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Mathematics for Machine Learning
Artificial intelligence is the broader field of building systems that perform intelligent tasks, while machine learning is a branch of AI that learns patterns from data.
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Build deep learning skills fast with a free PyTorch course: tensors, training, evaluation, and CNNs for image classification—plus practical Colab workflows.
5
(6)
3h39m
19 exercises
Build real AI skills fast with a free online course: search, machine learning, neural nets and NLP, plus hands-on practice and a certificate option.
4.7
(65)
12h40m
7 exercises
Build real AI skills with a free online course: search, heuristics, logic, and uncertainty—ideal for launching projects or preparing for interviews.
4.6
(11)
25h26m
34 exercises
Free CourseMachine Learning tutorial
5
(1)
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6 exercises
Free CourseGoogle Prompting Essentials
4.8
(4)
3h24m
10 exercises
Free CourseData Science
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5h58m
38 exercises
Free CourseR programming for Data Science
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1h07m
6 exercises
Free CourseGoogle AI Essentials
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13 exercises
Free CourseMachine Learning for complete beginners
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1h09m
17 exercises
Free CourseMachine Learning
4.5
(2)
3h51m
6 exercises
Free CourseGenerative AI
4.5
(4)
1h43m
11 exercises
Free CourseData Science full course
4.5
(13)
11h22m
Free CourseArtificial Intelligence Masterclass: Search, Logic, Machine Learning and Deep Learning
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31h57m
57 exercises
Free CourseChat GPT and OpenAI API course
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Free CourseMachine learning for Healthcare
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Free CourseTensorFlow complete course
4
(1)
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Free CourseLarge Language Model LLM
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Free CourseChatGPT full course
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7h06m
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Free CourseComputer AI Vision tutorial
4
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Free CourseNeural Networks and TensonFlow
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Responsible AI in Practice: Fairness, Transparency, and Safety for Real-World Systems
Practical guide to Responsible AI covering fairness, transparency, safety, data governance, and real-world deployment best practices.
Reinforcement Learning Explained: Teaching AI to Make Decisions Through Rewards
Learn reinforcement learning in a practical way, from states and rewards to policies, deep RL, and real-world applications.
MLOps for Beginners: How to Take Machine Learning Models from Notebook to Production
Learn MLOps from the ground up and understand how to take ML models from notebook experiments to reliable production systems.
From Idea to Impact: How to Build and Evaluate an AI Project End-to-End
Learn how to build and evaluate an AI project end-to-end, from problem framing and data to deployment, monitoring, and communication.
AI in the Real World: Building Reliable Systems from Data to Decisions
Learn how real-world AI systems go from data to decisions with reliable modeling, deployment, monitoring, and responsible AI practices.
AI Fundamentals You Actually Use: Data, Features, Evaluation, and Model Selection
Learn practical AI fundamentals like data quality, features, evaluation, baselines, and model selection to build reliable real-world projects.
AI Career Roadmap: Build Job-Ready Skills with a Portfolio (Without Getting Lost)
Build an AI career with a focused roadmap, practical skills, and a portfolio that helps you become job-ready without overwhelm.
An Introduction to Machine Learning: Concepts, Types, and Applications
Learn the basics of machine learning, including core concepts, types, and real-world applications that are shaping industries worldwide.
Web Development
Programming Languages ( Python, Ruby, Java, C )
Office Productivity (Excel, Word and More)
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Develop practical, academic and career-focused skills with free online courses covering intelligent systems, predictive modeling, neural networks, data analysis and generative technologies. Learners can study algorithms, supervised and unsupervised learning, model evaluation, classification, regression, natural language processing and computer vision. Each course is free, includes free certification and features exercises that reinforce theoretical concepts through active learning and practical application.
Beginners can establish a foundation in computational thinking, probability, calculus and linear algebra before progressing to deep neural networks, transformers, convolutional architectures, optimization and large language models. Developers and data professionals can also explore Python, R, TensorFlow, PyTorch, OpenCV, APIs, prompt engineering, chatbots, retrieval-augmented generation and AI agents.
Create a structured curriculum by exploring related collections in machine learning, data science, deep learning, computer vision and mathematics for machine learning. These educational pathways support progressive study, from data preparation and statistical reasoning to model training, validation, deployment and responsible use.
To access the courses, exercises and free certification, install the Cursa app on your mobile device. Android users can get it from Google Play using Download for Android. Apple users can install it from the App Store using Download for iOS / iPhone. Learn at your own pace and strengthen your understanding through accessible lessons and applied educational activities.
What is the difference between artificial intelligence and machine learning?
Artificial intelligence is the broader field of building systems that perform intelligent tasks, while machine learning is a branch of AI that learns patterns from data.
Which AI and machine learning course is best for beginners?
Start with AI fundamentals or machine learning for beginners, then progress to Python, TensorFlow, neural networks, and deep learning.
Do I need programming skills to learn machine learning?
Basic programming is helpful, especially Python, but introductory AI, ChatGPT, and machine learning courses can be taken with little or no coding experience.
What is TensorFlow used for in machine learning?
TensorFlow is a software library used to build, train, evaluate, and deploy machine learning and deep learning models.
What are neural networks and deep learning?
Neural networks are models inspired by connected brain cells. Deep learning uses neural networks with many layers to solve complex tasks such as image, audio, and language analysis.
What is a large language model (LLM)?
A large language model is an AI trained on vast amounts of text to understand and generate language, powering tools such as ChatGPT and AI chatbots.
What can I learn in a computer vision course?
Computer vision courses teach AI methods for interpreting images and video, including image filtering, object detection, recognition, CNNs, and OpenCV.
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What are people saying about free online courses of Artificial Intelligence and Machine Learning
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It's informative and educative for someone beginning and looking forward to utilize AI tools for various purposes for example emailing.
CourseChatGPT Basics course for beginners
Jacopo Ferretti
This is a really good course, especially the second part. I have learned some interesting things from it
CourseData Science
Muhammad Yasir
The PyTorch course was clear, practical, and well paced, helping me gain real skills in deep learning. However, I still haven’t received the certifica
CourseDeep Learning With PyTorch
Farhan Ali
Outstanding Recommendation For People who love to learn about prompting Essentials.
CourseGoogle Prompting Essentials
Constance T
Great info, but the longer videos were repeated in shorter videos. I completed the longer videos, but had to watch the shorter ones for completion.
CourseGoogle AI Essentials
Aakash Kumar
IITian teacher are great and telling about next level of idea.
CourseFundamentals of Artificial Intelligence
Janat Gul
Sir! how can fix the official signature of mine in certificate.
CourseChatGPT full course
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Tiny fonts used therefore learner is unable to follow but just listen.
CourseChatGPT Basics course for beginners
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this is great, I just need more practice and the time because I'm a little bit busy :)
CourseMachine Learning