RiseUpp Logo
Educator Logo

Deep Neural Networks with PyTorch

Master deep learning with PyTorch: Build and train neural networks from basic to advanced architectures including CNN and transfer learning.

Master deep learning with PyTorch: Build and train neural networks from basic to advanced architectures including CNN and transfer learning.

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

(1,683 ratings)

72,615 already enrolled

English

پښتو, বাংলা, اردو, 3 more

Powered by

Provider Logo
Deep Neural Networks with PyTorch

This course includes

31 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

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

PyTorch
Deep Learning
Neural Networks
CNN
Tensor Operations
Gradient Descent
Backpropagation
Model Optimization
GPU Computing
Transfer Learning

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

Share your certificate with prospective employers and your professional network on LinkedIn.

Created by

Provided by

Certificate

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

icon-0icon-1icon-2icon-3icon-4

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

Instructor

Joseph Santarcangelo
Joseph Santarcangelo

4.9 rating

18,630 Reviews

17,12,849 Students

33 Courses

Pioneering Data Scientist Bridging AI Research and Education

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.

Deep Neural Networks with PyTorch

This course includes

31 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.4 course rating

1,683 ratings

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.