Deep Learning With PyTorch

Start solving Computer Vision problems using Deep Learning techniques and the PyTorch framework. Dive into the architecture of Neural Networks, and learn how to train and deploy them on the cloud.

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Prerequisites: Basic understanding of Computer Vision required
(Courses are (a little) oversubscribed and we apologize for your enrollment delay. As an apology, you will receive a 20% discount on all waitlist course purchases. The current wait time will be sent to you in the confirmation email.)
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A glimpse of the topics covered

Course Topics

  1. Introduction to Artificial Intelligence
  2. NumPy Refresher
  3. Introduction to PyTorch
  4. What is inside an ML algorithm?
  1. Understanding Neural Networks
  2. Building Neural Networks in PyTorch
  3. Building Blocks of a Neural Network
  4. Multi-Class Classification using PyTorch
  1. Image Classification
  2. Convolutional Neural Networks
  3. LeNet in PyTorch
  4. Evaluation Metrics for Classification
  5. Important CNN Architectures
  1. Optimizers and LR Schedulers
  2. Training Deep Networks
  3. Using your own Data
  4. Model Complexity, Generalization and Handling Overfitting
  5. Gaining Insights
  1. Troubleshooting Training with TensorBoard
  2. Transfer Learning and Fine-Tuning in PyTorch
  3. Write your own Custom Dataset Class
  4. PyTorch Lightning
  1. Introduction to Semantic Segmentation
  2. PyTorch Segmentation Models and Custom Dataset
  3. Transposed Convolutions
  4. Fully Convolutional Networks
  5. UNet
  6. Dilated Convolution
  7. DeepLabV3
  8. Instance Segmentation
  1. Introduction to Object Detection
  2. Hands on with Object Detection
  3. Classification to Detection
  4. Non Maximum Supression
  5. Evaluation Metrics
  6. Popular Object Detection Architecture
  1. Understanding Faster RCNN
  2. Detectron 2
  3. Ultralytics YOLO
  4. Create a Custom Object Detector

Tool Kit



To receive a Certificate of Completion from, you need to complete the graded quizzes + assignments + projects, with more than 50% marks and within 6 months of enrolling in the course.

Graduation Certificate

Certificate of Completion

You will receive a Certificate of Excellence if you score more than 70% marks on the graded quizzes + assignments + projects within 6 months of enrolling in the course.

Honor Certificate

Certificate of Excellence

This course is available as part of the following Programs


Mastering OpenCV with

Python (Python) - $149

Fundamentals of Computer

Vision & Image Processing
(Python or C++) - $499

Deep Learning with

PyTorch (Python) - $799

Deep Learning with TensorFlow & Keras (Python) - $799

Computer Vision & Deep Learning Applications (Python) - $499

Mastering Generative AI

for Art (Python) - $159

Standard Retail

Student Pricing (30% Discount)

Program 1
CVDL Essentials



Program 2
CVDL Professional



Program 3
CVDL Expert



Program 4
CVDL Master



Program 1
Program 2
Program 3
Program 4
MOCV - Mastering OpenCV with Python - $149
CVIP - Fundamentals of CV & IP - (Python & C++) - $499
DLPT - Deep Learning With PyTorch - $799
DLTK - DL with TensorFlow & Keras -$799
DLAP - CV & DL Applications - $499
GENAI - Mastering Generative AI for Art - $159

Courses Offered

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Dive deep into Stable Diffusion. Learn all the techniques of generating images, fine-tuning Stable Diffusion on your own images and even training a GPT language model.

Available in Python



Frequently Asked Questions

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Yes, our courses are designed to accommodate learners with varying levels of experience. All that is required is a basic understanding of at least one programming language (Python is preferable but not mandatory). We will walk you through the fundamental concepts, providing step-by-step guidance.

To get the most from our courses, you should possess a working knowledge of Python or a similar programming language. For the courses offered in C++, you should have a basic proficiency in C++.

Aside from the programming experience mentioned above, the series of courses are designed to take you from the fundamentals in Image Processing and Computer Vision through more advanced topics in Deep Learning. If you are looking to jump in directly to our Deep Learning courses, then you should have a good understanding of the foundational material in Image Processing and Computer Vision.

Upon finishing a course, you will be awarded a certificate of completion from To qualify for the certificate, you must complete all graded quizzes, assignments, and projects, obtaining a score of at least 50% within six months of enrollment. If your score exceeds 70%, you will be granted an Honor Certificate.