Utilize pretrained DL models in TensorFlow
Learn to apply pretrained deep learning models in real-world manufacturing and analytics tasks using TensorFlow. This course equips you with hands-on tools for smarter decision-making through feature extraction and inference.
$499
Total: Course cost
10/21/2025
Next start date
2 Weeks to complete
4 modules
Online - scheduled
Learning modality
Earn a credential
View credential
$499
Total: Course cost
10/21/2025
Next start date
2 Weeks to complete
4 modules
Online - scheduled
Learning modality
Earn a credential
View credential
$499
Total: Course cost
10/21/2025
Next start date
2 Weeks to complete
4 modules
Online - scheduled
Learning modality
Earn a credential
View credential
$499
Total: Course cost
2 Weeks to complete
Duration
Online - scheduled
Overview
Required Prerequisites: Please ensure the following before enrolling in this microcredential:
- Fundamental programming knowledge in Python or similar languages (e.g., C/C++, R, Matlab, Java).
- Basic understanding of linear algebra and statistics is also recommended.
In modern engineering environments, the ability to apply deep learning (DL) effectively is a significant advantage. This course provides practical training on how to utilize pretrained DL models using TensorFlow in industrial contexts. You'll learn to build efficient data pipelines, perform inference on production datasets, and extract meaningful features for tasks such as clustering and anomaly detection.
Whether you're working in manufacturing, quality control, or data analytics, this course bridges the gap between theory and practical implementation—providing you with tools that can be immediately applied to improve performance, optimize processes, and support smarter, data-driven decisions.
Key Benefits
- Hands-on TensorFlow model implementation
- Applied feature extraction techniques
- Use cases from industrial applications
- Build production-ready data pipelines
- Develop inference skills with pretrained models
This micro-badge is a part of the Deep Learning with TensorFlow Badge.
Program Schedule: Sessions will be held via Zoom:
- Tuesday, October 21, 2025, 9-11:30am MST
- Thursday, October 23, 2025, 9-11:30am MST
- Tuesday, October 28, 2025, 9-11:30am MST
- Thursday, October 30, 2025, 9-11:30am MST
Micro-badge Level
This micro-badge is offered at Level 2. Level 2 micro-badges empower learners to apply their foundational knowledge through hands-on practice, allowing them to demonstrate their skills with tangible evidence.
Learn more about the Ira A. Fulton Schools of Engineering micro-badge leveling system.
Course Modules
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Who this course is designed for
- Data analysts and engineers in manufacturing – looking to automate insights
- Software developers entering the AI/ML field – seeking practical TensorFlow experience
- Process engineers and operations managers – aiming to enhance predictive capabilities
- Career changers into data science – needing applied DL experience with real data
Outcomes
By the end of this course, you’ll be able to:
- Apply pretrained deep learning models to solve industrial decision-making problems.
- Extract meaningful features from high-dimensional data using dimensionality reduction techniques.
- Build efficient data pipelines to preprocess and feed production data into TensorFlow models.
- Run inference on single and batched data inputs using loaded pretrained models
Practical skills you will develop
This program equips learners with vital skills to thrive in today's complex workforce. Key skills include:
FAQs
Program support
Have additional questions?
Please reach out directly to exec-fseonline@asu.edu for program related questions.
Instructors
Shenghan Guo
Assistant Professor, School of Manufacturing Systems and Networks
Arizona State University
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