Best Courses to Learn Machine Learning from Scratch

In this blog, we’ll explore the best courses to learn Machine Learning from scratch, their features, and why they stand out. We’ll also share a roadmap on how to pick the right course for you. 

Why Learn Machine Learning in 2026? 

Before diving into the list of courses, let’s understand the demand. 

• Growing Job Market: According to reports, the global AI and ML job market is expected to grow by over 35% in the next five years. 
• High Salaries: ML engineers are among the top earners in the IT industry. In India, salaries range from ₹6 LPA for freshers to ₹25+ LPA with experience. 
• Cross-Industry Applications: Whether it’s healthcare, fintech, e-commerce, or robotics, ML is transforming industries. 
• Future-Proof Career: With automation and AI adoption rising, ML is no longer optional it’s essential. 

Skills You Need Before Starting Machine Learning 

Don’t worry if you’re a complete beginner. You just need some basic skills: 

• Python Programming – Most ML libraries like TensorFlow, Scikit-learn, and PyTorch are built on Python. 
• Mathematics – Linear algebra, probability, and statistics form the backbone of ML algorithms. 
• Data Handling – Understanding how to clean, analyze, and visualize data is critical. 
• Problem-Solving Mindset – More than coding, ML is about asking the right questions. 

If you don’t have these skills yet, some courses in the list also cover the basics before diving deep. 

Best Courses to Learn Machine Learning from Scratch 

Here’s a handpicked list of courses, including both global platforms and practical career-oriented programs like Uncodemy. 

1. Machine Learning by Andrew Ng (Coursera) 

• Level: Beginner to Intermediate 
• Duration: ~11 weeks 
• Why Take It? 
• This is the most popular ML course in the world. 
• Taught by Andrew Ng, Stanford professor and one of the pioneers of AI. 
• Covers supervised learning, unsupervised learning, linear regression, neural networks, and more. 
• Pros: Strong theoretical foundation, structured lessons, globally recognized certificate. 
• Cons: Limited hands-on coding (focuses more on theory). 
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2. Machine Learning Bootcamp – Uncodemy 

• Level: Beginner-Friendly, Career-Oriented 
• Duration: Flexible (Instructor-led with projects) 
• Why Take It? 
• Tailored for students and freshers who want to start from scratch. 
• Covers Python basics, data preprocessing, ML algorithms, deep learning, and real-life projects. 
• Offers placement assistance and one-on-one mentorship. 
• Includes practical case studies from domains like finance, healthcare, and retail. 
• Pros: Affordable, live mentoring, real projects, strong job support. 
• Cons: Requires commitment to finish assignments and projects. 
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 If you’re looking for a hands-on course with guidance and career support, Uncodemy is one of the best options in India. 

3. Python for Data Science and Machine Learning Bootcamp (Udemy) 

• Level: Beginner 
• Duration: ~40 hours of video lectures 
• Why Take It? 
• Covers Python programming, data visualization, and machine learning basics. 
• Learn popular libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn. 
• Affordable one-time purchase. 
• Pros: Good balance of coding + theory, lifetime access. 
• Cons: Limited support compared to live classes. 
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4. Machine Learning Specialization (DeepLearning.AI + Coursera) 

• Level: Beginner to Advanced 
• Duration: ~3 months 
• Why Take It? 
• Modern update of Andrew Ng’s original course. 
• Includes TensorFlow, advanced deep learning techniques, and deployment. 
• Focused on making students industry-ready. 
• Pros: Industry-level concepts, strong TensorFlow training. 
• Cons: Requires time commitment and good grasp of basics. 
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5. Applied Data Science with Python (University of Michigan – Coursera) 

• Level: Beginner to Intermediate 
• Duration: 5 months (specialization) 
• Why Take It? 
• Focuses on practical data science applications before moving to ML. 
• Covers data visualization, text analysis, and social network analysis. 
• Pros: Great for those interested in applied ML. 
• Cons: Less depth in advanced ML algorithms. 
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6. Intro to Machine Learning with PyTorch (Udacity) 

• Level: Beginner to Intermediate 
• Duration: 3–4 months 
• Why Take It? 
• Focuses on PyTorch, a framework widely used in research and industry. 
• Includes projects, quizzes, and mentor feedback. 
• Pros: Hands-on, project-based. 
• Cons: Paid program with higher pricing. 
•  

7. Machine Learning A-Z (Udemy) 

• Level: Beginner 
• Duration: 45 hours 
• Why Take It? 
• Great starter pack for ML beginners. 
• Covers regression, classification, clustering, reinforcement learning, and deep learning. 
• Pros: Comprehensive beginner-friendly content. 
• Cons: Lacks depth in modern frameworks like TensorFlow or PyTorch. 

How to Choose the Right Course 

With so many courses available, how do you pick the right one? Consider these factors: 

1. Your Goal – If you want a strong theoretical base → Andrew Ng’s course. If you want a job-oriented program → Uncodemy. 

2. Learning Style – Prefer structured videos? Udemy & Coursera. Prefer live classes & mentorship? Uncodemy. 

3. Budget – Coursera/Udemy are affordable. Udacity & bootcamps are costlier but give better mentorship. 

4. Hands-On Projects – Always check if the course offers real projects. That’s what employers value the most. 

Roadmap After Completing a Machine Learning Course 

Completing a course is just step one. To become industry-ready, follow this roadmap: 

1. Practice on Kaggle – Start with beginner datasets like Titanic Survival Prediction. 

2. Work on Real Projects – Predict stock prices, detect fake news, or build recommendation engines. 

3. Build a Portfolio – Push your code to GitHub and showcase projects on LinkedIn. 

4. Learn Deployment – Learn how to deploy ML models using Flask, FastAPI, or cloud platforms. 

5. Prepare for Interviews – Revise ML theory, algorithms, and coding challenges. 

Final Thoughts 

Machine Learning is not just a career option; it’s a gateway to the future of technology. Whether you want to become a Machine Learning Engineer, Data Scientist, or AI Specialist, starting with the right course will set the foundation for your journey. 

If you’re looking for a guided, practical, and placement-focused program in India, the Uncodemy Machine Learning Bootcamp in Noida is one of the best choices. 

Remember: It’s not about learning everything at once, but about taking consistent small steps. The earlier you start, the stronger your career will be.