Google Artificial Intelligence Course (Free Certificates)
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Anyone can obtain the free completion badge certificate for Google’s New Artificial Intelligence Course from your Google profile. The Google Artificial Intelligence Course is available for enrollment online. The Google AI Course is open to anybody, everywhere, and those who request certificates will receive them after finishing each course. These are Google’s Free Online Courses.
Recently, AI has gained a lot of popularity. Many universities, groups, and businesses began studying and comprehending AI. Therefore it can automate processes. Numerous jobs that are currently carried out by people can be automated using it. ChatGPT and Bard are two popular examples of AI.
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Google Artificial Intelligence (AI) Course
Course Host: Google Cloud
Offered By: Google
Free Certificate: Yes
No. of Courses: 10
Fees: Free
Deadline: No any deadlines, anytime you can enroll for this course
Why Should You Focus and Learn AI
▪ There is a big need for skilled personnel in the quickly expanding field of AI.
▪ AI can complete several tasks in a matter of seconds.
▪ The future is AI.
▪ With the aid of, you may complete your tasks, assignments, theses, and essays.
▪ AI will take care of you.
▪ There is no need for thought. Just ask the AI questions.
Google AI Courses
1) Introduction to Generative 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.
2) Introduction to Large Language Models
In this introductory level microlearning course, you will learn about large language models (LLM), their use cases, and how prompt adjustment can improve 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.
The emblem that is shown above can be yours if you’ve finished this course! Visit your profile page to see all the badges you have achieved. By showcasing your acquired skills to the world, you can advance your cloud career!
Also, you can check: Harvard University’s Free Online Courses
3) Introduction to Responsible AI
This basic microlearning course aims to define responsible AI, discuss its significance, and outline how Google incorporates responsible AI into its products. The 7 AI concepts of Google are also introduced.
4) Introduction to Image Generation
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.
5) Encoder-Decoder Architecture
An overview of the encoder-decoder architecture, a potent and common machine learning architecture for sequence-to-sequence tasks like machine translation, text summarization, and question answering, is provided in this course. You gain knowledge of the key elements of the encoder-decoder architecture as well as the training and maintenance of these models. You will write a basic implementation of the encoder-decoder architecture for poetry generation in TensorFlow in the related lab walkthrough.
6) Attention Mechanism
The attention mechanism, a potent method that enables neural networks to concentrate on particular elements of an input sequence, will be covered in this course. You’ll discover how attention functions and how it may be used to enhance a number of machine learning tasks, such as question answering, text summarization, and machine translation.
It should take you about 45 minutes to finish this course.
7) Transformer Models and BERT Model
You will learn about the Bidirectional Encoder Representations from Transformers (BERT) model and the Transformer architecture in this course. You gain knowledge of the key elements of the Transformer architecture, including the self-attention mechanism and how the BERT model is created using it. Additionally, you gain knowledge of the various tasks that BERT can be applied to, including text classification, query resolution, and natural language inference.
8) Create Image Captioning Models
This course shows you how to use deep learning to build an image captioning model. You gain knowledge about how to train and test your model as well as the many elements of an image captioning model, such as the encoder and decoder. You will be able to develop your own image captioning models by the conclusion of the course and use them to produce captions for photos.
9) Introduction to Generative AI Studio
In order to exploit the possibilities of generative AI models in your applications, this course introduces Generative AI Studio, a Vertex AI tool that enables you to prototype and customise generative AI models. By watching product demonstrations, you may discover what Generative AI Studio is, its features and settings, and how to use it. You’ll have a quiz at the end to gauge your understanding.
10) Generative AI Fundamentals
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.
A skill badge is a digital award given out by Google Cloud in appreciation of your expertise with their offerings. Make your profile public and add it to your social media profiles to share your skill badge.
