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Verified Information • Last Updated Mar 2026
Deep Learning with PyTorch : Image Segmentation
In this 2-hour project-based course, you will be able to :
- Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair.
- Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library.
- Create train function and evaluator function which will helpful to write training loop. Moreover, you will use training loop to train the model.
Duration
5 Months
Institution
Coursera
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$182
Total Est. Investment
$182
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Deep Learning with PyTorch : Image Segmentation program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.