You can go from beginner to Pro by watching these free AI courses because, surprisingly Google and Microsoft are sharing many Secrets for you to use. free courses from generative AI and large language models to computer vision and deep learning they don’t only teach the fundamentals, but also how you can use cloud platforms to develop for yourself without any previous experience all completely for free.
Just imagine how much more knowledgeable you’d be if you downloaded their information into your brain so stay to the end of this article to find out which course is the best fit for you.
Free artificial intelligence courses with certificate
1- Introduction to Generative AI by Google
this is an introductory-level microlearning course aimed at explaining what generative AI is, how it is used, and how it differs from traditional machine-learning methods. it also covers Google’s tools to help you develop your own gen AI apps. All you need to do is to join this course you’ll also get a completion badge once you’ve finished the course. after joining the course inside you’ll see a course overview section on the left side of the site which contains the videos with titles – introduction to Generative AI Studio, course review: reflection cards, a quiz, and a reading list.
Important questions related to generative AI (FAQ’S)
what is generative AI?
it is a type of artificial intelligence that generates content for you.
what kind of content does generative AI create?
The generative content can be multimodal including text, images, audio, and videos. when given a prompt or a request. generative AI can help you achieve various tasks such as document summarization, information extraction, and code generation.
what is Vertex AI?
vertex AI is an end-to-end ML development platform on Google Cloud that helps you build, deploy, and manage machine learning models with vertex AI.
if you are an app developer or data scientist and want to build an application you can use Generative AI Studio to quickly prototype and customize. Generative AI models with no code or low code.
if you are a data scientist or ML developer who wants to build and automate a generative AI model you can start from Model Garden. model Garden lets you discover and interact with Google’s foundation and third-party open-source models and has built-in ml Ops tools to automate the ml pipeline.
2- Introduction to responsible AI by Google
This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it’s important, and how Google implements responsible AI in its products. it also introduces Google’s seven AI principles. the platform looks very similar to the previous course. on the right side, they have an introduction video to responsible AI.
3- Introduction to Large Language Models by Google
This is an introductory-level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. it also covers Google’s tools to help you develop your own gen AI apps. join the course and start you journey in AI field.
What is large language models? (LLMs)
LLMs and generative AI intersect and they are both a part of deep learning, another area of AI you may be hearing a lot about is generative AI. This is a type of artificial intelligence that can produce new content including text images audio, and synthetic data. large language models refer to large general-purpose language models that can be pre-trained and then fine-tuned for specific purposes.
4- Introduction to image generation by Google
This course introduces diffusion models a family of machine learning models that recently showed promise in the image generation space. the fusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models have become popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
5- Create Image Captioning Models by Google
This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you’ll be able to create your own image-capturing models and use them to generate captions for images. they have two different videos in this course the captioning models overview and the lab walkthrough.
6- artificial intelligence for beginners by Microsoft
Explore the world of Artificial Intelligence (AI) with Microsoft’s 12-week, 24-lesson curriculum! Dive into Symbolic AI, Neural Networks, Computer Vision, Natural Language Processing, and more. Hands-on lessons, quizzes, and labs enhance your learning. Perfect for beginners, this comprehensive guide, designed by experts, covers TensorFlow, PyTorch, and ethical AI principles. Start your AI journey today!”
In this curriculum, you will learn:
- Different approaches to Artificial Intelligence, including the “good old” symbolic approach with Knowledge Representation and Reasoning (GOFAI).
- Neural Networks and Deep Learning, are at the core of modern AI. We will illustrate the concepts behind these important topics using code in two of the most popular frameworks – TensorFlow and PyTorch.
- Neural Architectures for working with images and text. We will cover recent models but may lack a little bit on the state-of-the-art.
- Less popular AI approaches, such as Genetic Algorithms and Multi-Agent Systems.
7- Introduction to Artificial Intelligence by Linkedin
If you’re a project manager, a product manager, a director executive, and an AI Enthusiast starting your career. You can grasp most of the key Concepts in artificial intelligence. This course starts with some simple questions what is artificial intelligence, the rise of machine learning, common AI systems, learn from data, identify patterns, machine learning algorithms, and a lot more. the best part of this course is that each topic video is about 3 minutes long, which makes it easy for you to learn. it also have chapter quiz for each chapter.
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