Comprehensive course analysis
About the course
Machine Learning, Artificial Intelligence, Deep Learning, and Business Analytics are just a few of the terms you might encounter in the world of data science. Moreover, this terminology increasingly finds its way into our everyday lives, as well as the business world. Some fluency in the language of data is now a prerequisite for business success.
But there are caveats. Data will never tell you “what to do.” Numbers don’t take a position—they’re just information for us to interpret. Similarly, the tools of statistics and data science don’t tell you how to use them. Many great mishaps in data science, missed opportunities, and intentional misleads have been the result of misapplied tools and bad data interpretation. This program presents several foundations for evaluating quantitative information, and provides pragmatic approaches for using data -- for good.
*Part 1: Distinguishing the Truth from the Lies *
We begin with a critical data thinking framework as our foundation for objectively inspecting the way data are presented and improving data-based decision-making skills.
Part 2: Data-driven Decision Making
How do you use data to make better decisions? This session uses real-life examples and activity-based/role-play exercises to improve risk assessment abilities, situation analysis, and strategic decision-making skills.
*Part 3: Demystifying Data Science *
Provides a straightforward framework for understanding how data mining, machine learning, and artificial intelligence fit together, and how your organization might better use data science to improve business operations.
*Part 4: Quant IQ – Integrating what we’ve learned *
Knowing the language is integral to operating in a foreign country. Data science is no different. Using the knowledge built in previous sessions, this session develops the capability to be conversant with data scientists and analysts, as well as the ability to ask critical questions of data-driven analysis and presentations.
- Big Data: Questions we “could ask” vs. “should ask”
- Determining what you need to know from your data
- How data is often misinterpreted or misrepresented
- Strategic decision making, situation analysis, and scenario planning
- Values-based, data-driven decision-making
- How, when, and why machine learning, data-mining, and AI are used
- Interrogating data analysis, and asking penetrating questions
- The role of situation and context in flexing the data
- Enable critical thinking about data use and interpretation, and improve your ability to distinguish appropriate vs inappropriate use of analytics
- Provide a structure that helps non-specialists better understand modern data science and the potential implications for their organization’s business strategy
- Show you how to use analytics to make better decisions
- Help you see the “big picture”, and think strategically about data, and data science
Read more about Business Analytics
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.