About this Course

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Intermediate Level
Approx. 31 hours to complete
English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 4 of 6 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 31 hours to complete
English

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IBM

Syllabus - What you will learn from this course

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Week
1

Week 1

5 hours to complete

Tensor and Datasets

5 hours to complete
6 videos (Total 44 min), 1 reading, 11 quizzes
6 videos
1.1 Tensors 1D13m
1.2 Two-Dimensional Tensors9m
Differentiation in PyTorch5m
1.3 Simple Dataset7m
1.5 Dataset4m
1 reading
Labs10m
5 practice exercises
1.1 Tensors 1D5m
1.2 Two-Dimensional Tensors5m
1.3 Derivatives in PyTorch5m
Simple Dataset5m
Datasets10m
Week
2

Week 2

2 hours to complete

Linear Regression

2 hours to complete
7 videos (Total 35 min)
7 videos
2.1 Linear Regression Training3m
Loss3m
Gradient Descent4m
Cost3m
Linear Regression PyToch5m
PyTorch Linear Regression Training Slope and Bias5m
7 practice exercises
Prediction in One Dimension5m
Linear Regression Training5m
Loss5m
Gradient Descent5m
Cost5m
Training Parameters in PyTorch5m
PyTorch Linear Regression Training Slope and Bias5m
3 hours to complete

Linear Regression PyTorch Way

3 hours to complete
5 videos (Total 21 min)
5 videos
Mini-Batch Gradient Descent3m
Optimization in PyTorch3m
Training, Validation and Test Split4m
Training, Validation and Test Split PyTorch3m
4 practice exercises
Quiz: Stochastic Gradient Descent5m
Mini-Batch Gradient Descent5m
3.3 Optimization in PyTorch5m
Training and Validation Data PyTorch5m
Week
3

Week 3

2 hours to complete

Multiple Input Output Linear Regression

2 hours to complete
4 videos (Total 18 min)
4 videos
Multiple Linear Regression Training2m
Linear Regression Multiple Outputs5m
Multiple Output Linear Regression Training1m
2 practice exercises
Multiple Linear Regression Prediction5m
Multiple Output Linear Regression5m
2 hours to complete

Logistic Regression for Classification

2 hours to complete
4 videos (Total 31 min)
4 videos
5.1 Logistic Regression: Prediction6m
Bernoulli Distribution and Maximum Likelihood Estimation5m
Logistic Regression Cross Entropy Loss10m
5 practice exercises
5.0 Linear Classifiers5m
5.0 Linear Classifiers5m
5.1 Logistic Regression: Prediction10m
Bernoulli Distribution and Maximum Likelihood Estimation5m
5.3 Logistic Regression Cross Entropy Loss10m
Week
4

Week 4

2 hours to complete

Softmax Rergresstion

2 hours to complete
3 videos (Total 18 min)
3 videos
6.2 Softmax Function:Using Lines to Classify Data3m
Softmax PyTorch6m
3 practice exercises
6.1 Softmax Function:Using Lines to Classify Data5m
6.2 Softmax Prediction5m
6.3 Softmax PyTorch Quizz5m
3 hours to complete

Shallow Neural Networks

3 hours to complete
6 videos (Total 33 min)
6 videos
More Hidden Neurons2m
Neural Networks with Multiple Dimensional Input5m
7.4 Multi-Class Neural Networks5m
7.5 Backpropagation5m
7.5 Activation Functions4m
6 practice exercises
Neural Networks5m
More Hidden Neurons 5m
Neural Networks with Multiple Dimensional Inputs5m
Multi-Class Neural Networks5m
Backpropagation5m
Activation Functions5m

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