How to Master Generative AI with These 10 Free Courses from Google
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Mastering Generative AI
Generative AI is one of the most exciting and innovative fields of artificial intelligence, where machines can create new and original content, such as images, text, music, and more. If you want to learn how to harness the power of generative AI for your own projects, you are in luck. Google has launched a series of free courses that will teach you the fundamentals and applications of generative AI as well as the best practices and principles of responsible AI.
These courses are designed for anyone who is interested in generative AI, regardless of their background or experience level. You will learn from Google experts and use Google tools to build your own generative AI models. You will also earn badges and certificates to highlight your skills and knowledge.
10 Free AI Courses by Google
Here are the 10 free courses that you can enroll in right now:
- Introduction to Generative AI: Learn what generative AI is, how it works, and what it can do. You will also discover the Google tools that can help you develop your own generative AI applications. This course takes about 45 minutes to complete.
Enroll in Introduction to Generative AI
- Introduction to Large Language Models: Learn what large language models (LLMs) are, how they can generate natural language, and how to use prompt tuning to improve their performance. You will also explore the Google tools that can help you work with LLMs. This course takes about 45 minutes to complete.
Enroll in Introduction to Large Language Models
- Introduction to Responsible AI: Learn what responsible AI is, why it is important, and how Google implements it in their products. You will also learn about the Google’s 7 AI principles that guide their ethical and social impact of AI. This course takes about 45 minutes to complete.
Enroll in Introduction to Responsible AI
- Generative AI Fundamentals: Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models, and Introduction to Responsible AI courses. You will also take a final quiz to test your understanding of the foundational concepts of generative AI.
Enroll in Generative AI Fundamentals
- Introduction to Image Generation: Learn how to use diffusion models, a type of generative AI models that can create realistic images. You will also learn how to train and deploy diffusion models on Vertex AI, a Google Cloud platform for machine learning.
Enroll in Introduction to Image Generation
- Encoder-Decoder Architecture: Learn how to use the encoder-decoder architecture, a common machine learning architecture for sequence-to-sequence tasks, such as machine translation, text summarization, and question answering. You will also learn how to code a simple encoder-decoder model for poetry generation in TensorFlow.
Enroll in Encoder-Decoder Architecture
- Attention Mechanism: Learn how to use the attention mechanism, a technique that allows neural networks to focus on specific parts of an input sequence. You will also learn how attention can improve the performance of various machine learning tasks, such as machine translation, text summarization, and question answering.
- Transformer Models and BERT Model: Learn how to use the Transformer architecture and the BERT model, two of the most powerful and popular generative AI models for natural language processing. You will also learn how to use the Transformer and BERT for different tasks, such as text classification, question answering, and natural language inference.
Enroll in Transformer Models and BERT Model
- Create Image Captioning Models: Learn how to create an image captioning model, a type of generative AI model that can generate natural language descriptions for images. You will also learn how to train and evaluate your image captioning model.
Enroll in Create Image Captioning Models
- Introduction to Generative AI Studio: Learn how to use Generative AI Studio, a product on Vertex AI that helps you prototype and customize generative AI models. You will also learn how to use Generative AI Studio by walking through demos of the product.
Enroll in Introduction to Generative AI Studio
Google’s initiative to offer these free courses is commendable, as it shows their commitment to nurturing the next generation of AI pioneers. These courses offer a great opportunity for anyone who wants to learn and master generative AI, one of the most cutting-edge and creative fields of AI. So, don’t miss this chance, sign up for these courses today, and become a part of the generative AI revolution.
FAQ
Q: What is the purpose of Google’s free courses on Generative AI?
A: The courses are designed to teach the fundamentals and applications of generative AI and the best practices and principles of responsible AI.
Q: Who can enroll in these courses?
A: Anyone interested in generative AI, regardless of their background or experience level, can enroll in these courses.
Q: How many courses are offered by Google on Generative AI?
A: Google offers 10 free courses on Generative AI.
Q: Is Google offering free AI courses? A: Yes, Google is offering 10 free courses on Generative AI. These courses cover a wide range of topics, from the basics of Generative AI to specific applications like image generation and language models.
Q: Can I use Google AI for free?
A: Yes, Google offers several AI tools and platforms that you can use for free, such as TensorFlow and Google Colab. However, some advanced features and resources may require payment.
Q: How can I learn AI for free?
A: You can learn AI for free by enrolling in online courses, such as the ones offered by Google. There are also many other resources available online, including tutorials, blogs, and forums where you can learn about AI.
Q: Does Google have an AI program?
A: Yes, Google has several AI programs. One of them is the Google AI Residency Program, which is a one-year research training position designed to give you hands-on experience with machine learning research.
Q: What are 4 types of AI?
A: The four types of AI are: Reactive Machines, Limited Memory, Theory of Mind, and Self-Awareness. Each type represents a different level of AI sophistication.