Sungkyunkwan University - Fundamentals of CNNs and RNNs
- Offered byCoursera
- Public/Government Institute
Fundamentals of CNNs and RNNs at Coursera Overview
Fundamentals of CNNs and RNNs
at Coursera
Duration | 5 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Fundamentals of CNNs and RNNs
Table of content
- Overview
- Highlights
- Course Details
- Curriculum
Fundamentals of CNNs and RNNs at Coursera Highlights
Fundamentals of CNNs and RNNs
at Coursera
- Earn a Certificate upon completion from SKKU
Fundamentals of CNNs and RNNs at Coursera Course details
Fundamentals of CNNs and RNNs
at Coursera
More about this course
- This course covers fundamental concepts of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are widely used in computer vision and natural language processing areas
- Learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs
- Learn the concept and the structure of RNNs, and the two variants of RNNs, LSTMs and GRUs
- The goal of this course is to give learners basic understanding of CNNs and RNNs
- Throughout this course, you will be equipped with skills required for computer vision and natural language processing
Fundamentals of CNNs and RNNs at Coursera Curriculum
Fundamentals of CNNs and RNNs
at Coursera
Week 1. CNN Basics
New Video
New Reading
week1
Week 2. Convolution and Pooling
New Video
New Reading
Week2
Week 3. Structure of CNNs
New Video
New Reading
Week3
Week 4. Recurrent Neural Network
New Video
Week4
Week5. LSTM GRU
New Video
Week5
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