About this Course

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Flexible deadlines

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Advanced Level

Approx. 23 hours to complete

Suggested: 5 weeks of study/ 4-5 hours per week...

English

Subtitles: English, Korean

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 23 hours to complete

Suggested: 5 weeks of study/ 4-5 hours per week...

English

Subtitles: English, Korean

Syllabus - What you will learn from this course

Week
1

Week 1

3 hours to complete

Introduction to image processing and computer vision

3 hours to complete
9 videos (Total 56 min), 1 reading, 2 quizzes
9 videos
Short introduction to computer vision4m
Digital images3m
Structure of human eye and vision6m
Color models15m
Image processing goals and tasks2m
Contrast and brightness correction5m
Image convolution7m
Edge detection8m
1 reading
About the University10m
1 practice exercise
Basic image processing10m
Week
2

Week 2

4 hours to complete

Convolutional features for visual recognition

4 hours to complete
12 videos (Total 91 min)
12 videos
AlexNet, VGG and Inception architectures11m
ResNet and beyond10m
Fine-grained image recognition5m
Detection and classification of facial attributes6m
Content-based image retrieval7m
Computing semantic image embeddings using convolutional neural networks8m
Employing indexing structures for efficient retrieval of semantic neighbors9m
Face verification6m
The re-identification problem in computer vision5m
Facial keypoints regression6m
CNN for keypoints regression5m
1 practice exercise
Convolutional features for visual recognition24m
Week
3

Week 3

3 hours to complete

Object detection

3 hours to complete
13 videos (Total 46 min)
13 videos
Sliding windows3m
HOG-based detector2m
Detector training3m
Viola-Jones face detector5m
Attentional cascades and neural networks3m
Region-based convolutional neural network3m
From R-CNN to Fast R-CNN5m
Faster R-CNN4m
Region-based fully-convolutional network2m
Single shot detectors3m
Speed vs. accuracy tradeoff1m
Fun with pedestrian detectors1m
1 practice exercise
Object Detection16m
Week
4

Week 4

4 hours to complete

Object tracking and action recognition

4 hours to complete
11 videos (Total 74 min)
11 videos
Optical flow5m
Deep learning in optical flow estimation5m
Visual object tracking5m
Examples of visual object tracking methods13m
Multiple object tracking5m
Examples of multiple object tracking methods8m
Introduction to action recognition6m
Action classification7m
Action classification with convolutional neural networks5m
Action localization6m
1 practice exercise
Video Analysis16m

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Offered by

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National Research University Higher School of Economics

About the Advanced Machine Learning Specialization

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings....
Advanced Machine Learning

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.