The 5 Best Generative AI Courses

With so many resources available on the Internet, it’s easy to get confused, but you needn’t worry. These handpicked courses on generative AI can help you cut through the noise and select the best course for your needs.

This course is one of the best tutorials for beginners to get started with generative AI. The learning path covers fundamental concepts including large language models (LLM), responsible AI, and prompt engineering.

The learning path is divided into the following five courses.

1. Introduction to Generative AI: This course provides a clear explanation of generative AI, its applications, and how it differs from traditional machine learning techniques.
2. Introduction to Large Language Models: This course introduces LLMs, their use cases, and how prompt tuning can boost LLM performance.
3. Introduction to Responsible AI: This course explores responsible AI and its importance. It also covers Google’s 7 AI principles and how it implements them in its products.
4. Prompt Design in Vertex AI: This course includes four hands-on labs that can help you gain a foundational understanding of generative AI implementation, including real-world marketing scenarios. You’ll use the Vertex AI Studio and learn the art of prompt engineering with Gemini.
5. Responsible AI (Applying AI Principles with Google Cloud): Implementing AI principles can be challenging. This course demonstrates how to do so, using Google’s experience as an example.

These courses provide materials in the form of videos, complementary reading lists, hands-on labs, and quizzes to check your understanding of the concepts. Upon completing each course, you’ll also earn a badge of completion.

This 30-hour freeCodeCamp course on generative AI is one of the most comprehensive courses for developers. You can access it on freeCodeCamp’s YouTube channel or the iNeuron platform. If you access the course via iNeuron, you’ll get more features, including dashboard access, course resources, dedicated community support, quizzes, and assessments in all modules.

You’ll first learn the theoretical concepts related to genAI. Then, you’ll gain hands-on knowledge of several tools, including Gemini Pro, OpenAI, Llama, Langchain, Pinecone, and Vector Databases. You’ll build many real-world applications while doing this course. Quizzes, community support, and assessments can help you further solidify the learned concepts.

Although you can cover this course at your own pace, the instructors have structured it over 13 days. According to freeCodeCamp, here’s what you can expect:

• Days 1-2: The course kicks off with an introduction to the Generative AI Community and OpenAI, laying the foundational knowledge about the OpenAI API, a critical tool in AI development.
• Days 3-5: Learners will dive into LangChain and its integration with the Hugging Face API, emphasizing memory in LangChain to build more cohesive AI models.
• Days 6-7: The course ramps up with a hands-on project utilizing OpenAI & LangChain, guiding students through the development and deployment phases of a generative AI project.
• Days 8-10: A deep dive into Vector Databases for AI and mastering these with tools like Pinecone and ChromaDB, essential for handling complex AI data efficiently.
• Day 11: Introduction to Meta Llama 2, exploring the latest advancements in generative models.
• Days 12-13: An intensive two-part series on building an end-to-end medical chatbot project, demonstrating real-world applications of generative AI.
• Special Sessions: Additional insights on everything you need to know about Gemini Pro LLM Models and an end-to-end generative AI project using Google Gemini Pro. The course culminates with a webinar on the generative AI revolution, forecasting the future of AI.

This short generative AI course is taught by AI pioneer Andrew Ng. It covers how generative AI works, what it can and cannot do, how to use it effectively, and the opportunities and risks in genAI. You’ll also get some tips on prompt engineering. The best part of this course is that you don’t need any prior coding or AI knowledge to take it.

The instructor, Andrew Ng, has taught other courses on machine learning and AI, which are considered among the best courses on the topic. Quizzes, reading materials, and hands-on exercises complement the course modules.

According to DeepLearning.AI, by the end of this course, you’ll learn:

• What generative AI is.
• What it can and cannot do.
• How to use it in your own world/business.
• How to debunk misinformation about generative AI and use the technology at its best.
• Best practices for learning and exploring whether or not genAI would be useful.

This course by Microsoft is arguably the most in-depth open-source course available for those who want to enter the generative AI world. Structured as a series of “Learn” and “Build” lessons, it offers a comprehensive understanding of generative AI concepts and practical implementation using Python and TypeScript.

Each topic includes a short video introduction followed by a written lesson. You’ll have access to Python and TypeScript code samples that support Azure OpenAI and the OpenAI API.

This course also provides links to extra resources if you want to go beyond the core curriculum. You can join the official Discord server to meet and network with other learners.

This course by IBM on Coursera offers a comprehensive overview of generative AI’s foundational concepts, capabilities, models, tools, and applications. Through five short, self-paced courses, each requiring 3–5 hours to complete, you can understand how to use generative AI to enhance your career and life in general.

The specialization covers a wide array of topics, including powerful prompt engineering techniques to achieve desired outcomes, understanding foundational models like GPT, DALL-E, and IBM Granite, and introduction to the ethical implications and considerations surrounding generative AI.

If you’re already experienced with generative AI, you can enroll in one of IBM’s role-based specializations: