About this Course

10,169 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
  • Basic calculus, linear algebra, stats
  • Knowledge of AI, deep learning
  • Experience with Python, TF/Keras/PyTorch framework, decorator, context manager
Approx. 25 hours to complete
English

Skills you will gain

SalienceImage SegmentationModel InterpretabilityClass Activation MapsTensorFlow Object Detection API
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
  • Basic calculus, linear algebra, stats
  • Knowledge of AI, deep learning
  • Experience with Python, TF/Keras/PyTorch framework, decorator, context manager
Approx. 25 hours to complete
English

Offered by

Placeholder

DeepLearning.AI

Syllabus - What you will learn from this course

Week
1

Week 1

6 hours to complete

Introduction to Computer Vision

6 hours to complete
9 videos (Total 32 min), 4 readings, 2 quizzes
9 videos
Segmentation intro2m
Why transfer learning?4m
What is transfer learning?4m
Options in transfer learning3m
Transfer learning with ResNet-503m
ResNet-50 in code4m
Network architecture for object localization3m
Evaluating object localization1m
4 readings
Reading item: TensorFlow prerequisite courses10m
Transfer Learning 30m
Transfer Learning with ResNet 5030m
Image Classification and Object Localization30m
1 practice exercise
Introduction and Concepts of Computer Vision30m
Week
2

Week 2

6 hours to complete

Object Detection

6 hours to complete
10 videos (Total 46 min), 5 readings, 2 quizzes
10 videos
R-CNN10m
Getting the model from TensorFlow Hub1m
Running the model on an image2m
Installation and overview of APIs4m
Visualization with APIs3m
Loading a RetinaNet model5m
Loading weights4m
Data prep and training overview3m
Custom Training Loop Code4m
5 readings
Implement Simple Object Detection30m
Predict bounding boxes for object detection30m
Read about the object detection API10m
Use the Object Detection API30m
Eager Few Shot Object Detection30m
1 practice exercise
Object Detection30m
Week
3

Week 3

6 hours to complete

Image Segmentation

6 hours to complete
10 videos (Total 45 min), 3 readings, 2 quizzes
10 videos
Popular image segmentation architectures4m
FCN architecture details5m
Upsampling methods3m
Encoder in code2m
Decoder in code4m
Evaluation with IOU and Dice score4m
U-net overview5m
U-net code: encoder and decoder7m
Instance Segmentation2m
3 readings
Implement a fully convolutional neural network30m
Implement a U-Net30m
Implement Instance Segmentation30m
1 practice exercise
Image Segmentation30m
Week
4

Week 4

7 hours to complete

Visualization and Interpretability

7 hours to complete
6 videos (Total 30 min), 5 readings, 2 quizzes
6 videos
Class activation maps3m
Fashion MNIST class activation map code walkthrough4m
Saliency5m
GradCAM5m
ZFNet5m
5 readings
Class Activation Maps with Fashion MNIST45m
Class Activation Maps with Cats vs Dogs30m
Saliency Maps45m
A conceptual overview of GradCam10m
GradCAM and GradCAM with guided backprop45m
1 practice exercise
Visualization and Interpretation30m

About the TensorFlow: Advanced Techniques Specialization

TensorFlow: Advanced Techniques

Frequently Asked Questions

More questions? Visit the Learner Help Center.