24 hrs
Machine Learning for Beginners is a comprehensive 12-week program from Microsoft that takes you through the fundamentals of classic machine learning. Whether you're curious about how computers learn patterns in data or want to build your first predictive models, this course breaks down complex concepts into digestible lessons covering regression, classification, clustering, natural language processing, and time series analysis.
Microsoft's structured approach means you'll learn not just theory, but practical skills you can apply immediately—and you can do it entirely free, on your own schedule.
If you're starting your AI journey or want to understand machine learning fundamentals before diving into deep learning, this course is designed for you. No prior ML experience needed—just curiosity and basic comfort with math and coding concepts.
None — this course is beginner-friendly. You should have basic familiarity with Python or another programming language, and comfort with simple algebra and statistics concepts. Everything else is taught from the ground up.
Machine learning skills are in high demand across India's growing AI and analytics sector. Companies like Flipkart, Amazon, Paytm, and countless startups are hiring for data science and ML engineering roles—and demand far outpaces supply of qualified talent. Learning classical ML first gives you the conceptual foundation that employers value, and keeps you competitive for roles paying ₹6–15 LPA for freshers and significantly more with experience.
By completing this course, you'll be ready to tackle real problems: improving recommendation systems for e-commerce, building fraud detection for fintech, or optimizing supply chains. This is the starting point for many career paths in India's booming AI industry.
Yes, completely free. Microsoft makes this curriculum and all materials available at no cost.
The course is designed as a 12-week program, which averages about 2 hours per week. If you have more time available, you can move faster; if you prefer a slower pace, you can spread it over 3–4 months. The total time investment is roughly 24 hours of active learning and project work.
This course does not offer an official certificate upon completion. However, you'll build a portfolio of completed projects that you can showcase to employers—often more valuable than a certificate.