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ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING

10 Best AI and ML Courses For You [Free + Paid]

By Lukesh S

Are you curious about how machines can learn, predict, and make decisions, just like humans? If you’ve been exploring the world of Artificial Intelligence (AI) and Machine Learning (ML), you’re not alone. 

These technologies are revolutionizing everything from healthcare to finance, and the demand for skilled professionals is only rising. 

In this article, we’ve curated a list of the best AI and ML courses, both free and paid, that cater to all learning levels. Each course has been selected based on real-world applicability, learning outcomes, and user ratings to help you make the most informed choice.

Table of contents


  1. Top 10 AI and ML Courses – Overview
  2. Top 10 AI and ML Courses - Detailed Look
    • GUVI's AI/ML Career Program
    • Stanford University’s Machine Learning by Andrew Ng (Coursera)
    • Harvard’s CS50’s Introduction to AI with Python (edX)
    • IBM AI Engineering Professional Certificate (Coursera)
    • Google’s Machine Learning Crash Course
    • Udemy: AI & Machine Learning Bootcamp
    • Simplilearn AI & ML Certification (in collaboration with IBM)
    • AI for Everyone by Andrew Ng (Coursera)
    • fast.ai – Practical Deep Learning for Coders
    • Great Learning – Artificial Intelligence & Machine Learning Foundations
  3. Conclusion
  4. FAQs
    • Which is the best AI and ML course for beginners?
    • Do I need to learn math for AI and ML?
    • Can I get a job after completing an AI/ML course?
    • How long does it take to learn AI and ML?
    • Are free AI and ML courses worth it?

Top 10 AI and ML Courses – Overview

Here’s an overview of the top 10 AI and ML Courses:

S.No.Course NameFeatures of the CourseCourse ComplexityPricingCourse Link
1GUVI’s AI/ML Career ProgramIndustry-focused, includes mentorship & projectsBeginner–Intermediate₹90,000Link
2Stanford University’s Machine Learning (Coursera)Taught by Andrew Ng, theory + math-richIntermediateFree to audit (~ ₹3,635 for certificate)Link
3Harvard’s CS50’s Introduction to AI (edX)Case-study approach, good for codersIntermediate~₹16,000+Link
4IBM AI Engineering (Coursera)Python, Deep Learning, and deployment includedIntermediate~₹12,000Link
5Google’s Machine Learning Crash CourseHands-on with TensorFlowBeginnerFreeLink
6Udemy: AI & Machine Learning BootcampReal-world case studies and toolsBeginner–Intermediate₹499 – ₹3,499 (depending on ongoing offers)Link
7Simplilearn AI & ML CertificationCollaboration with IBM, job-ready focusIntermediate₹1,90,000Link
8AI for Everyone by Andrew Ng (Coursera)Non-technical, strategy-focused AI fundamentalsBeginnerFreeLink
9fast.ai Practical Deep Learning for CodersCode-first deep learningIntermediateFreeLink
10Great Learning’s AI/ML CourseBasics to deployment with capstone projectsBeginner~₹2,75,000Link
Top 10 AI and ML Courses – Overview

Top 10 AI and ML Courses – Detailed Look

Let’s explore each of these AI and ML courses in detail:

1. GUVI’s AI/ML Career Program

GUVI’s AI/ML Career Program is a hands-on, job-oriented course designed to help learners transition into AI and ML roles confidently. It’s created by top industry experts and offers mentoring, live classes, and real-world project work. The course also comes with placement assistance and certification.

  • Course Duration: 3 to 6 months (flexible learning paths)
  • Course Complexity: Beginner to Intermediate
  • Technology Stacks covered in the course: Python, NumPy, Pandas, Scikit-learn, TensorFlow, OpenCV, NLP
  • Pre-Requisites: Basic understanding of Python and math fundamentals
  • Learning Outcome: Build complete ML/AI solutions using real-world datasets, get mentored by industry experts, and become placement-ready
  • Course Price [INR]: ₹90,000 (EMI & scholarship options available)
  • Course Rating: 4.7 / 5 (based on 3,000+ reviews)
  • Course Link: GUVI AI/ML Course
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2. Stanford University’s Machine Learning by Andrew Ng (Coursera)

This is one of the most renowned and foundational AI and ML courses ever created. Taught by Andrew Ng, the course introduces key machine learning algorithms, theory, and applications with a strong focus on mathematical intuition.

