Empower yourself with Deep Learning with TensorFlow

In the ever-evolving landscape of technology, deep learning has emerged as a transformative force, reshaping how we approach artificial intelligence. The Deep Learning with TensorFlow badge from the Ira A. Fulton Schools of Engineering at Arizona State University equips participants with the essential skills needed to thrive in this field.

Designed for data scientists, machine learning engineers, and smart manufacturing professionals, this program covers the fundamentals of TensorFlow, the leading open-source library for building and deploying machine learning models. Participants will gain a solid understanding of the core principles and applications of deep learning. 

The badge is earned by completing four micro-badges, each with 10 hours of instruction and application:

1. Import Pretrained Deep Learning Models in TensorFlow: Learners will gain foundational knowledge on accessing and importing pre-trained deep learning models to accelerate their projects.
2. Utilize Pretrained Deep Learning Models in TensorFlow: Participants will learn how to leverage the power of pre-trained models, including feature extraction and decision-making processes.
3. Develop Convolutional Neural Networks with TensorFlow: Learners will dive into the technical aspects of coding Convolutional Neural Networks (CNNs) to tackle image-based data.
4. Develop Recurrent Neural Networks with TensorFlow: Participants will explore the intricacies of developing Recurrent Neural Networks (RNNs) to work with time-series data.

One of the highlights of this program is the seamless integration of pre-trained models. Participants will learn how to access, import, and leverage these powerful tools to accelerate their deep learning projects. By understanding the process of feature extraction and decision-making, they will gain the ability to harness the power of pre-trained models to tackle real-world problems with efficiency and precision.

Learners who continue onto the final two micro-badges, will dive into the intricacies of coding Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) using TensorFlow. These cutting-edge techniques are essential for tackling a wide range of data types, from images to time-series data, enabling participants to develop robust and versatile deep-learning solutions.

The Deep Learning with TensorFlow program is designed and instructed by ASU's Assistant Professor Shenghan Guo in the School of Manufacturing Systems and Networks; commenting on the upcoming program, Guo says, "I'm excited to share my expertise and help learners navigate the transformative world of deep learning with TensorFlow." Guo brings a wealth of experience and dedication in the field, giving learners the opportunity to glean insights from her specialized experience handling complex real-world data from manufacturing environments. 

As one of the world's top-ranked engineering schools, the Ira A. Fulton Schools of Engineering at Arizona State University is renowned for its excellence in engineering education. By choosing this Deep Learning with TensorFlow program, learners can trust that they are receiving a high-quality, industry-relevant education that will launch them towards success in the ever-evolving world of technology.

Interested in learning more? Explore the program and take the first step towards mastering the art of deep learning with TensorFlow.