Top 5 Generative AI Courses

With so many resources on the internet, it can be easy to get confused, but don't worry. These carefully selected courses on Generative AI will help you cut through the noise and choose the course that best suits your needs.

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

The learning path is divided into five courses:

1. Generative AI overview: This course provides a clear explanation of generative AI, its applications, and how it differs from traditional machine learning techniques.
2. Overview of large-scale language models: This course introduces LLM, its use cases, and how quick tuning can improve its performance.
3. Overview of responsible AI: This course explores responsible AI and its importance. We also discuss Google's seven AI principles and how to implement them in your products.
4. Rapid design with Vertex AI: This course includes four hands-on labs that help you understand the basics of generative AI implementation, including real-world marketing scenarios. Learn the art of prompted engineering with Gemini using Vertex AI Studio.
5. Responsible AI (Google Cloud's application of AI principles): Implementing AI principles can be difficult. This course shows you how to do that, using Google's experience as an example.

These courses provide material in the form of videos, supplemental reading lists, hands-on labs, and quizzes to check your understanding of concepts. Completing each course also earns you a completion badge.

This 30-hour freeCodeCamp course on Generative AI is one of the most comprehensive courses for developers. It can be accessed through freeCodeCamp's YouTube channel or the iNeuron platform. Accessing your course via iNeuron gives you even more features, including dashboard access, course resources, dedicated community support, quizzes, and assessments for all modules.

First, learn the theoretical concepts related to genAI. You will then gain practical knowledge of several tools such as Gemini Pro, OpenAI, Llama, Langchain, Pinecone, and Vector databases. You will build many real-world applications while taking this course. Quizzes, community support, and assessments help you further consolidate the concepts you learn.

Although this course is self-paced, the instructor structured the course over 13 days. According to freeCodeCamp, you can expect:

• Days 1-2: This course begins with an introduction to the Generative AI community and OpenAI, and provides a foundational understanding of the OpenAI API, a key tool for AI development.
• Days 3-5: Learners will learn more about LangChain and its integration with the Hugging Face API, and focus on LangChain's memory to build more consistent AI models.
• Day 6-7: This course begins with a hands-on project utilizing OpenAI and LangChain, guiding students through the development and deployment phases of a generative AI project.
• Days 8-10: Dive deep into vector databases for AI and master them using tools like Pinecone and ChromaDB that are essential for efficiently processing complex AI data.
• Day 11: Introducing Meta Llama 2. Explore the latest advances in generative models.
• Day 12-13: A two-part intensive series on building an end-to-end medical chatbot project, demonstrating real-world applications of generative AI.
• special session: Additional insight into Gemini Pro LLM models and everything you need to know about end-to-end generative AI projects using Google Gemini Pro. The course culminates in a webinar on the generative AI revolution that predicts the future of AI.

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

Instructor Andrew Ng has taught other courses on machine learning and AI, which are considered some of the best on the subject. Quizzes, reading material, and practical exercises complement the course modules.

According to DeepLearning.AI, by the end of this course you will have learned:

• What is generative AI?
• What you can do and what you can't do.
• How can I use it in my world/business?
• Debunking the misinformation about generative AI and how to get the most out of the technology.
• Best practices for learning and exploring whether genAI can help you.

This course by Microsoft is probably the most in-depth open source course available for anyone looking to enter the world of generative AI. Organized as a series of “Learn” and “Build” lessons, it provides 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. Access Python and TypeScript code samples that support Azure OpenAI and OpenAI API.

This course also includes links to additional resources if you wish to study beyond the core curriculum. Join our official Discord server to meet and network with other learners.

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

This specialization covers a wide range of topics, including powerful prompt engineering techniques to achieve desired results, an understanding of fundamental models such as GPT, DALL-E, and IBM Granite, and an introduction to the ethical implications and considerations surrounding generative AI. It's covered.

If you already have experience with generative AI, you can enroll in one of IBM's role-based specializations.