  • Course Duration: 2 Months (Flexible pace, ~5–7 hours/week)
  • Course Complexity: Intermediate
  • Technology Stacks covered in the course: Octave/MATLAB (not Python), mathematical derivations of ML algorithms
  • Pre-Requisites: Basic linear algebra, probability, and calculus
  • Learning Outcome: Understand supervised learning, unsupervised learning, logistic regression, SVMs, clustering, and more
  • Course Price [INR]: Free to audit (~ ₹3,635 for certificate)
  • Course Rating: 4.9 / 5 (33k+ learners)
  • Course Link: Stanford ML – Coursera 

3. Harvard’s CS50’s Introduction to AI with Python (edX)

Part of Harvard’s prestigious CS50 series, this course explores modern AI concepts through hands-on projects. It blends theory with real-world applications, including game-playing agents, handwriting recognition, and search optimization.

  • Course Duration: 7 weeks (8–10 hours/week)
  • Course Complexity: Beginner
  • Technology Stacks covered in the course: Python, TensorFlow, neural networks, search algorithms, reinforcement learning
  • Pre-Requisites: Familiarity with Python and foundational programming concepts (CS50 or equivalent preferred)
  • Learning Outcome: Build intelligent systems and understand how they work under the hood, from search and inference to neural networks
  • Course Price [INR]: ~₹16,000+
  • Course Rating: 4.8 / 5
  • Course Link: CS50 AI – edX 

4. IBM AI Engineering Professional Certificate (Coursera)

This course is designed for aspiring AI engineers and covers multiple aspects of AI development, machine learning, deep learning, and NLP. It includes hands-on labs and tools such as Jupyter Notebooks and IBM Watson.

  • Course Duration: Approx. 6 months (Self-paced)
  • Course Complexity: Intermediate
  • Technology Stacks covered in the course: Python, Scikit-learn, Keras, PyTorch, IBM Watson, Flask
  • Pre-Requisites: Python programming and basic statistics
  • Learning Outcome: Create, train, and deploy AI models; implement neural networks and NLP pipelines; use real datasets
  • Course Price [INR]: ~₹12,000
  • Course Rating: 4.5 / 5
  • Course Link: IBM AI Engineering

5. Google’s Machine Learning Crash Course

Offered directly by Google, this free course is ideal for beginners looking for a practical introduction to machine learning. It includes videos, exercises, and real-world case studies with TensorFlow.

  • Course Duration: ~15 hours
  • Course Complexity: Beginner
  • Technology Stacks covered in the course: Python, TensorFlow, NumPy
  • Any Pre-requisites needed: Basic programming skills and high school-level math
  • Learning Outcome: Understand ML concepts like model training, loss functions, and overfitting; apply ML to real datasets using TensorFlow
  • Course Price [INR]: Free
  • Course Rating: 4.7 / 5
  • Course Link: Google ML Crash Course

6. Udemy: AI & Machine Learning Bootcamp

This course is designed to take you from a beginner to intermediate level by teaching both the theory and implementation of AI/ML using real datasets. It emphasizes hands-on projects, making it suitable for aspiring professionals and students.

  • Course Duration: 35+ hours of video content
  • Course Complexity: Beginner to Intermediate
  • Technology Stacks covered in the course: Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Keras
  • Any Pre-requisites needed: No prior experience needed; basic computer skills are enough
  • Learning Outcome: Build AI and ML projects such as recommendation systems, face detection, and predictive models using real-world data
  • Course Price [INR]: ₹499 – ₹3,499 (depending on ongoing offers)
  • Course Rating: ★★★★☆ 4.6 / 5 (35,000+ learners)
  • Course Link: Udemy Course

7. Simplilearn AI & ML Certification (in collaboration with IBM)

This is a comprehensive program that combines theory, practical labs, and real industry projects. The course is co-created with IBM and is designed to help professionals transition into AI/ML roles effectively.

  • Course Duration: 6 months (self-paced + live classes)
  • Course Complexity: Intermediate
  • Technology Stacks covered in the course: Python, Keras, TensorFlow, Scikit-learn, Tableau, Hadoop, Spark
  • Any Pre-requisites needed: Programming basics, math fundamentals (statistics, linear algebra)
  • Learning Outcome: Master ML, deep learning, NLP, computer vision, and model deployment with real-time case studies
  • Course Price [INR]: ₹1,90,000 (includes tools access and certifications along with EMI options that starts at ₹8,000)
  • Course Rating: 4.5 / 5
  • Course Link: Simplilearn AIML Course

8. AI for Everyone by Andrew Ng (Coursera)

Unlike technical courses, this one focuses on the strategic, societal, and organizational implications of AI. It’s great for managers, non-engineers, and business professionals who want to understand AI without diving into code.

