About this Course

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Learner Career Outcomes

35%

started a new career after completing these courses

40%

got a tangible career benefit from this course

21%

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

Subtitles: English, Korean

Skills you will gain

Recurrent Neural NetworkTensorflowConvolutional Neural NetworkDeep Learning

Learner Career Outcomes

35%

started a new career after completing these courses

40%

got a tangible career benefit from this course

21%

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

Subtitles: English, Korean

Offered by

National Research University Higher School of Economics logo

National Research University Higher School of Economics

Syllabus - What you will learn from this course

Content RatingThumbs Up83%(6,807 ratings)Info
Week
1

Week 1

6 hours to complete

Introduction to optimization

6 hours to complete
10 videos (Total 64 min), 3 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
3 readings
About the University10m
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

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.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.