Unlocking the Secrets of Google's FREE AI Course Offerings
Written on
Chapter 1: Introduction to Google's Generative AI Learning Path
Recently, Google unveiled a comprehensive learning path focused on Generative AI, featuring courses that delve into subjects such as the basics of Generative AI, Large Language Models, and Image Generation.
This initiative is particularly exciting because many of the courses come without prerequisites, making them accessible even for individuals without programming backgrounds. Below, you'll find all the essential details regarding these AI courses.
Section 1.1: Who Should Enroll in These Courses?
These courses cater to anyone eager to explore Generative AI technologies, Large Language Models, and the deployment of AI solutions. Out of the ten courses available, approximately five do necessitate prior knowledge in Python and Machine Learning. Don’t worry, as I will provide a deeper insight into each course shortly, including which ones are beginner-friendly.
Upon completing a course, participants will receive a badge as a recognition of their achievement.
Section 1.2: Course Content Overview
Google's Generative AI learning path offers a carefully selected array of content related to generative AI products and technologies.
Here’s a summary of the ten courses included in this learning path:
The following five courses do not require any prerequisites:
- Introduction to Generative AI: This course covers the fundamentals of Generative AI, its applications, and how it contrasts with traditional machine learning.
- Introduction to Large Language Models (LLMs): Learn about LLMs, their use cases, and techniques for prompt engineering.
- Introduction to Responsible AI: This course discusses the principles of responsible AI, its significance, and how Google incorporates these practices into its offerings.
- Introduction to Generative AI Studio: Understand the functionalities of the Generative AI Studio and how to utilize its features effectively.
Conversely, the remaining courses necessitate familiarity with Python programming, Machine Learning, and Deep Learning:
- Introduction to Image Generation: Explore the theory of diffusion models and how to implement them on Vertex AI.
- Encoder-Decoder Architecture: Learn about the key components and training of encoder-decoder models.
- Attention Mechanism: Discover how attention improves performance in various ML tasks, including translation and summarization.
- Transformer Models and BERT: Understand the transformer architecture and its application in building BERT models.
- Creating Image Captioning Models: Gain insights into developing an image captioning model through deep learning techniques.
Chapter 2: How to Access the Courses
This learning path is accessible through the Google Cloud platform. Click here to enroll in any of the courses offered in the Generative AI Learning Path. Keep in mind that this is just one of many free courses available on Google Cloud, with additional offerings like the Data Engineer and Data Analyst Learning Paths. Explore the complete catalog on Google Cloud Skill Boost.
Video Description: Google has recently introduced a free course on AI, providing valuable insights into the world of generative AI. This course is a fantastic opportunity for anyone interested in exploring AI technologies.
Additionally, there are a plethora of free AI courses available online. One of my personal favorites is the ChatGPT Prompt Engineering course created by OpenAI and Andrew Ng. For further details about this course, refer to my previous article.
Furthermore, here are four free prompt engineering courses suited for individuals with no coding experience.
Video Description: Discover how to potentially earn $660 a day by obtaining free Google Generative AI certificates. This video outlines the steps and benefits of enrolling in these courses.
That’s all for now! I hope these courses enhance your understanding of artificial intelligence.