Best Websites to Learn AI and Machine Learning
Interested in how AI and machine learning are changing the world and want to get in on the action without spending a rupee?
Dive into the best websites to learn AI and Machine Learning for free, where you can start unlocking the mysteries of these amazing technologies without any cost.
10 Best Websites for AI and Machine Learning – Overview
Here’s an overview of the top 10 websites to learn AI and Machine Learning:
| S.No. | Website Name | Course Duration | Pricing | Certification | Website Link |
|---|---|---|---|---|---|
| 1 | GUVI | 5 months | Paid | Yes | Visit Now |
| 2 | Coursera | 8 hours | Freemium | Yes | Visit Now |
| 3 | edX | 7 weeks | Freemium | Yes | Visit Now |
| 4 | Udacity | 3 months | Paid | Yes | Visit Now |
| 5 | Fast.ai | 12 weeks | Free | No | Visit Now |
| 6 | Kaggle Learn | 3 hours | Free | Yes | Visit Now |
| 7 | Google AI | Self-paced | Freemium | Yes | Visit Now |
| 8 | Stanford University Online | Self-paced | Freemium | Yes | Visit Now |
| 9 | MIT OpenCourseware | Varied | Free | No | Visit Now |
| 10 | DeepLearning.AI | 6 hours | Paid | Yes | Visit Now |
Best Websites to Learn AI and Machine Learning for Beginners
Below is the list of best websites to learn AI and Machine Learning for beginners:
1. GUVI
The “Artificial Intelligence & Machine Learning” course offered by GUVI, in collaboration with IIT-M Pravartak, is a comprehensive program designed to master AI and ML skills within 5 months.
The course covers the latest developments in cloud technologies, deep learning, NLP, and machine learning model building and deployment, along with the fundamentals of AI. The curriculum includes live online classes, lifetime access to recorded videos, hands-on workshops, and hackathons.
It’s available in English and Tamil, and upon completion, participants receive a globally recognized certification from GUVI and IIT-M Pravartak.
Course Diversity: Covers AI, ML, cloud technologies, deep learning, NLP, and more.
Learning Style: Live online classes, hands-on workshops, and hackathons.
Pricing Structure: Course fee INR ₹89,999 with EMI options available.
Platform Usability: Online live class learning program.
Certifications Offered: Globally recognized certification from GUVI and IIT-M Pravartak.
Language Options: Available in English and Tamil.
Instructor Expertise: Taught by IIT professors and industry experts.
Duration of Courses: 5 months (weekend program).
Community and Support: Technical support and 100% job placement assistance.
2. Coursera
The “Introduction to Artificial Intelligence (AI)” course on Coursera, offered by IBM, is designed to provide learners with a comprehensive understanding of AI, its applications, use cases, and how it is transforming our lives. The course is taught in English and is available with subtitles in 20 languages.
The course aims to describe what AI is, explain terms like Machine Learning, Deep Learning, and Neural Networks, and address several issues and ethical concerns surrounding AI. It also provides advice from experts about learning and starting a career in AI.
Course Diversity: Covers AI fundamentals, machine learning, deep learning, and neural networks.
Learning Style: Structured learning with quizzes and practical insights.
Pricing Structure: Accessible through Coursera subscription, financial aid available.
Platform Usability: User-friendly platform with courses structured for easy navigation and progress tracking.
Certifications Offered: Shareable certificate upon completion.
Language Options: Content available in English with subtitles in 20 languages.
Instructor Expertise: Taught by Rav Ahuja, an experienced instructor from IBM.
Duration of Courses: Approximately 8 hours, self-paced learning.
Community and Support: Access to Coursera’s community of learners and developers.
3. edX
Harvard University’s “CS50’s Introduction to Artificial Intelligence with Python” on edX is an introductory course that delves into the concepts and algorithms foundational to modern artificial intelligence.
