COVID-19 Update
Visit our COVID update page.

Deep Learning and Artificial Intelligence with TensorFlow and Keras | DBDA.X425
Students will build deep learning prediction models of different complexities, from simple linear logistic regression to major categories of neural networks including convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTMs), and gated recurrent units (GRUs). By the end of the class, students will be proficient in best practices of using TensorFlow and Keras.
The class prepares students to pursue a career in data sciences and AI model development.
Learning Outcomes
At the conclusion of the course, you should be able to
- Use the common deep learning architectures such as CNN and RNN that are used in the industry
- Discuss the significance of hyper-parameters in the architectures
- Prepare data for deep learning using Pandas and NumPy, the de-facto standard for data prep in Python
- Write scalable TensorFlow and Keras code that can be used to train deep learning architectures on real-world business problems
- Debug and understand the inner working of deep learning architectures
Topics Include
- Deep learning and TensorFlow/Keras
- Multilayer perceptrons
- Advanced multilayer perceptrons
- Convolutional neural networks
- Image processing CNN architectures
- Recurrent neural networks
- RNN - prediction with multilayer perceptron
- RNN - prediction with long short term memory networks
Note(s): Students are required to bring laptops for the classroom and work with Python3/
Jupyter Notebook environment.
Skills Needed: Moderate level of computer programming ability in Python, comfortable with
an editor, familiarity with command-line operations on a laptop, and a basic understanding
of Machine Learning models.
- Save Your Seat
Help us confirm course scheduling. Enroll at least seven days before your course starts. - Accessing Canvas
Learn more about gaining access to your course on Canvas in our FAQ section. -
Accessibility and Accommodation
For accessibility questions or to request an accommodation, please visit Access for Students with Disabilities or email the Extension registrar. -
Finance Your Education
Here are ways to pay for your education.
Prerequisite(s)
Sections Open for Enrollment:
Schedule
Date: | Start Time: | End Time: | Meeting Type: | Location: |
---|---|---|---|---|
Thu, 04-13-2023 | 6:30 p.m. | 9:30 p.m. | Hybrid Live-Online | REMOTE |
Thu, 04-27-2023 | 6:30 p.m. | 9:30 p.m. | Hybrid Live-Online | REMOTE |
Thu, 05-11-2023 | 6:30 p.m. | 9:30 p.m. | Hybrid Live-Online | REMOTE |
Thu, 05-25-2023 | 6:30 p.m. | 9:30 p.m. | Hybrid Live-Online | REMOTE |
Thu, 06-15-2023 | 6:30 p.m. | 9:30 p.m. | Hybrid Live-Online | REMOTE |