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Jee-Hyong Lee
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.
Read more
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.
Read more
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.
In the CNN part, you will learn the concepts of CNNs, the two major operators (convolution and pooling), and the structure of CNNs. In the RNN part, you will 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.
Register for this course and see more details by visiting:
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What's inside
Syllabus
Week 1. CNN Basics
Week 2. Convolution and Pooling
Week 3. Structure of CNNs
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Syllabus
Week 1. CNN Basics
Week 2. Convolution and Pooling
Week 3. Structure of CNNs
Read more
Week 4. Recurrent Neural Network
Week5. LSTM GRU
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Delves into deep learning models, which is a must-learn subject for those seeking a career in AI and machine learning
Taught by an expert in the field of natural language processing and deep learning
Examines how to address complex problems using deep learning models
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Activities
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Career center
Learners who complete Fundamentals of CNNs and RNNs will develop knowledge and skills
that may be useful to these careers:
AI Engineer
AI Engineer
An AI Engineer may wish to study the concepts of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to improve their ability to create models for computer vision and natural language processing. The Fundamentals of CNNs and RNNs course from Sungkyunkwan University covers the fundamental concepts of CNNs and RNNs. This course can help AI Engineers build a foundation that will enhance their work.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use CNNs and RNNs to train models for various tasks in computer vision, natural language processing, and other domains. The Fundamentals of CNNs and RNNs course from Sungkyunkwan University provides a solid foundation in these concepts, enabling Machine Learning Engineers to build and deploy more effective models. This course is especially beneficial for those seeking to specialize in computer vision or natural language processing.
Deep Learning Engineer
Deep Learning Engineer
Deep Learning Engineers utilize CNNs and RNNs to develop deep learning models for various applications. The Fundamentals of CNNs and RNNs course from Sungkyunkwan University provides a comprehensive overview of these techniques, empowering Deep Learning Engineers to design and implement more sophisticated deep learning models. This course is a valuable asset for those seeking to advance their skills in deep learning.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers leverage CNNs to develop computer vision systems for various applications, such as image recognition, object detection, and medical imaging. The Fundamentals of CNNs and RNNs course from Sungkyunkwan University provides a strong foundation in CNNs, empowering Computer Vision Engineers to build and deploy more accurate and robust computer vision systems.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers employ RNNs to develop natural language processing systems for various applications, such as machine translation, text summarization, and sentiment analysis. The Fundamentals of CNNs and RNNs course from Sungkyunkwan University provides a comprehensive overview of RNNs, enabling Natural Language Processing Engineers to build and deploy more effective natural language processing systems.
Data Scientist
Data Scientist
Data Scientists may utilize CNNs and RNNs for various tasks in data analysis and machine learning, such as image classification, natural language processing, and time series forecasting. The Fundamentals of CNNs and RNNs course from Sungkyunkwan University provides a foundational understanding of these techniques, enabling Data Scientists to expand their skillset and tackle more complex data science problems.
Software Engineer
Software Engineer
Software Engineers working in computer vision or natural language processing may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University beneficial. This course provides a solid foundation in these concepts, enabling Software Engineers to develop more sophisticated and effective software solutions in these domains.
Research Scientist
Research Scientist
Research Scientists working in artificial intelligence, computer vision, or natural language processing may benefit from the Fundamentals of CNNs and RNNs course from Sungkyunkwan University. This course provides a comprehensive overview of these techniques, enabling Research Scientists to conduct more advanced research and develop innovative solutions in these fields.
Computer Science Professor
Computer Science Professor
Computer Science Professors teaching courses in computer vision, natural language processing, or deep learning may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University useful. This course provides a comprehensive overview of these topics, enabling Computer Science Professors to stay up-to-date with the latest advancements and effectively teach these concepts to their students.
Data Analyst
Data Analyst
Data Analysts working with image data or text data may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University helpful. This course provides a foundational understanding of these techniques, enabling Data Analysts to extract more insights from their data and develop more accurate and reliable data analysis models.
Product Manager
Product Manager
Product Managers working on products that incorporate computer vision or natural language processing may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University helpful. This course provides a basic understanding of these technologies, enabling Product Managers to make more informed decisions about the features and capabilities of their products.
Business Analyst
Business Analyst
Business Analysts working in industries that utilize computer vision or natural language processing may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University beneficial. This course provides a basic understanding of these technologies, enabling Business Analysts to better understand the potential applications and limitations of these technologies in their business context.
Marketing Manager
Marketing Manager
Marketing Managers working on campaigns that utilize computer vision or natural language processing may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University helpful. This course provides a basic understanding of these technologies, enabling Marketing Managers to better understand the capabilities and limitations of these technologies and develop more effective marketing strategies.
Sales Manager
Sales Manager
Sales Managers working with clients in industries that utilize computer vision or natural language processing may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University helpful. This course provides a basic understanding of these technologies, enabling Sales Managers to better understand the needs of their clients and effectively communicate the benefits of their products or services.
Financial Analyst
Financial Analyst
Financial Analysts working with companies that utilize computer vision or natural language processing may find the Fundamentals of CNNs and RNNs course from Sungkyunkwan University helpful. This course provides a basic understanding of these technologies, enabling Financial Analysts to better understand the potential risks and opportunities associated with these technologies and make more informed investment decisions.
For more career information including salaries, visit:
OpenCourser.com/course/0vwqz0/fundamentals
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Fundamentals of CNNs and RNNs.
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Provides a comprehensive overview of deep learning, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of recurrent neural networks, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about RNNs.
Provides a comprehensive overview of natural language processing with deep learning, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about NLP.
Save
Provides a comprehensive overview of deep learning for computer vision, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about computer vision.
Provides a comprehensive overview of deep learning with Keras, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of natural language processing with spaCy, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about NLP.
Save
Provides a comprehensive overview of computer vision with OpenCV, covering the latest advances in the field. It valuable resource for anyone who wants to learn more about computer vision.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0vwqz0/fundamentals
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Effort
4 hours/week
Level
Introductory
Via
Coursera
Institution
Sungkyunkwan University
Instructor
Jee-Hyong Lee
Language
한국어
Good to know
Delves into deep learning models, which is a must-learn subject for those seeking a career in AI and machine learning
Taught by an expert in the field of natural language processing and deep learning
Examines how to address complex problems using deep learning models
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