Deep Learning Using TensorFlow
CSE-41312
Build Practical Expertise in Modern Neural Network Development with TensorFlow and PyTorch
Deep learning is at the core of today’s most advanced artificial intelligence systems, powering applications such as image recognition, natural language processing, and Generative AI.
In this course, you will develop practical skills in building and deploying deep neural networks using TensorFlow 2 and PyTorch. You will explore key architectures including fully connected neural networks (FCNN), convolutional neural networks (CNN), recurrent neural networks (RNN), ResNet, Transformers, and Large Language Models (LLMs).
Through hands-on projects, you will learn when to use pre-trained models and when to build your own, gaining the confidence to design, analyze, and implement complete end-to-end deep learning solutions for real-world AI challenges.
Course Highlights
- Core principles of deep learning and neural network architectures
- Hands-on training with TensorFlow 2 and PyTorch
- CNNs and ResNet for image classification and segmentation
- RNNs and Transformers for natural language processing (NLP)
- Large Language Models (LLMs) and Generative AI concepts
- End-to-end neural network project development and deployment
- Gain practical experience with industry-standard deep learning tools
- Build and deploy neural networks for real-world applications
- Understand when to use pre-trained models versus custom models
- Strengthen skills in computer vision and NLP
- Prepare for careers in artificial intelligence and machine learning
- Credit earned may be applied toward an academic degree or professional credential, subject to the approval of the receiving institution(s)
Course Details and Next Steps
- 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
Who Should Take This Course?
- Aspiring machine learning and deep learning engineers
- Data scientists and AI practitioners
- Software developers transitioning into AI
- University students in computer science, engineering, or related fields
- Professionals seeking hands-on experience with TensorFlow and PyTorch
- Anyone interested in building real-world AI and deep learning applications