8 Artificial Intelligence Courses: Artificial intelligence is more advanced than before. An increasing number of students wish to study AI. Top businesses worldwide provide a variety of online courses in addition to university courses. Students can benefit from flexibility that institutions cannot offer without compromising their legitimacy by enrolling in online courses.
The need for tech workers with these specific talents is growing as AI-powered apps and other technologies become more and more popular. AI programmes that offer basic, intermediate, and advanced-level training are important in this situation where skilling and reskilling are required. In this article, we have listed 8 courses that Google offers on artificial intelligence that you can use to skill up in the vast field of AI.
8 Artificial Intelligence Courses offered by Google
Introduction to Generative AI
This introductory microlearning course aims to define generative artificial intelligence (AI), outline its uses, and emphasise how it differs from traditional machine learning methods. It also covers Google Tools, which can let you develop your own GenAI apps. This course may be completed in roughly 45 minutes.
Introduction to Large-Language Models
This is a course on beginning-level microlearning that covers large language models (LLMs), their applications, and fast tuning to enhance LLM performance. The Google tools that you can use to develop your own GenAI applications are also highlighted. This course should be completed in 45 minutes or less.
Introduction to Responsible AI
This beginner-friendly microlearning course covers the basics of responsible AI, its importance, and how Google uses it in its products. Additionally, it outlines the seven AI principles that Google has created.
Generative AI Fundamentals
You can obtain a skill badge by passing the Introduction to Generative AI, Introduction to Large Language Models, and Introduction to Responsible AI courses. By passing the final exam, you’ll be able to demonstrate that you understand the principles of generative AI.
Introduction to Generative AI Studio
You will get knowledge about Vertex AI’s Generative AI Studio in this course. This platform makes it easier to prototype and modify generative AI models so they can be used in applications. Generative AI Studio capabilities, operations, and usage are demonstrated throughout this course through product demonstrations. To gauge your knowledge, there will be a quiz at the end.
Encoder-Decoder Architecture
An overview of the encoder-decoder architecture, a popular and powerful machine learning architecture for sequence-to-sequence tasks like text summarization, question answering, and machine translation, is provided in this course. You get knowledge on how to train and serve these models as well as the essential elements of the encoder-decoder architecture. You will code a basic implementation of the encoder-decoder architecture for poetry production in TensorFlow starting from scratch in the associated lab walkthrough.
Transformer Models and BERT Model
In this course, the Bidirectional Encoder Representations from the Transformers (BERT) model and the Transformer architecture are introduced. Learn about the self-attention mechanism, one of the key elements of the Transformer design, and how it’s utilised to construct the BERT model. The various applications of BERT, including question answering, text classification, and natural language inference, are also covered in this course.
Attention Mechanism
You will learn about the attention mechanism in this course. It is an effective tool that lets neural networks concentrate on particular segments of an input sequence. You will discover how attention functions and how it might enhance the efficiency of a number of machine-learning tasks, such as text summarization, question answering, and machine translation.
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