Deep Learning Playlist (CampusX)

About this course

CampusX's Deep Learning Playlist is a comprehensive journey through the foundations and frontiers of deep learning, taught in a mix of Hindi and English for maximum accessibility. From the basics of perceptrons to cutting-edge transformer architectures, this playlist builds your understanding methodically, with real code examples and intuitive explanations. CampusX has earned a strong reputation in India's self-taught tech community for making complex concepts tangible and practical.

What you'll learn

• How perceptrons and neural networks form the backbone of deep learning, and how to implement them from scratch
• Convolutional Neural Networks (CNNs) for image recognition and computer vision tasks
• Recurrent Neural Networks (RNNs), LSTMs, and GRUs for sequential data and time-series problems
• Attention mechanisms and Transformer architectures that power modern large language models
• Practical training techniques: backpropagation, optimization (SGD, Adam), and regularization methods
• How to preprocess data, build models in popular frameworks, and evaluate performance rigorously
• Real-world applications of deep learning in NLP, computer vision, and beyond

Who this is for

This course suits anyone serious about moving beyond machine learning basics into the depth required for AI roles. You should be comfortable with Python and linear algebra fundamentals—if those feel rusty, a quick review beforehand will help.

• Engineering students — master deep learning before internship season, and stand out in campus placements at tech companies
• Self-taught programmers and career switchers — acquire the skills employers expect for junior ML engineer and AI researcher roles

Prerequisites

Solid grasp of Python programming, basic linear algebra (vectors, matrices, multiplication), and familiarity with NumPy or similar libraries. If you're shaky on math fundamentals, budget extra time for those sections—the instructors explain well, but prior exposure helps.

Why this matters for Indian learners

Deep learning expertise opens doors across India's booming AI sector. Startups in Bangalore, Delhi, and Mumbai are hiring ML engineers aggressively, and roles at companies like Flipkart, Amazon India, and Google India actively seek candidates with transformer and CNN knowledge. Salaries for mid-level deep learning engineers in India start around ₹10–15 LPA and climb steeply with experience. Learning in Hindi and English also removes a barrier many Indian learners face with purely English-medium content, so you can absorb concepts faster.

Frequently asked questions

Is this course really free?

Yes, completely free. CampusX hosts the entire playlist on YouTube with no paywalls or hidden fees.

How long will it take to complete?

The course is designed as 60 hours of content. If you dedicate 8–10 hours per week, you'll finish in about 6–8 weeks. Learners often spend extra time on projects and coding exercises, which we recommend—that's where deep learning truly sinks in.

Will I get a certificate?

This course does not offer an official certificate. However, completing the projects and building a portfolio of deep learning work (shared on GitHub) carries far more weight with employers than a course certificate.