Table of Contents
- General Introduction to AI
- Introduction to AI (IBM / In Portuguese)
- Applied AI (IBM / In Portuguese)
- AI for everyone (DeepLearning / In Portuguese)
- Artificial Intelligence (AWS / In English)
- Machine Learning (AWS / In English)
- Machine Learning Fundamentals (AWS / In English)
- Specialization in Machine Learning (Stanford / In English)
- The AI Economy (University of Virginia / In English)
- Introduction to Responsible AI (Google / In English)
- Introduction to Artificial Intelligence (Microsoft / In English)
- Simplifying your work with Microsoft Copilot (Microsoft / In English)
- AI Curriculum for Beginners (Microsoft / In English)
- Development with AI
- Language Models
- Language models (Google / In English)
- Introduction to major language models (Google / In English)
- Machine Learning Engineer (Google / In English)
- Advanced ML (Google / In English)
- The Nuts and Bolts of ML (Google / In English)
- Data Science and ML (Harvard / In English)
- ML with Python (IBM / In Portuguese)
- Neural Networks and Deep Learning (DeepLearning / In Portuguese)
- Structuring ML projects (DeepLearning / In Portuguese)
- Applied ML in Python (University of Michigan / In English)
- Generative AI
- Introduction to Generative AI (AWS / In English)
- Ethics in the era of generative AI (Microsoft / In English)
- What is Generative Artificial Intelligence (Microsoft / In English)
- Generative AI: the evolution of thinking online research (Microsoft / In English)
- Introduction to Generative AI (Google / In English)
- Generative AI Fundamentals (Google / In English)
- Introduction to Generative AI Studio (Google / In English)
- Create image caption templates (Google / In English)
- Introduction to image generation (Google / In English)
- Prompt Engineering
With the growing relevance of Artificial Intelligence (AI) In several areas, the search for knowledge in this field has become fundamental. With this in mind, we have compiled a list of 41 free courses on AI that range from basic concepts to advanced applications, offering an unmissable opportunity for anyone who wants to deepen their knowledge in this promising area. The courses cover topics such as machine learning algorithm , deep learning, AI ethics,practical business applications and much more, taught by renowned institutions and experts on the subject.
General Introduction to AI
The courses of General Introduction to AI They are essential for anyone who wants to start their studies in this area. They generally cover the basic concepts of Artificial Intelligence, including its definition, history, main areas of application and some basic techniques. Furthermore, these courses often present the main ethical and social challenges related to AI, offering a panoramic view of the field. By completing a General Introduction to AI course, students will be better prepared to understand more advanced courses and practical applications of AI in different industries.
Introduction to AI (IBM / In Portuguese)
This course offered by IBM on the platform Coursera is a comprehensive introduction to the world of Artificial Intelligence (AI). Throughout the course, participants will have the opportunity to learn fundamental AI concepts, such as machine learning algorithm e deep learning, and how these technologies are being applied in different sectors. With instructions in Portuguese, the course is ideal for beginners who want to explore the potential of AI in their careers or studies. Participants will have access to high-quality teaching materials and will be able to learn from renowned experts in the field.
Applied AI (IBM / In Portuguese)
Deepen your knowledge in Artificial Intelligence with the course Applied AI da IBM on the platform Coursera. In this course, you will learn how to apply AI concepts to real-world projects, from collecting and preparing data to implementing AI models. With instructions in Portuguese, this course is recommended for those who want to delve deeper into the practical application of AI in various areas.
AI for everyone (DeepLearning / In Portuguese)
The programme AI for Everyone da Deepearning It is an excellent opportunity for anyone who wants to understand the fundamentals of Artificial Intelligence, even without prior knowledge in the area. With content in Portuguese, this course covers the basic concepts of AI in an accessible way, allowing anyone to understand how this technology is impacting the world around us.
Artificial Intelligence (AWS / In English)
The programme of Artificial Intelligence da AWS offers a broad exploration of the fundamentals and practical applications of AI. Participants dive into essential AI concepts such as machine learning algorithm e deep learning, and discover how these technologies are being applied in different sectors, from healthcare to the automobile industry. This course is available in multiple languages, including English, and is ideal for professionals who want to better understand AI and explore its potential for innovation in AWS.
Machine Learning (AWS / In English)
The programme of Machine Learning da AWS is designed to deepen knowledge in machine learning algorithm . Participants explore different types of machine learning, such as supervised, unsupervised, and reinforcement, and learn how to apply these techniques to real-world problems. This course is available in multiple languages, including English, and is suitable for anyone who wants to become proficient in building and implementing machine learning models in the AWS, to solve complex challenges in various areas.
Machine Learning Fundamentals (AWS / In English)
The programme Machine Learning Fundamentals da AWS is a starting point for beginners who want to understand the basics of machine learning. Participants explore the fundamental principles of supervised and unsupervised learning, learn how to evaluate model accuracy, and discover how to avoid problems like overfitting. This course is available in multiple languages, including English, and is ideal for anyone who wants to start their journey into the world of machine learning and understand its impact on current and future technologies.
Specialization in Machine Learning (Stanford / In English)
A Specialization in Machine Learning da Stanford University is a comprehensive program that covers the fundamental and advanced concepts of machine learning. Throughout the course, participants have the opportunity to explore a variety of topics, including machine learning algorithms, deep learning, natural language processing, and more. This program is accessible to multiple languages, including English, and is ideal for professionals who want to delve deeper into the field of machine learning and apply their knowledge to real-world projects.
The AI Economy (University of Virginia / In English)
The programme The AI Economy offered by University of Virginia explores the economic impact of artificial intelligence on different sectors. Participants learn about the economic models behind AI, the opportunities and challenges it presents, and how companies and governments can prepare for an increasingly AI-driven future. This course is accessible in several languages, including English, and is suitable for professionals interested in better understanding the role of AI in the current and future economy.
Introduction to Responsible AI (Google / In English)
The programme Introduction to Responsible AI offered by Google is an introduction to the ethical and practical principles of responsible AI. Participants learn about the ethical challenges of AI, including algorithmic biases, privacy, and transparency. They also explore best practices for developing and deploying responsible AI systems. This course is accessible in multiple languages, including English, and is ideal for professionals and developers who want to create and use AI ethically and responsibly.
Introduction to Artificial Intelligence (Microsoft / In English)
The programme Introduction to Artificial Intelligence da Microsoft offers a comprehensive overview of fundamental AI concepts. Participants will learn about key topics such as machine learning algorithm , deep learning and practical applications of AI. This course is accessible to multiple languages, including English, and is ideal for beginners who want to understand the fundamentals of AI and how it is shaping the world around us.
Simplifying your work with Microsoft Copilot (Microsoft / In English)
The programme Simplifying your work with Microsoft Copilot (formerly Bing Chat) is designed to help professionals make the most of the chat platform Microsoft's Bing. Participants will learn how to configure, customize, and optimize Bing Chat to improve efficiency and productivity in the workplace. This course is accessible to several languages, including English, and is suitable for professionals who want to improve their skills in using Copilot.
AI Curriculum for Beginners (Microsoft / In English)
O AI resume for beginners da Microsoft is a comprehensive program that covers the basic principles and practical applications of AI. Participants will have the opportunity to learn about the fundamentals of AI, such as machine learning algorithm e data analysis, and explore how these technologies are being used in different sectors. This course is accessible to multiple languages, including English, and is ideal for beginners who want to start their AI journey.
Development with AI
AI Development courses are aimed at those who want to learn how to create practical solutions using Artificial Intelligence techniques. In certain cases, they cover topics that include using popular tools and libraries, such as TensorFlow and PyTorch, for developing AI models. Upon completing an AI Development course, students will be able to interpret intelligent applications and systems that may involve various sectors, such as healthcare, finance, marketing and information technology.
Introduction to AI with Python (Harvard / In English)
The programme Introduction to AI with Python from the University Harvard offers a practical and comprehensive introduction to using the Python to develop artificial intelligence applications. Participants will learn the fundamentals of the language Python and how to apply them in AI projects. This course is accessible to multiple languages, including English, and is ideal for anyone who wants to learn how to program in Python for AI.
Google Cloud Tensorflow (Google / In English)
The programme TensorFlow Google Cloud is designed to help developers master the TensorFlow platform to build machine learning and deep learning models. Attendees will learn how to use TensorFlow to build and train AI models, as well as deploy them in the cloud. Google. This course is accessible in several languages, including English, and is suitable for developers who want to deepen their knowledge of TensorFlow and AI.
Introduction to Amazon CodeWhisperer (AWS / English)
The programme Getting started with Amazon CodeWhisperer da AWS is a comprehensive training program that teaches participants how to use CodeWhisperer, an AI development tool from Amazon. Participants will learn how to use CodeWhisperer to create and train AI models, as well as deploy them in applications and services. AWS. This course is accessible in multiple languages, including English, and is ideal for developers who want to learn how to develop and deploy AI solutions in the AWS.
Using Amazon CodeWhisperer (AWS / English)
The programme Using Amazon CodeWhisperer da AWS is an advanced training program that teaches participants how to use CodeWhisperer, an AI development tool from Amazon. Attendees will learn how to use CodeWhisperer to create, train, and deploy AI models in applications and services. AWS. This course is accessible in multiple languages, including English, and is ideal for developers who want to deepen their knowledge of AI development in AWS.
