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Deep Neural Networks with PyTorch
This course is part of multiple programs. Learn more.
Course Cost
Free course
Intermediate
Skill Level
13 Hours
Self-paced Video lessons
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full IBM AI Engineering Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.4
72,615 Enrolled
English
What you'll learn
Implement deep neural networks using PyTorch
Master tensor operations and automatic differentiation
Build and train various neural network architectures
Optimize models using advanced techniques and GPU acceleration
Skills you'll gain
This course includes:
6.5 Hours PreRecorded video
1 quiz, 42 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
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Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
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Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 6 modules in this course
This comprehensive course covers deep learning implementation using PyTorch. Starting with fundamental concepts like tensors and automatic differentiation, students progress through various neural network architectures and training techniques. The curriculum includes linear regression, logistic regression, feedforward neural networks, and convolutional neural networks. Advanced topics cover activation functions, normalization, dropout layers, and optimization techniques. The course emphasizes hands-on learning with extensive programming assignments and practical applications.
Tensor and Datasets
Module 1 · 4 Hours to complete
Linear Regression
Module 2 · 2 Hours to complete
Linear Regression PyTorch Way
Module 3 · 2 Hours to complete
Multiple Input Output Linear Regression
Module 4 · 1 Hours to complete
Logistic Regression for Classification
Module 5 · 1 Hours to complete
Practice Project and Final Project
Module 6 · 3 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: IBM Deep Learning with PyTorch, Keras and Tensorflow, IBM AI Engineering Professional Certificate
Reviews
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Faculties
These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.
4.9
18,630
Reviews
17,12,849
Students
33
Courses
Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.
Frequently asked Questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.