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 decisions, business strategies, and interactions with data science professionals and consultants.
The Autumn 2021 section of DSFB (August 30 – September 3) is postponed and future dates will be announced soon.
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, you will 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:
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.
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 series, Build 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.
- 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 Instructors
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. Read his full biography here.
Dr. Suresh Kotha is professor of Management and outgoing chair of the Department of Management and Organization at the UW Foster School of Business, where he serves as research director of the Buerk Center for Entrepreneurship. Suresh is an awarding winning teacher who teaches courses in the Foster’s Executive MBA, Hybrid MBA, and other specialized masters programs. Prior to coming to Foster, he served on the faculty at the Stern School of Business, New York University. He has taught classes at the National University of Singapore, the Indian School of Business, GIBS Business School affiliated with the University of Pretoria, and the International University of Japan in Niigata, Japan. He teaches courses on competitive strategy, technology and innovation, and entrepreneurship. His research interests are in competitive strategy, corporate entrepreneurship, and technology entrepreneurship, and he is among the top 0.9% of highly cited researchers overall by a recent Stanford University Study. He has served on multiple editorial boards of top tier academic journals including the Academy of Management Journal, the Journal of Business Venturing, and the Strategic Management Journal. Read his full biography here.
Dr. Scott J. Reynolds is Professor of Business Ethics, the Weyerhaeuser Endowed Faculty Fellow, and incoming chair of the Department of Management and Organization at the UW Foster School of Business. He teaches courses on Ethical Leadership in UW’s MBA programs and his research includes ethical decision making and corporate social responsibility. Recently named Professor of the Year, Scott relies on readings, cases, and discussions to help others to identify and resolve individual, managerial and organizational issues with moral content. Read his full biography here.
Dr. Michael R. Wagner is Associate Professor of Operations Management and the Neal and Jan Dempsey Endowed Faculty Fellow at the UW’s Foster School of Business. He is also an Amazon Scholar. At the UW, Mike teaches courses in business analytics and tools for big data, operations management, models for managerial decision making, and mathematical programming. His areas of research and expertise include crowdsourcing, manufacturing management, operations management, operations research, project management, and supply chain management. He has consulted with organizations ranging from Amazon and Microsoft, to the United States Coast Guard. Read his full biography here.
Dr. Hema Yoganarasimhan is a Professor of Marketing at the University of Washington’s Foster School of Business and a leading expert in quantitative marketing. She also holds affiliate appointments in Computer Science and Engineering, Economics, and the Center for Statistics in the Social Sciences. Hema’s research brings together large-scale marketing data, economic theory, and econometric and machine learning tools to help firms optimize and automate their marketing decisions. She teaches courses in analytics for marketing decisions, digital marketing, and dynamic structural models in marketing. Her recent work focuses creative yet technically viable solutions to the challenges that businesses face in today’s world – how to target ads at scale using personalized user history, how to quantify the optimal level of targeting from a platform’s perspective, and methods to personalize search rankings in online platforms in real time. Read her full biography here.
Course Details & Registration
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.)
The Autumn 2021 section of DSFB (August 30 - September 3) is postponed and future dates will be announced soon.
For information on future offerings of this course, complete the Stay Updated form below and select Data Science For Business as your interest area.
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