AI on Microsoft Azure (Microsoft / In Portuguese)
The programme AI in Microsoft Azure offers a practical introduction to using the Azure platform to develop artificial intelligence solutions. Participants will learn how to create and train AI models using tools like Azure Machine Learning and deploy these models to Azure applications and services. This course is accessible in Portuguese and is ideal for developers interested in learning how to use AI in Microsoft Azure.
Language Models
Language Models courses are focused on teaching how computers can understand and intelligently generate natural language. They cover advanced natural language processing (NLP) techniques, such as language models, recurrent neural networks (RNNs) and transformers, which are fundamental for building AI systems capable of understanding and producing texts naturally. Additionally, these courses often explore practical applications of language models in areas such as machine translation, text summarization, text generation, and chatbots.
Language models (Google / In English)
The programme Language Models da Google offers a comprehensive overview of the main language models used in the field of artificial intelligence. Participants will learn about the theoretical and practical foundations behind these models, including the most common architectures such as BERT and GPT, and how to apply them in different contexts. This course is taught in English and is ideal for professionals and students interested in deepening their knowledge of language models.
Introduction to major language models (Google / In English)
The programme Introduction to Major Language Models da Google is a practical introduction to the concepts and applications of major language models such as BERT and GPT. Participants will learn about how these models work, how to train them and how to use them in artificial intelligence projects. This course is taught in English and is suitable for professionals and students who want to learn about the most advanced language models.
Machine Learning Engineer (Google / In English)
The programme Machine Learning Engineer da Google is a comprehensive program that prepares participants to serve as machine learning engineers. Attendees will learn about best practices for developing machine learning models, how to create efficient data pipelines, and how to deploy models to production. This course is taught in English and is ideal for professionals who want to enter or advance their careers in the field of machine learning.
Advanced ML (Google / In English)
The programme of Advanced ML Google is designed for professionals who want to deepen their knowledge in machine learning. Participants explore advanced modeling techniques such as deep neural networks and reinforcement learning and learn to apply these techniques to real-world problems. This course is accessible in multiple languages, including English, and is ideal for anyone who wants to become an expert in machine learning.
The Nuts and Bolts of ML (Google / In English)
The programme The Nuts and Bolts of ML da Google is a practical introduction to the fundamental concepts of machine learning. Participants learn about different types of ML algorithms, how to preprocess and prepare data, and how to evaluate the effectiveness of a model. This course is accessible in multiple languages, including English, and is suitable for beginners who want to understand the fundamentals of ML.
Data Science and ML (Harvard / In English)
The programme of Data Science and ML from the University Harvard is a comprehensive exploration of the techniques and tools used in data science and machine learning. Participants learn how to collect, clean and analyze data, and apply ML models to gain valuable insights. This course is accessible in multiple languages, including English, and is ideal for professionals who want to improve their data science and ML skills.
ML with Python (IBM / In Portuguese)
The programme ML with Python da IBM offers a practical introduction to machine learning using the programming language Python. Participants will learn the fundamental concepts of machine learning and how to apply them to real-world projects. This course is taught in Portuguese and is ideal for beginners who want to learn how to use Python for data analysis and machine learning.
Neural Networks and Deep Learning (DeepLearning / In Portuguese)
The programme Neural Networks and Deep Learning da Deepearning is designed for professionals who want to deepen their knowledge of neural networks and deep learning. Participants explore the theoretical foundations behind these technologies and learn how to apply them to real-world problems. This course is available in Portuguese and is ideal for anyone who wants to become an expert in neural networks and deep learning.
Structuring ML projects (DeepLearning / In Portuguese)
The programme Structuring ML Projects da Deepearning covers best practices and methodologies for structuring and managing machine learning projects. Participants learn to define project goals, create appropriate datasets, select appropriate models, and evaluate model performance. This course is taught in Portuguese and is ideal for professionals who want to improve their ML project management skills.
Applied ML in Python (University of Michigan / In English)
The programme ML Applied in Python da University of Michigan is a practical introduction to machine learning using the programming language Python. Participants learn the basic concepts of machine learning and how to apply them to real-world problems. This course is taught in English and is ideal for beginners who want to learn how to use Python for data analysis and machine learning.
Generative AI
Generative AI courses are focused on teaching how to create Artificial Intelligence models capable of generating new and original content, such as images, music, text and videos. They cover advanced machine learning techniques, such as generative adversarial networks (GANs) and autoregressive language models, which are fundamental to developing systems capable of creating art and media autonomously.
