compares to conventional machine learning approaches.
• Introduction to Responsible AI is an introductory-level microlearning course that explains responsible AI, why it's important, and how Google implements it in its products. It also introduces Google's 7 AI principles.
• Introduction to Large Language Models: This course also introduces Generative AI, covering its applications and key differences from traditional machine learning approaches.
• Digital Transformation with Google Cloud: An overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey.

2. Amazon Path (AWS Educate):

• Generative AI Foundations on AWS Technical Deep Dive Series: Introduces Generative AI, its applications, and need-to-know concepts, like foundation models.
• Generative AI Learning Plan for Decision Makers: This is a three-course series covering how to plan a Gen AI project and build an AI-ready organization.
• Foundations of Prompt Engineering: Introduces the basics of prompt engineering, the practice of designing inputs for generative AI tools, and advanced prompt techniques.

3. Additional:

• Amazon Q: Equips participants with skills to leverage Amazon's AI development tool for code generation.
• Power and Prediction: The Disruptive Economics of Artificial Intelligence, video available here: Stanford Digital Economy Lab

4. Recommended readings:

• Google “The Prompt: Let’s talk about recent AI missteps”
• Are you fluent in prompts and embeddings? Here’s a generative AI primer for busy executives
• The Future of Industries: How generative AI is altering the enterprise security landscape

Conclusion

Given the complexity of topics framed within artificial intelligence, it is difficult for people who want to learn from 0, managers who want to implement AI projects in their companies, and companies that want to create competitive advantage with AI to understand the training path in artificial intelligence that their teams and themselves should have.

Some of the courses and pages we gave above repeat some topics. It is very common to see generative AI topics repeated in several classes. However, we believe this is not a problem since it is good to reinforce some concepts in this topic.