Introduction to ML and Deep Learning (Raschka)

About this course

This comprehensive course from Sebastian Raschka, a respected machine learning researcher and author, walks you through the complete journey from foundational ML concepts to cutting-edge deep learning techniques. You'll build real projects using PyTorch, one of the most practical frameworks in industry today, gaining hands-on experience that translates directly to real-world work.

What you'll learn

• Core machine learning fundamentals: supervised and unsupervised learning, classification, regression, and model evaluation
• Feature engineering and data preprocessing techniques to prepare raw data for modeling
• Deep neural networks: architectures, training strategies, and how to tune them effectively
• PyTorch essentials: building, training, and deploying neural networks from scratch
• Practical computer vision tasks including image classification and object detection
• Natural language processing basics and how transformers work
• Debugging and optimizing models for better performance and faster inference

Who this is for

If you're serious about AI but want to skip the hype and learn what actually works, this course is for you. You don't need to be an expert—just willing to get your hands dirty with code and math.

• College students and fresh graduates — build a portfolio that gets you noticed in AI hiring pipelines and campus placements
• Working professionals switching careers — gain job-ready ML skills to move into AI-focused roles at tech companies, startups, or research teams

Prerequisites

You'll need solid Python programming skills and basic understanding of linear algebra and probability. If statistics and calculus make you nervous, don't worry—the course teaches what you need—but you can't skip Python.

Why this matters for Indian learners

AI roles in India are growing fast, from startups in Bangalore to established tech companies across metros. Machine learning engineers command competitive salaries, and deep learning expertise puts you ahead in competitive hiring cycles. Whether you're aiming for roles at companies like Flipkart, Amazon India, or emerging AI startups, or planning to contribute to India's growing AI research community, hands-on skills in PyTorch and neural networks are increasingly non-negotiable.

Frequently asked questions

Is this course really free?

Yes. Sebastian Raschka shares this course completely free online. There's no hidden paywall, no "premium" version dangling behind a subscription.

How long will it take to complete?

The course is structured for about 40 hours of active work. If you dedicate 5–7 hours per week, you'll move through it in 6–8 weeks. Go faster or slower depending on how deep you want to dive into projects.

Will I get a certificate?

This course doesn't offer an official certificate of completion. What you do get is real understanding and a portfolio of projects that matter more to employers than a badge anyway.