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Course

Deep Learning Using TensorFlow

CSE-41312

Master Deep Learning with TensorFlow & PyTorch: End-to-End Neural Network Projects

 

Unlock the skills to navigate the dynamic world of deep learning with this comprehensive course! From understanding when to use pre-trained models versus building your own, to diving into the critical algorithms behind neural networks, you will gain the foundational knowledge to thrive as an Artificial Intelligence (AI) practitioner.

Explore cutting-edge machine learning techniques and deep neural network architectures such as CNNs, FCNNs, ResNet, RNNs, Transformers, Large Language Models, and more. Learn the practical applications of TensorFlow2 and PyTorch, with hands-on exercises that walk you through the implementation and deployment of complete neural network projects.

Empower yourself to tackle real-world AI challenges and confidently design, analyze, and deploy solutions using the latest AI methods and tools. Whether you're aiming to enhance your career or take your skills to the next level, this course is your gateway to get practical handle on AI and Deep Neural Networks.


Learning Outcomes:

  • Master Deep Learning Tools by using hands-on experience with TensorFlow 2 and PyTorch,
  • Understand the core principles of Neural Networks,
  • Learn to train and deploy neural networks for image classification, image segmentation, and natural language processing (NLP),
  • Write applications in TensorFlow2 and PyTorch for practical neural networks


Course typically offered: Online in Spring and Fall quarters

Prerequisites: Introduction to Programming (CSE-40028) or a basic working knowledge of Python. Students must have access to a web-enabled computer

Next Steps: After completing of this course, consider taking other courses in the Machine Learning Methods, or Technical Aspects of Artificial Intelligence certificate program

More Information: For more information about this course, please contact unex-techdata@ucsd.edu

Course Information

Online
3.00 units
$775.00

Course sessions

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Section ID:

187140

Class type:

Online Asynchronous.

This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.

Textbooks:

All course materials are included unless otherwise stated.

Policies:

  • No refunds after: 4/7/2025

Schedule:

No information available at this time.
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Instructor: Biljana Aleksic

Biljana Aleksic