This course covers a range of AI topics, including graph search algorithms, classification, optimization, machine learning, large language models, and more.
Students will learn to incorporate these concepts into Python programs and gain experience with libraries for machine learning. The course is designed for learners with CS50 or prior programming experience in Python and is part of the Professional Certificate in Computer Science for Artificial Intelligence.
It’s a self-paced course, estimated to take 7 weeks at 10–30 hours per week.
Course Diversity: Covers a range of AI topics, including machine learning and graph search algorithms.
Learning Style: Hands-on projects with theoretical and practical applications.
Pricing Structure: Free to enroll with an optional upgrade available.
Platform Usability: User-friendly interface with easy navigation.
Certifications Offered: Part of the Professional Certificate in Computer Science for AI.
Language Options: Available in English with video transcripts in multiple languages.
Instructor Expertise: Taught by Harvard University faculty.
Duration of Courses: 7 weeks, 10–30 hours per week.
Community and Support: Access to edX’s community and support resources.
4. Udacity
The “AI Artificial Intelligence Nanodegree” program on Udacity is a comprehensive course designed to provide in-depth knowledge and hands-on experience in artificial intelligence.
This program, taught by industry experts like Sebastian Thrun, Thad Starner, and Peter Norvig, covers a wide range of AI topics, including optimization algorithms, likelihood functions, minimax search, Bayesian networks, and more.
The course is structured to offer real-world projects and practical applications of foundational AI concepts. It is suitable for advanced learners who have a background in object-oriented Python and intermediate Python programming.
Course Diversity: Covers optimization algorithms, Bayesian networks, minimax search, and other AI concepts.
Learning Style: Hands-on learning with real-world projects and practical applications.
Pricing Structure: Paid program with a month-to-month subscription model.
Platform Usability: User-friendly platform with structured learning paths.
Certifications Offered: Completion certificate provided.
Language Options: Content available in English, with subtitles in multiple languages.
Instructor Expertise: Courses taught by industry experts like Sebastian Thrun, Thad Starner, and Peter Norvig.
Duration of Courses: Approximately 3 months to complete.
Community and Support: Access to Udacity’s community and mentorship for learner success.
5. Fast.ai
The “Introduction to Machine Learning for Coders” course on Fast.ai, taught by Jeremy Howard, is a comprehensive and free online program designed for individuals with at least one year of coding experience. The course, which spans approximately 24 hours of lessons, is structured to be completed over 12 weeks with an estimated 8 hours of study per week.
It covers essential machine learning models and includes practical exercises for creating them from scratch. Key skills in data preparation, model validation, and building data products are also addressed. The course is based on lessons recorded at the University of San Francisco for their Masters of Science in Data Science program. It assumes a basic understanding of high school math.
Course Diversity: Covers machine learning models, data preparation, model validation, and data products.
Learning Style: Video-based lessons with practical exercises.
Pricing Structure: Free access to all course materials.
Platform Usability: Online format accessible for self-paced learning.
Certifications Offered: Does not specify certifications.
Language Options: Content available in English.
Instructor Expertise: Taught by Jeremy Howard, an experienced educator and Kaggle’s #1 competitor.
Duration of Courses: Approximately 24 hours of lessons over 12 weeks.
Community and Support: Forums for questions and discussion.
6. Kaggle Learn
Kaggle’s “Intro to Machine Learning” course is a beginner-friendly program designed to teach the core concepts of machine learning and guide learners in building their first models.
The course is structured into seven lessons, each focusing on a key aspect of machine learning. These lessons include “How Models Work,” “Basic Data Exploration,” “Your First Machine Learning Model,” “Model Validation,” “Underfitting and Overfitting,” “Random Forests,” and “Machine Learning Competitions.”
It builds on Python and prepares learners for more advanced topics like Machine Learning Explainability and Intermediate Machine Learning.
Course Diversity: Covers fundamental machine learning concepts and model building.