  • Course Duration: 4 weeks (~6–8 hours total)
  • Course Complexity: Beginner
  • Technology Stacks covered in the course: No coding – conceptual only
  • Any Pre-requisites needed: None
  • Learning Outcome: Understand what AI can and cannot do, identify business applications of AI, and communicate AI strategies across teams
  • Course Price [INR]: Free (~₹3,699 for certificate)
  • Course Rating: 4.8 / 5
  • Course Link: AI for Everyone – Coursera 

9. fast.ai – Practical Deep Learning for Coders

This is a code-first course that allows you to build state-of-the-art deep-learning models without needing a PhD. It’s aimed at developers who want to get hands-on quickly and apply deep learning in real-world applications.

  • Course Duration: 7 weeks (~1–2 hours/week recommended)
  • Course Complexity: Intermediate
  • Technology Stacks covered in the course: Python, PyTorch, fastai, Jupyter Notebooks
  • Any Pre-requisites needed: Solid Python programming experience
  • Learning Outcome: Train image classifiers, NLP models, and recommendation systems, and deploy them using cutting-edge DL techniques
  • Course Price [INR]: Free
  • Course Rating: 4.8 / 5
  • Course Link: fast.ai Course

10. Great Learning – Artificial Intelligence & Machine Learning Foundations

Great Learning’s beginner-friendly AI/ML program helps you understand the fundamentals through self-paced videos and interactive quizzes. The course is ideal for freshers and working professionals looking to start with ML.

  • Course Duration: 12 months (self-paced)
  • Course Complexity: Beginner
  • Technology Stacks covered in the course: Python, Scikit-learn, Pandas, Matplotlib
  • Any Pre-requisites needed: None – designed for absolute beginners
  • Learning Outcome: Understand AI/ML concepts like classification, regression, clustering, and build mini-projects
  • Course Price [INR]: ~₹2,75,000
  • Course Rating: 4.7 / 5
  • Course Link: Great Learning AIML

These AI and ML courses focus solely on the working nature of Artificial Intelligence and Machine Learning, which is particularly useful for those who want to learn it practically!

Conclusion

In conclusion, the journey into AI and ML doesn’t have to be intimidating; it starts with the right learning path. Whether you prefer hands-on coding, conceptual learning, or project-based application, there’s a course tailored for you. From GUVI’s career-focused mentorship to Google’s bite-sized crash course and Stanford’s rigorous theory, each program offers a unique perspective.

By investing your time in any of these AI and ML courses, you’re not just learning a skill, you’re stepping into one of the most transformative fields of our time. So go ahead, choose a course that fits your style, and begin shaping the intelligent solutions of tomorrow.

FAQs 

GUVI’s AI/ML Career Program and Google’s ML Crash Course are excellent choices for beginners due to their structured content and real-world focus.

Yes, understanding linear algebra, statistics, and calculus helps, especially as you move into more advanced areas of AI and ML.

Yes, many online AI and ML courses (like GUVI, Simplilearn, and Coursera) offer placement support and real-world projects to improve job-readiness.

Depending on your pace and background, it can take 3 to 12 months to become proficient through consistent learning and practice.

Absolutely. Platforms like Google, Coursera, and fast.ai offer free yet high-quality content that’s ideal for self-motivated learners.

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Table of contents Table of contents
Table of contents Articles
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  1. Top 10 AI and ML Courses – Overview
  2. Top 10 AI and ML Courses - Detailed Look
    • GUVI's AI/ML Career Program
    • Stanford University’s Machine Learning by Andrew Ng (Coursera)
    • Harvard’s CS50’s Introduction to AI with Python (edX)
    • IBM AI Engineering Professional Certificate (Coursera)
    • Google’s Machine Learning Crash Course
    • Udemy: AI & Machine Learning Bootcamp
    • Simplilearn AI & ML Certification (in collaboration with IBM)
    • AI for Everyone by Andrew Ng (Coursera)
    • fast.ai – Practical Deep Learning for Coders
    • Great Learning – Artificial Intelligence & Machine Learning Foundations
  3. Conclusion
  4. FAQs
    • Which is the best AI and ML course for beginners?
    • Do I need to learn math for AI and ML?
    • Can I get a job after completing an AI/ML course?
    • How long does it take to learn AI and ML?
    • Are free AI and ML courses worth it?