Modern AI Engineering

AI Engineering Bootcamp · Deep learning course

Deep Learning Course: Neural Networks From the Ground Up

A deep learning course that shows what happens inside a neural network. You start with a single neuron, follow backpropagation with real numbers, and finish knowing why deep networks train, fail and generalise.

3 modules · 20 video lessons · 14 interactive labs · a quiz in every lesson

What you will learn

  • What a neuron computes, and why stacking layers makes a network powerful
  • Activation functions: sigmoid, tanh, ReLU and when each is used
  • The forward pass and the loss, worked through by hand
  • Backpropagation and the chain rule, one step at a time
  • Gradient descent, learning rates and why training can stall
  • Vanishing and exploding gradients, and how normalisation fixes them
  • Dropout and regularisation to stop a deep network overfitting
  • Recurrent neural networks, and what PyTorch and TensorFlow do underneath

Who this course is for

  • Beginners in deep learning who want the ideas explained with pictures before formulas.
  • Machine learning learners who know regression and want to move on to neural networks.
  • Engineers heading to generative AI who need deep learning foundations before Transformers and LLMs.

Course syllabus: 3 modules

  1. Module 1: AI Engineering Starter Kit (1 lessons). Before going deep, we meet the six words that come up in every AI engineering conversation: LLM, RAG, MCP, Agent, Fine-tuning and Quantization.
  2. Module 2: Learning from Data (9 lessons). In this module, we will learn what Machine Learning is, the different ways a machine can learn, and the basic terms we will keep using in every later module of this AI Engineering Course.
  3. Module 3: Neural Architectures Deep Dive (10 lessons). In this module, we will learn how a neural network actually learns. We will understand the math behind gradient descent and backpropagation step by step, and the techniques that make training stable.

How the course works

  • Every lesson has a video, a written explanation with diagrams, and real code
  • Interactive labs let you change a value and watch the result
  • A 5-question quiz ends each lesson; 4 correct is a pass
  • Run Python in your browser on the Practice page
  • Learn at your own pace and open lessons in any order

Price

ML & Deep Learning: ₹3,599 a month (a subscription you can cancel any time) or ₹6,599 once for lifetime access in India; $41 or $71 elsewhere. Taxes are included. Compare plans.

Frequently asked questions

Is this deep learning course good for beginners?

Yes. It starts with one neuron and builds up. You need basic Python and school-level math; the calculus is explained where it is used.

Do I need to learn machine learning before deep learning?

A little. The same track teaches the machine learning foundations first: regression, loss functions and gradient descent. Deep learning then builds directly on them.

Does the course explain backpropagation?

Yes, step by step with numbers you can follow, and an interactive lab where you watch the gradients flow back through a small network.

Which deep learning framework does the course use?

The code is plain Python with NumPy so nothing is hidden, and a lesson explains how PyTorch and TensorFlow do the same work internally.

Does this deep learning course cover Transformers and LLMs?

It takes you up to them. Transformers, large language models, RAG and agents are in the Generative AI Engineering track; the Complete AI Engineer track includes everything.

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