Best 6 Artificial Intelligence AI Courses from Google [Free]
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The six free artificial intelligence courses listed below provide a well-organized introduction to the field for newcomers. Every course is designed to provide basic ideas and useful tools in an easy-to-understand manner. Anyone can take the course to enhance their artificial intelligence journey.
All Courses:
Course No. 1: Introduction to Responsible AI
The moral implications of AI technology are the main topic of this course. It provides an overview of responsible AI and emphasizes its significance for AI system development. Google’s seven AI principles are also covered in the course, which helps participants apply AI ethically to their projects. This is essential to guaranteeing that AI technology is applied in a morally righteous and constructive manner for society.
You can earn a completion badge after completing this course. Go to your profile page and view all of the badges you have earned. Enhance your career in cloud computing by showcasing your acquired skills to the world!
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Course No. 2: Introduction to Generative AI
An introduction to generative artificial intelligence is given in this course, along with details on its definition and distinctions from conventional machine learning techniques. Attendees will discover the uses of generative AI and have the opportunity to experiment with Google’s development tools to create AI-powered apps of their own. If you’re interested in studying how artificial intelligence (AI) can create content and develop in many sectors, this microlearning lesson is ideal.
You can earn a completion badge after completing this course. Go to your profile page and view all of the badges you have earned. Enhance your career in cloud computing by showcasing your acquired skills to the world!
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Course No. 3: Introduction to Large Language Models
Large Language Models (LLMs) and their uses are examined in this subject. Students will comprehend LLMs, their applications, and how prompt adjustment may improve output. In addition, the course covers how to create LLM apps with Google tools, offering useful advice on how to implement these models.
You can earn a completion badge after completing this course. Go to your profile page and view all of the badges you have earned. Enhance your career in cloud computing by showcasing your acquired skills to the world!
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Course No. 4 : Attention Mechanism
The attention mechanism, an important component that improves neural networks’ performance by allowing them to concentrate on particular segments of an input sequence, is covered in this course. The use of attention in machine-learning tasks, such as text summarization and machine translation, is covered in this subject. Students will have a greater understanding of how to use focus methods to enhance model performance.
You can earn a completion badge after completing this course. Go to your profile page and view all of the badges you have earned. Enhance your career in cloud computing by showcasing your acquired skills to the world!
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Course No. 5 : Encoder-Decoder Architecture
Knowing how sequence-to-sequence tasks in AI, such as machine translation and text summarization, are tackled, requires an understanding of the encoder-decoder architecture. Learners may design a basic encoder-decoder model using TensorFlow in this hands-on lesson, which also covers the fundamentals of this architecture. AI applications for language challenges benefit greatly from this practical expertise.
You can earn a completion badge after completing this course. Go to your profile page and view all of the badges you have earned. Enhance your career in cloud computing by showcasing your acquired skills to the world!
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Course No. 6 : Transformer Models and BERT Model
The Bidirectional Encoder Representations from Transformers (BERT) model and the intricacies of transformer models are explored in this course. The material covers a number of applications, including text categorization and question answering, and provides a thorough examination of the elements of transformer design, such as the self-attention mechanism. For individuals who are interested in the newest developments in natural language processing technology, this course is perfect.
You can earn a completion badge after completing this course. Go to your profile page and view all of the badges you have earned. Enhance your career in cloud computing by showcasing your acquired skills to the world!
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Conclusion:
Every course is intended to take 45 minutes or less, and upon completion, students receive a digital badge that helps them display their new abilities on professional platforms.
These six free artificial intelligence courses from Google offer a comprehensive introduction to various aspects of AI, ranging from responsible AI practices to advanced topics like transformer models and BERT.
Whether you’re a newcomer to the field or seeking to enhance your existing knowledge, these courses provide valuable insights and practical skills to help you navigate the world of AI with confidence.
Yes, absolutely! These courses are designed to provide a well-organized introduction to artificial intelligence, making them ideal for newcomers to the field who want to gain foundational knowledge.
While some basic understanding of computer science concepts may be helpful, these courses are structured to be accessible to individuals with varying levels of experience in AI.
Yes, most of Google’s online courses, including these AI courses, are self-paced, allowing you to learn at your own convenience and progress through the material at a pace that suits you.
Yes, Google often provides completion badges or certificates for their courses. Upon successfully finishing a course, you may earn a badge or certificate that you can add to your profile or resume to showcase your newly acquired skills.
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