Data Science for Business
Move beyond the spreadsheet
Designed for managers, this Harvard Online course provides a hands-on approach for demystifying the data science ecosystem and making you a more conscientious consumer of information.
What You'll Learn
There is more data available to businesses and organizations today than ever before, offering the potential to quickly and efficiently identify and reach desired business goals and outcomes. What is the best way to access and use this data to help develop business solutions and make decisions? What is data-driven decision making, and how can a better understanding and use of data impact your business or organization?
Data is only as useful as the insights you can collect from it. As a business professional, you can help realize the full potential of your data by building the skills that will help you effectively understand, visualize, and analyze the data available to you.
Data Science for Business will help you appreciate the full benefits of data-driven decision making and teach you the business analytics tools and techniques you need to effectively build better business solutions and become a stronger manager.
Through real-life case studies and hands-on exercises, you will understand how experts from across industries used data to answer some of their biggest business questions, and:
- Build a framework that will support data-driven decision making in your organization.
- Identify trends in data that lead to hypotheses and insights.
- Catch data mistakes or missing components.
- Communicate and work with data analysts and scientists to better lead your team to long-term success.
By the end of this course, you will be prepared to harness data to help you reach your business goals.
Start making decisions with data in Data Science for Business.
- Break away from the spreadsheet by developing a foundational understanding of data science tools, processes, and models.
- Use business analytics and data science to make better decisions that lead to organizational success.
- Identify and avoid common mistakes while interpreting datasets, metrics, and visualizations.
- Create a data-driven framework for your organization and yourself; develop hypotheses and insights; and identify data and missing components.
- Speak a common language with data scientist teams to uncover actionable recommendations and findings.
- Put key techniques into practice such as data curation, regression models, prediction and analyses, and visualization.
- Read basic code in order to comprehend the syntax that informs data requests.
- Assess applicable methodologies in statistics, data analytics, and data science by hearing from real-world examples across industries, topics, and business challenges.
Yael Grushka-Cockayne is the Altec Styslinger Foundation Bicentennial Chair in Business Administration and Senior Associate Dean for Professional Degree Programs at the University of Virginia Darden School of Business and was formerly a Visiting Professor of Business Administration at Harvard Business School and Professor of Business Administration. Her research and teaching activities focus on data science, forecasting, project management, and behavioral decision-making. Her research is published in numerous academic and professional journals, and she is a regular speaker at international conferences in the areas of decision analysis, project management, and management science. In 2014, Grushka-Cockayne was named one of "21 Thought-Leader Professors" in Data Science.
Real World Case Studies
Affiliations are listed for identification purposes only.
Temple Fennell is the CEO and founder of ATO Pictures, LLC, a motion pictures finance, production and distribution company that provides U.S. distribution and production funding. Step into Hollywood and explore how this company used data to identify box office success in the entertainment industry.
Paul Matherne, MD
Paul Matherne, MD is a pediatric cardiologist and the associate chief medical officer for UVA Children's. He will demonstrate how even preemies can benefit from data science in the case of a children’s hospital’s bid to expand the NICU.
Susanna Gallani is an Assistant Professor Of Business Administration at Harvard Business School. She used data to determine if employees were fully engaged at work and will analyze how data can be used to fine-tune incentive strategies.
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