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The top Google AI courses every techie should take in 2023


In 2023, every techie should enroll in one of Google’s many AI courses in order to be equipped and upskilled to harness the potential of AI.

As we already know, artificial intelligence (AI) is one of today’s most revolutionary technologies, reshaping and changing a variety of sectors. Google is now a front-runner in the AI space.

Google is now providing a variety of AI courses that every techie should participate in by 2023 in order to empower and upskill people and businesses to harness the power of AI.

This beginner-level microlearning course explains what generative artificial intelligence (AI) is, how it works, and how it differs from more conventional machine learning techniques. Additionally covered are Google Tools for creating your own Gen AI apps.It should take you about 45 minutes to finish this course.

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This basic microlearning course outlines responsible AI’s definition, significance, and use in Google’s products. The 7 AI concepts of Google are also introduced.

Finish the Introduction to Generative AI, Introduction to Large Language Models, and Introduction to Responsible AI courses to receive a skill badge. You will prove that you comprehend the basic ideas behind generative AI by passing the final exam.

This beginner level microlearning course investigates large language models (LLM), their use cases, and prompt tuning’s benefits for improving LLM performance. Additionally covered are Google tools for creating your own Gen AI apps. It should take you about 45 minutes to finish this course.

Diffusion models are a family of machine learning models that have lately shown promise in the field of picture production, and they are introduced in this course. Diffusion models are influenced by thermodynamics, a branch of physics. Diffusion models have gained popularity recently in both academia and business. Many cutting-edge picture generating models and tools on Google Cloud are supported by diffusion models. You will learn how to train and use diffusion models on Vertex AI as well as the theory behind them in this course.



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