Introduction to Generative AI (AWS / In English)
The programme Introduction to Generative AI da AWS offers a comprehensive overview of the principles and applications of generative artificial intelligence. Participants will learn the basic concepts behind generative AI, including generative and adversarial neural networks (GANs), and how to apply these concepts to practical projects. This course is available in several languages, including English.
Ethics in the era of generative AI (Microsoft / In English)
The programme Ethics in the Era of Generative AI da Microsoft explores the ethical challenges associated with the development and use of generative artificial intelligence. Participants will discuss issues related to privacy, algorithmic bias, liability and social impact of generative AI. This course is available in several languages, including English.
What is Generative Artificial Intelligence (Microsoft / In English)
The programme What is Generative Artificial Intelligence da Microsoft offers a clear and accessible introduction to generative artificial intelligence. Attendees will learn about key techniques and applications of generative AI, including examples of how it is being used across industries. This course is available in several languages, including English.
Generative AI: the evolution of thinking online research (Microsoft / In English)
The programme Generative AI: The Evolution of Thinking Online Search da Microsoft explores recent advances in the area of generative artificial intelligence. Participants will learn about the latest research and developments in this field, including generative and adversarial neural networks (GANs). This course is available in several languages, including English.
Introduction to Generative AI (Google / In English)
The programme Introduction to Generative AI do Google offers a comprehensive introduction to the concepts and applications of generative artificial intelligence. Participants will learn about key techniques, such as GANs, and how to apply them in practical projects. This course is available in several languages, including English.
Generative AI Fundamentals (Google / In English)
The programme Generative AI Fundamentals do Google covers the fundamental principles of generative artificial intelligence. Participants will learn about basic concepts such as neural networks and deep learning and how these concepts apply to generative AI. This course is available in several languages, including English.
Introduction to Generative AI Studio (Google / In English)
The programme Introduction to Generative AI Studio do Google provides a practical introduction to using Generative AI Studio to create generative artificial intelligence models. Participants will learn to use the tools available in Studio and develop models for various purposes. This course is available in several languages, including English.
Create image caption templates (Google / In English)
The programme Create Image Caption Templates do Google teaches you how to create generative artificial intelligence models to generate automatic captions for images. Participants will learn the fundamental concepts behind these models and how to apply them to practical projects. This course is available in several languages, including English.
Introduction to image generation (Google / In English)
The programme Introduction to Imaging do Google offers a comprehensive introduction to the concepts and techniques of imaging using artificial intelligence. Participants will learn how to create realistic and artistically stunning images using generative models. This course is available in several languages, including English.
Check out the best prompts for generating images with AI.
Prompt Engineering
Prompt Engineering courses are aimed at teaching how to design and optimize prompts for language models such as GPT (Generative Pre-trained Transformer). They cover advanced techniques for creating effective prompts that direct the model to generate the desired type of text, avoiding unwanted or inappropriate responses. Additionally, these courses often explore strategies for adjusting and refining prompts based on model feedback, thereby improving your text generation capabilities.
Introduction to Prompt Engineering (AWS / English)
The programme Introduction to Prompt Engineering da AWS offers a comprehensive look at the fundamentals of prompt engineering, an essential technique for improving the ability of language models like GPT-3 to generate text more accurately and relevantly. Participants will learn how to create effective prompts to improve the quality of responses generated by language models. This course is available in several languages, including English.
Pro Prompt Engineering (Learn Prompting / In English)
The programme Pro Prompt Engineering da Learn Prompting is designed for professionals who want to deepen their knowledge in prompt engineering. Participants will learn advanced techniques for optimizing text generation by language models, including strategies for dealing with bias and improving the coherence and relevance of responses. This course is available in several languages, including English.
Prompt Engineering for ChatGPT (Vanderbilt University / In English)
The programme Prompt Engineering for Chat GPT da Vanderbilt University is focused on the practical application of prompt engineering to improve interaction with the Chat GPT, a language model developed by OpenAI. Participants will learn how to create specific prompts to elicit more useful and relevant responses in different contexts. This course is available in several languages, including English.
AI Engineering (IBM / In Portuguese)
The programme of AI Engineering da IBM offers a comprehensive overview of the principles and practices of artificial intelligence engineering. Participants will learn about the fundamentals of AI, including machine learning, neural networks, and AI algorithms. Among several languages, this course is also taught in Portuguese.
Encoder-decoder architecture (Google / In English)
The programme of Encoder-Decoder Architecture do Google explores the principles and techniques behind encoder-decoder architecture in artificial intelligence models. Participants will learn about different architectures, such as LSTM and Transformer, and how to apply them in practical projects. This course is available in English.
See also:
Sources: Learn Prompting, AWS e Google Cloud.
reviewed by Glaucon Vital in 12 / 4 / 24.
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