About this Course

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Learner Career Outcomes

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Shareable Certificate
Earn a Certificate upon completion
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Flexible deadlines
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Intermediate Level

Course 1 of the TensorFlow Specialization, Python coding, and high-school level math are required. ML/DL experience is helpful but not required.

Approx. 26 hours to complete
English

Skills you will gain

Inductive TransferAugmentationDropoutsMachine LearningTensorflow

Learner Career Outcomes

13%

got a tangible career benefit from this course

10%

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.
Intermediate Level

Course 1 of the TensorFlow Specialization, Python coding, and high-school level math are required. ML/DL experience is helpful but not required.

Approx. 26 hours to complete
English

Instructor

Offered by

Placeholder

deeplearning.ai

Syllabus - What you will learn from this course

Content RatingThumbs Up97%(7,916 ratings)Info
Week
1

Week 1

7 hours to complete

Exploring a Larger Dataset

7 hours to complete
8 videos (Total 18 min), 5 readings, 3 quizzes
8 videos
A conversation with Andrew Ng1m
Training with the cats vs. dogs dataset2m
Working through the notebook4m
Fixing through cropping49s
Visualizing the effect of the convolutions1m
Looking at accuracy and loss1m
Week 1 Wrap up33s
5 readings
Before you Begin: TensorFlow 2.0 and this Course10m
The cats vs dogs dataset10m
Looking at the notebook10m
What you'll see next10m
What have we seen so far?10m
1 practice exercise
Week 1 Quiz30m
Week
2

Week 2

7 hours to complete

Augmentation: A technique to avoid overfitting

7 hours to complete
7 videos (Total 14 min), 6 readings, 3 quizzes
7 videos
Introducing augmentation2m
Coding augmentation with ImageDataGenerator3m
Demonstrating overfitting in cats vs. dogs1m
Adding augmentation to cats vs. dogs1m
Exploring augmentation with horses vs. humans1m
Week 2 Wrap up37s
6 readings
Image Augmentation10m
Start Coding...10m
Looking at the notebook10m
The impact of augmentation on Cats vs. Dogs10m
Try it for yourself!10m
What have we seen so far?10m
1 practice exercise
Week 2 Quiz30m
Week
3

Week 3

7 hours to complete

Transfer Learning

7 hours to complete
7 videos (Total 14 min), 5 readings, 3 quizzes
7 videos
Understanding transfer learning: the concepts2m
Coding transfer learning from the inception mode1m
Coding your own model with transferred features2m
Exploring dropouts1m
Exploring Transfer Learning with Inception1m
Week 3 Wrap up36s
5 readings
Start coding!10m
Adding your DNN10m
Using dropouts!10m
Applying Transfer Learning to Cats v Dogs10m
What have we seen so far?10m
1 practice exercise
Week 3 Quiz30m
Week
4

Week 4

7 hours to complete

Multiclass Classifications

7 hours to complete
6 videos (Total 12 min), 5 readings, 3 quizzes
6 videos
Moving from binary to multi-class classification44s
Explore multi-class with Rock Paper Scissors dataset2m
Train a classifier with Rock Paper Scissors1m
Test the Rock Paper Scissors classifier2m
A conversation with Andrew Ng1m
5 readings
Introducing the Rock-Paper-Scissors dataset10m
Check out the code!10m
Try testing the classifier10m
What have we seen so far?10m
Wrap up10m
1 practice exercise
Week 4 Quiz30m

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About the DeepLearning.AI TensorFlow Developer Professional Certificate

DeepLearning.AI TensorFlow Developer

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