Friday, November 22, 2024

Google Launches 10 Free AI Courses To Empower Innovators

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In a significant move to address the rising demand for skills in generative Artificial Intelligence (AI), Google has launched a collection of free courses aimed at equipping individuals with the knowledge necessary to thrive in this burgeoning field.

As generative AI begins to transform industries and the way we interact with technology, Google’s initiative is poised to make a substantial impact on future innovation and creativity.

Google’s new educational initiative, as highlighted by Mirasys India, includes 10 comprehensive courses designed to provide foundational and advanced understanding of generative AI. These courses are available for free, reflecting Google’s commitment to nurturing the next generation of AI pioneers.

Hereunder are the courses offered by Google:

1. Introduction to Generative AI: This introductory microlearning course explains what generative AI is, how it differs from traditional machine learning methods, and how to use Google tools to develop Gen AI apps. Estimated completion time is 45 minutes.

2. Introduction to Large Language Models: Another introductory course that delves into the use cases of large language models (LLM) and how to enhance LLM performance using prompt tuning. This course also takes approximately 45 minutes.

3. Introduction to Responsible AI: This course covers the importance of responsible AI, how Google implements it, and introduces Google’s seven AI principles.

4. Generative AI Fundamentals: By completing the first three courses and passing a final quiz, learners can earn a skill badge demonstrating their understanding of generative AI.

5. Introduction to Image Generation: This course introduces diffusion models and their application in image generation, particularly using Google Cloud’s Vertex AI.

6. Encoder-Decoder Architecture: Learners are introduced to the encoder-decoder architecture for sequence-to-sequence tasks, with practical implementation in TensorFlow.

7. Attention Mechanism: This course explains the attention mechanism, enhancing understanding of its role in improving machine learning tasks.

8. Transformer Models and BERT Model: An introduction to the Transformer architecture and the BERT model, covering their components and applications.

9. Create Image Captioning Models: This course teaches how to create and evaluate deep learning models for image captioning.

10. Introduction to Generative AI Studio: Learners are introduced to Generative AI Studio on Vertex AI, with practical demos and a final quiz to test knowledge.

Upon completing the courses, participants receive a ‘Completion Badge’ from Google Cloud, symbolising their mastery of generative AI. This badge serves as a valuable credential in an increasingly AI-driven world.

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