We've put together resources in this blog to teach you about generative AI, how to use it, and how it can affect your company.
Generative AI
Generative AI is a branch of computer science that is rapidly developing and uses machine learning to produce original text, graphics, and music. To assist you in gaining an understanding of generative AI, Google Cloud provides an extensive learning path that covers subjects like:
- Machine learning foundations: This course covers the fundamentals of supervised learning, unsupervised learning, and reinforcement learning.
- Generative models: This course covers the various varieties of generative models, including diffusion models, generative adversarial networks, and variational autoencoders.
- TensorFlow: In this course, you will learn how to create and train generative models using TensorFlow, a well-known open-source machine-learning library.
- Google Cloud Platform: This course demonstrates how to train and use generative models using services provided by Google Cloud Platform, such as Vertex AI and AI Platform.
The Generative AI Learning Path offered by Google Cloud is a set of courses that explains generative AI technologies and products. Engineers and software developers are the target audience for the courses. The learning path combines theory and experience through interactive labs, video classes, and skill badge-earning opportunities.
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Courses like these are part of the Generative AI for Developers learning path.
- Overview of Picture Production: Attention Mechanism and Encoder-Decoder Architecture
- Models of Transformers and BERT Models
- Build Models for Image Captioning
- A Brief Overview of Generative AI Studio
- Vertex AI's Generative AI Explorer
- Investigate and Assess Models with Model Garden
To finish the learning path, you need Google Cloud credits. As a requirement, it also comes with introductory training. Google also provides ten courses in a free learning path. A large number of the courses are designed for complete beginners. Some recommend having prior experience with Python, SQL, and/or machine learning.
Although the learning path is intended for novices, seasoned machine learning engineers who wish to learn more about generative AI may also find it useful. Experts in Google AI teach the courses, which include practical labs and exercises.
Advantages of Choosing Google Cloud's Generative AI Learning Path
The Google Cloud Generative AI Learning Path has numerous advantages, such as:
- Learn from Google AI experts: Teachers with extensive knowledge of generative AI are teaching the courses.
- Get practical experience: You will learn how to create and train generative models through the courses' practical labs and exercises.
- Discover Google Cloud Platform: The courses teach you how to train and deploy generative models using services provided by Google Cloud Platform.
- Become licensed: You will be qualified to sit for the Google Cloud Certified Professional Data Engineer exam after completing the learning path.
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Who ought to enroll in Google Cloud's Generative AI Learning Path?
Anyone who wishes to learn about generative AI can do so by following the Google Cloud Generative AI Learning Path, which includes:
- Machine learning engineers: The learning path will teach you how to create and develop generative models if you work in this field.
- Data scientists: The learning path will teach you how to apply generative AI to solve practical issues if you work in this field.
- For researchers: The learning path will provide you with up-to-date information on the newest developments in generative AI.
- Students: The learning path will provide you with a strong foundation in generative AI if you are a student.
How to begin using Google Cloud's Generative AI Learning Path?
You must first register for a Google Cloud account to access the Generative AI Learning Path. You can register for the learning path on the Google Cloud Skills Platform after creating an account. The learning path can be started for free, but to access all of the courses and features, you will have to pay a subscription fee.
It's crucial to remember that, even though this learning path provides insightful information, there are other free courses on the Google Cloud platform. Check out the full catalog in the Google Cloud Skill Boost to learn more about these and other interesting courses, like the Data Engineer and Data Analyst Learning Paths! Happy studying!
Who should take this learning path?
The Generative AI Learning Path is designed for developers who are interested in learning about and developing Generative AI applications. It is also a good resource for machine learning engineers and data scientists who want to expand their skills in Generative AI.
What are the prerequisites for this learning path?
The prerequisites for this learning path are a basic understanding of Python programming, knowledge of linear algebra and calculus, and experience with machine learning and deep learning.
What will I learn in this learning path?
In this learning path, you will learn about the following topics:
What Generative AI and its different types
How Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models work
How to train different Generative AI models
How to use Generative AI to generate text, images, and audio
How to deploy Generative AI applications at scale on Google Cloud AI Platform
What Generative AI and its different types
How Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models work
How to train different Generative AI models
How to use Generative AI to generate text, images, and audio
How to deploy Generative AI applications at scale on Google Cloud AI Platform
What resources do I need to complete this learning path?
You will need access to a Google Cloud account and the following resources:
TensorFlow
PyTorch
Hugging Face
Datasets
TensorFlow
PyTorch
Hugging Face
Datasets
How long does it take to complete this learning path?
The estimated time to complete this learning path is 3-6 months, depending on your prior experience with machine learning and Generative AI.
What can I do after completing this learning path?
After completing this learning path, you will be able to develop your own Generative AI applications. You can use your skills to build Generative AI applications for a variety of industries, such as art, music, design, and marketing. You can also pursue a career as a Generative AI engineer or researcher.