Data Science for Engineers
This series of intensive courses is designed to help working professionals harness the power of data in their work to achieve results.
Optimize Workflows and Improve Business Decisions with Data
To be effective and keep up to speed in today’s workforce, business, engineering, and research professionals need to understand how to efficiently manage, process, and respond to an ever-expanding stream of data. From industrial sensors, robotics and advanced instrumentation to marketing, sales, and distribution logistics, data literacy has never been more important. Participants in Data Science for Engineers at GIX learn to apply data analytics, science, and engineering methods to transform raw data and uncover valuable, actionable insights within their organizations.
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Who Should Enroll
This course series is designed for working engineers, business, and research professionals interested in optimizing and automating operations or developing data-driven strategies for their business. Each course can be taken individually or taken together as a linked series. Participants in individual courses will focus on specific topics and can earn an optional 2 Continuing Education Units (CEUs) per course.
Enroll in our project consulting if you intend to apply data science tools in your work on a regular basis and would like to build a robust working model with ongoing faculty consultation using your own dataset or one provided.
What You Will Learn
Participants in this series will learn how to apply fundamental programming skills and modern data science methods with real data sets and models. Participants will understand the opportunities and constraints of working with large data sets to improve automation, optimization, and strategic decision making that benefit operations and business, overall.
Python Foundations topics include:
- Jupyter notebooks
- Data structures
- Flow control
- Functions
- Data visualization
- Libraries: Pandas, NumPy, Matplotlib, and Seaborn
- Object-oriented programming
- Debugging
Data Science Foundations topics include:
- Bias-variance tradeoff
- Linear, logistic, and multivariate regression
- L1 and L2 regularization
- Inferential statistics including moods median, t-tests, f-tests, and ANOVA
- Descriptive statistics
- Tree-based and resampling (boosting/bagging) methods
- Clustering and dimensionality reduction
- Unit tests
General Applications of Neural Networks topics include:
- Convolutional neural networks (computer vision)
- Long-short term memory networks (time series analysis)
- Cloud applications and model deployment
- Unit tests and continuous integration
- Monolithic vs. microservices applications
At the conclusion of the series, participants will be able to confidently manage complex sets of data and use them to predict and model processes, automate tasks, reduce downtime, improve margin velocity, forecast sales, automate quality control, analyze customer feedback, and other means of optimization that have a direct impact on your company’s bottom line.
How You Will Learn
In this university-level course, attendees learn collaboratively alongside peers, industry speakers, and a member of the University of Washington faculty—exploring common challenges and studying real use cases (and in our project consulting option, applying learnings to their own data in real time). More than a generic series of tutorials, these courses give participants the tools and consulting necessary to provide actionable insights and immediate, hyper-relevant applications.
Concepts are introduced through illustrations, code samples, and guided labs. Case studies of a simulation of a factory, or surrogate model, along with real world datasets, provide a through-line for all courses in the series, which will help you to apply concepts and explore ways to optimize both a wide range of business processes and operations.
Actionable, Applied Content from the UW
These data science courses were custom-built in conjunction with University of Washington’s Chemical Engineering faculty to give working professionals advanced data science skills pertinent to their roles and needs. Python Foundations and Data Science Foundations are equivalent to University of Washington’s chemical engineering courses UW CHEM E 545 & 546, which were developed as part of a $3 million investment in creating unique graduate level coursework at the intersection of data science and engineering.
Dr. Wesley Beckner, GIX Data Science Instructor
Explore the Modules
Python Foundations
A high-impact fundamentals course that gives you the ability to create custom tools in Python. No prior coding experience necessary.
Data Science Foundations
Discover the tenets of machine learning and create your first models in our foundational data science course.
General Applications of Neural Networks
Apply neural networks to solve real world problems within computer vision, natural language processing, and beyond.
Data Science Workshops
Sign up for professional one-day workshops in data science.