Learning Style: Interactive tutorials and exercises.
Pricing Structure: Free access to all course materials.
Platform Usability: User-friendly and ideal for beginners.
Certifications Offered: They offer certification after completion.
Language Options: Content available in English.
Instructor Expertise: Taught by Dan Becker, an experienced instructor.
Duration of Courses: Approximately 3 hours (estimated).
Community and Support: Access to Kaggle’s community and discussions.
7. Google AI
The “Machine Learning & AI Courses” offered by Google Cloud Training provide a comprehensive learning experience for those interested in mastering machine learning and artificial intelligence technologies.
These courses are designed to help learners implement the latest machine learning and AI technology, covering a range of tools and platforms like Vertex AI, BigQuery, TensorFlow, Cloud Vision, and Natural Language API. The training is suitable for various job roles, including Data Scientists, Machine Learning Engineers, and Contact Center Engineers.
The courses cover foundational data, ML, and AI tasks in Google Cloud, machine learning on Google Cloud, advanced machine learning with TensorFlow, MLOps fundamentals, ML pipelines, and more.
Course Diversity: Covers a wide range of ML and AI topics, including TensorFlow, Vertex AI, and BigQuery.
Learning Style: Interactive labs and hands-on learning experiences.
Pricing Structure: Varies depending on the course or learning path chosen.
Platform Usability: User-friendly and designed for professionals and learners at various levels.
Certifications Offered: Opportunities for professional certification in machine learning and AI.
Language Options: Courses primarily in English, with some offering multiple language options.
Instructor Expertise: Courses taught by Google experts and industry professionals.
Duration of Courses: Varies based on the course, with flexible learning options.
Community and Support: Access to a community of learners and Google Cloud support.
8. Stanford University Online
The “Machine Learning Specialization” course offered by Stanford Online on edX is a foundational program created in collaboration with DeepLearning.AI.
The specialization provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and best practices for AI and machine learning innovation (evaluating and tuning models, data-centric performance improvement).
Course Diversity: Covers supervised and unsupervised learning, machine learning models, and AI best practices.
Learning Style: Online, self-paced learning with a focus on practical application.
Pricing Structure: Free to view course materials, with a fee for certification.
Platform Usability: User-friendly online platform with easy access to course modules.
Certifications Offered: Certificate available upon completion.
Language Options: Content available in English.
Instructor Expertise: Courses developed by Stanford University and DeepLearning.AI.
Duration of Courses: Self-paced learning experience.
Community and Support: Access to course forums and support resources.
9. MIT OpenCourseWare
The “Mathematics of Big Data and Machine Learning” course, offered by MIT OpenCourseWare, provides an in-depth exploration of artificial intelligence and machine learning.
Taught by Dr. Jeremy Kepner and Dr. Vijay Gadepally, this course was conducted during the January IAP 2020 and is categorized under Supplemental Resources at the undergraduate level.
The course content includes a comprehensive overview of AI and a deep dive into machine learning, encompassing supervised learning, unsupervised learning, and reinforcement learning. This lecture series is designed to offer insights into the mathematical foundations and practical applications of big data and machine learning.
Course Diversity: Covers AI, supervised learning, unsupervised learning, and reinforcement learning.
Learning Style: Lecture-based with in-depth theoretical and practical insights.
Pricing Structure: Free access to course materials.
Platform Usability: Well-organized content for easy learning.
Certifications Offered: Does not offer certifications.
Language Options: Content available in English.
Instructor Expertise: Taught by Dr. Jeremy Kepner and Dr. Vijay Gadepally.
Duration of Courses: Conducted during January IAP 2020.
Community and Support: Does not specify community or support options.
10. DeepLearning.AI
“AI for Everyone” by DeepLearning.AI is a non-technical course aimed at providing a broad understanding of artificial intelligence (AI) to a wide audience, including non-engineers.
