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Data Science for Business

This intensive course is designed for managers who want a better grasp of data science, AI, and machine learning to inform decisionsbusiness strategies, and interactions with data science professionals and consultants. 

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Improve Business Outcomes with Data

Massive amounts of data are now generated in all areas of business, but a new skillset and mindset are required to transform these raw numbers into real-world, bottom line results. Rather than simply using data as a reporting tool for what has already happened, learn how to harness data to predict outcomes and uncover actionable insights that drive you and your organization to a more successful future.

In this course you will learn the fundamentals of data science, AI and machine learning—and their business applications. You will learn how to wield data to inform decisions and strategies, get the most out of your data scientists and consultants, and leverage the power of machine learning to impact the bottom line. 

Learn How to:

Cultivate a data-driven approach to business strategies
Model processes and predict outcomes
Evaluate performance of machine learning frameworks
Determine the real (versus hyped) potential of machine learning and AI
Speak the language of data science teams and consultants

Who Should Enroll

This course is designed for managers, directors, and others interested in developing a deep working knowledge of data science methods and applications, so you can develop data-driven strategies for your business and answer key questions when tackling business challenges: Can data science methods help with this? How can I get the most out of my data science teams or consultants? How should I evaluate their recommendations? And more. 

Prerequisites:

Exercises are scaffolded to provide an understanding of the concepts and tools of data scientists without the need to code from scratch. To get the most out of the course, a working knowledge of Python and familiarity with the Python data analysis stack (Pandas, NumPy, Matplotlib, and SciPy) is recommended. Those wishing to refresh their skills or develop this familiarity may consider taking the self-paced tutorial available at Kaggle or the first course in the Data Science for Engineers seriesBuild Your Base, offered by GIX several times per year.

What You Will Learn

You will learn how to apply modern data science methods using large data sets and models. You will explore the opportunities and constraints of working with large data sets to improve automation, optimization, and strategic decision making that benefit operations and the business overall.

Topics include: 

  • Exploratory Data Analysis 
  • Model selection and regularization 
  • Supervised and unsupervised machine learning models 
  • Machine learning pipelines 
  • Business use cases for data science

Case studies introduce data science methods and concepts in a practical and accessible way. You will apply what you’re learning to a complex simulation, or surrogate model, of a business, and use a data set to conduct a margin analysis. Guest speakers from the University of Washington’s Foster School of Business and Seattle-based companies share real-world applications and lead discussions in how to use data to make smarter decisions, build better products, improve efficiency, automate tasks, model processes and predict outcomes.

Meet the Instructor

Dr. Wesley Beckner is a GIX faculty member, an instructor for the UW MS in Technology Innovation, a Data Science Advisor for the Pfaendtner Research Group, and partner at MFG Analytic, where he works with manufacturing clients to optimize their production processes using cloud-based tools. He received his Ph.D. in Chemical Engineering Data Science from the University of Washington and his B.S. in Chemical Engineering from the University of Texas at Austin. His consulting work inspired him to help organizations streamline their workflows and increase profit margins by training in-house employees to better understand and use data. In this course, he distills his knowledge as a chemical engineering data scientist to the most salient, practical information applicable to the practicing engineer. Read his full biography here.

Course Details & Registration

Format

The Data Science for Business course is 5 intensive days (8:00 a.m. - 4:00 p.m. PST) with a break for lunch (provided).

Instruction is a hybrid of in-person and virtual learning, with a fully virtual option for participants unable to attend in person. Enjoy a tour of the Steve Ballmer Building and see some of the creative work happening in the Prototyping Labs and its student makerspace.

(Note: We will follow all applicable COVID-19 protocols to ensure we can offer the course safely and in compliance with applicable state guidelines.)

Date

August 30 – September 3

Can't make these times?

Request a custom offering for your company or team

Price

$3750 ($3000 early bird through May 31, 2021)

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Dr. Beckner combines easy-to-follow explanations alongside visuals and active implementation of concepts followed by practical exercises to provide students of every learning style with an equal opportunity to absorb the material.

–DK, former student in the DSFE “Build Your Base” course

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