About this Course

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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

Approx. 19 hours to complete

Suggested: 9 hours/week...

English

Subtitles: English

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

Approx. 19 hours to complete

Suggested: 9 hours/week...

English

Subtitles: English

Offered by

Imperial College London logo

Imperial College London

Syllabus - What you will learn from this course

Week
1

Week 1

3 hours to complete

Introduction to TensorFlow

3 hours to complete
14 videos (Total 59 min), 8 readings
14 videos
Welcome to week 11m
Hello TensorFlow!1m
[Coding tutorial] Hello TensorFlow!2m
What's new in TensorFlow 24m
Interview with Laurence Moroney5m
Introduction to Google Colab2m
[Coding tutorial] Introduction to Google Colab8m
TensorFlow documentation3m
TensorFlow installation3m
[Coding tutorial] pip installation3m
[Coding tutorial] Running TensorFlow with Docker10m
Upgrading from TensorFlow 13m
[Coding tutorial] Upgrading from TensorFlow 16m
8 readings
About Imperial College & the team10m
How to be successful in this course10m
Grading policy10m
Additional readings & helpful references10m
What is TensorFlow?10m
Google Colab resources10m
TensorFlow documentation10m
Upgrade TensorFlow 1.x Notebooks10m
Week
2

Week 2

7 hours to complete

The Sequential model API

7 hours to complete
13 videos (Total 59 min)
13 videos
What is Keras?1m
Building a Sequential model4m
[Coding tutorial] Building a Sequential model4m
Convolutional and pooling layers4m
[Coding tutorial] Convolutional and pooling layers5m
The compile method5m
[Coding tutorial] The compile method5m
The fit method4m
[Coding tutorial] The fit method7m
The evaluate and predict methods6m
[Coding tutorial] The evaluate and predict methods4m
Wrap up and introduction to the programming assignment1m
2 practice exercises
[Knowledge check] Feedforward and convolutional neural networks15m
[Knowledge check] Optimisers, loss functions and metrics15m
Week
3

Week 3

7 hours to complete

Validation, regularisation and callbacks

7 hours to complete
11 videos (Total 60 min)
11 videos
Interview with Andrew Ng6m
Validation sets4m
[Coding Tutorial] Validation sets9m
Model regularisation6m
[Coding Tutorial] Model regularisation4m
Introduction to callbacks5m
[Coding tutorial] Introduction to callbacks7m
Early stopping and patience6m
[Coding tutorial] Early stopping and patience5m
Wrap up and introduction to the programming assignment51s
1 practice exercise
[Knowledge check] Validation and regularisation15m
Week
4

Week 4

7 hours to complete

Saving and loading models

7 hours to complete
12 videos (Total 74 min)
12 videos
Saving and loading model weights6m
[Coding tutorial] Saving and loading model weights10m
Model saving criteria4m
[Coding tutorial] Model saving criteria11m
Saving the entire model4m
[Coding tutorial] Saving the entire model8m
Loading pre-trained Keras models5m
[Coding tutorial] Loading pre-trained Keras models7m
TensorFlow Hub modules2m
[Coding tutorial] TensorFlow Hub modules8m
Wrap up and introduction to the programming assignment1m

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 purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, 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.