The course, taught by AI pioneer Andrew Ng, focuses on demystifying AI and explaining key concepts such as machine learning, deep learning, and neural networks. It also addresses the impact of AI on society and navigates through technological changes.
The course covers the workflow of machine learning and data science projects, AI terminology, and AI strategy. It includes case studies and practical advice for building a sustainable AI strategy, making it suitable for non-technical business professionals, machine learning engineers, and data scientists.
Course Diversity: Covers AI basics, machine learning, deep learning, and AI strategy.
Learning Style: Non-technical, with a focus on understanding AI’s impact and applications.
Pricing Structure: Accessible through a subscription or individual course purchase.
Platform Usability: User-friendly online learning platform.
Certifications Offered: Certificate of completion available.
Language Options: Content available in English.
Instructor Expertise: Taught by Andrew Ng, a renowned expert in AI.
Duration of Courses: Approximately 6 hours of content.
Community and Support: Access to a community of learners and professionals.
Frequently Asked Questions
1. What are the best websites for learning AI and Machine learning?
The best websites for learning AI and Machine learning are:
- GUVI
- Coursera
- edX
- Udacity
- Fast.ai
- Kaggle Learn
- Google AI
2. What are some free AI and Machine learning learning websites along with certifications?
edX, Fast.ai, Kaggle Learn, Stanford University Online, and MIT OpenCourseWare are some free AI and Machine learning learning websites along with certifications.
3. Why should I choose website for learning AI and Machine Learning?
You should choose a website for learning AI and Machine Learning because they offer flexibility and have a variety of learning resources. They cater to different learning styles with interactive tutorials, video lectures, and hands-on exercises.
4. How do I choose the right website for learning AI and Machine Learning?
You can choose the right website for learning AI and Machine Learning by considering factors like course content quality, learning style compatibility (videos, interactive exercises), instructor expertise, community support, and pricing.
5. Can a beginner learn AI and Machine Learning effectively through websites?
Yes, beginners can effectively learn AI and Machine Learning through websites. Many platforms offer beginner-friendly courses that start with basics and gradually progress to more complex topics.
6. Are there websites that offer content in multiple languages for learning AI and Machine Learning?
Yes, websites like GUVI, Coursera, edX, and Udacity provide AI and Machine Learning learning content in multiple languages and subtitles.
Final Words
These sites are like your friendly neighborhood tech gurus, making learning AI and machine learning fun. They’re perfect for getting a solid start in these exciting fields without having to spend almost nothing.
Keep checking this article as we will keep updating this space as more websites make space in the heart and study schedule of students preparing for placements and competitive exams.
Explore More AI & ML Resources
- AI and Machine Learning YouTube Channels
- AI Project Ideas
- Machine Learning Project Ideas
- AI Programming Languages
- Machine Learning Programming Languages
- Machine Learning Frameworks
Explore More Websites
- Python
- Java
- Coding
- C++
- C Programming
- SQL
- JavaScript
- Data Science
- HTML & CSS
- Web Development
- Data Structures and Algorithms
- Ethical Hacking
- Android Development
- React JS
- Game Development
- Competitive Programming
- Digital Marketing
- Tableau
- DBMS
- R Programming
- PHP
- Cyber Security
- Excel
- Node JS
- Data Analytics
- Bootstrap
- Cloud Computing
- Operating System
- Angular
- RPA
Thirumoorthy serves as a teacher and coach. He obtained a 99 percentile on the CAT. He cleared numerous IT jobs and public sector job interviews, but he still decided to pursue a career in education. He desires to elevate the underprivileged sections of society through education
Thirumoorthy serves as a teacher and coach. He obtained a 99 percentile on the CAT. He cleared numerous IT jobs and public sector job interviews, but he still decided to pursue a career in education. He desires to elevate the underprivileged sections of society through education
Related Posts
Best Apps to Learn Web Development
Ever thought about building your own website or launching a career in tech but don’t know where to start? With the …
