About this Course

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Learner Career Outcomes

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started a new career after completing these courses

36%

got a tangible career benefit from this course

20%

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Shareable Certificate
Earn a Certificate upon completion
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Start instantly and learn at your own schedule.
Flexible deadlines
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Advanced Level
Approx. 34 hours to complete
English

Skills you will gain

Recurrent Neural NetworkTensorflowConvolutional Neural NetworkDeep Learning

Learner Career Outcomes

31%

started a new career after completing these courses

36%

got a tangible career benefit from this course

20%

got a pay increase or promotion
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.
Advanced Level
Approx. 34 hours to complete
English

Offered by

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National Research University Higher School of Economics

Syllabus - What you will learn from this course

Content RatingThumbs Up85%(9,495 ratings)Info
Week
1

Week 1

6 hours to complete

Introduction to optimization

6 hours to complete
10 videos (Total 64 min), 4 readings, 3 quizzes
10 videos
Welcome to AML specialization!2m
Course intro6m
Linear regression9m
Linear classification10m
Gradient descent5m
Overfitting problem and model validation6m
Model regularization5m
Stochastic gradient descent5m
Gradient descent extensions9m
4 readings
About the University10m
Rules on the academic integrity in the course10m
Welcome!5m
Hardware for the course10m
2 practice exercises
Linear models30m
Overfitting and regularization30m
Week
2

Week 2

5 hours to complete

Introduction to neural networks

5 hours to complete
9 videos (Total 85 min), 3 readings, 4 quizzes
9 videos
Chain rule7m
Backpropagation9m
Efficient MLP implementation13m
Other matrix derivatives5m
What is TensorFlow10m
Our first model in TensorFlow10m
What Deep Learning is and is not8m
Deep learning as a language6m
3 readings
Optional reading on matrix derivatives1m
TensorFlow reading1m
Keras reading1m
2 practice exercises
Multilayer perceptron10m
Matrix derivatives20m
Week
3

Week 3

6 hours to complete

Deep Learning for images

6 hours to complete
6 videos (Total 59 min)
6 videos
Our first CNN architecture10m
Training tips and tricks for deep CNNs14m
Overview of modern CNN architectures8m
Learning new tasks with pre-trained CNNs5m
A glimpse of other Computer Vision tasks8m
1 practice exercise
Convolutions and pooling30m
Week
4

Week 4

5 hours to complete

Unsupervised representation learning

5 hours to complete
9 videos (Total 81 min)
9 videos
Autoencoders 1015m
Autoencoder applications9m
Autoencoder applications: image generation, data visualization & more7m
Natural language processing primer10m
Word embeddings13m
Generative models 1017m
Generative Adversarial Networks10m
Applications of adversarial approach11m
1 practice exercise
Word embeddings30m

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About the Advanced Machine Learning Specialization

Advanced Machine Learning

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