Linda Nozick is Professor and Director of Civil and Environmental Engineering at Cornell University. She is co-founder and a past director of the College Program in Systems Engineering and has been the recipient of several awards, including a CAREER award from the National Science Foundation and a Presidential Early Career Award for Scientists and Engineers from President Clinton for “the development of innovative solutions to problems associated with the transportation of hazardous waste.” Dr. Nozick has authored over 60 peer-reviewed publications, many focused on transportation, the movement of hazardous materials, and the modeling of critical infrastructure systems. She has been an associate editor for Naval Research Logistics and a member of the editorial board of Transportation Research Part A. Dr. Nozick has served on two National Academy Committees to advise the U.S. Department of Energy on renewal of their infrastructure. During the 1998-1999 academic year, she was a Visiting Associate Professor in the Operations Research Department at the Naval Postgraduate School in Monterey, California. Dr. Nozick holds a B.S. in Systems Analysis and Engineering from the George Washington University and an MSE and Ph.D. in Systems Engineering from the University of Pennsylvania.
By some estimates, 90% of the data that has ever existed has been created in the last two years. This is a staggering figure and has given rise to new challenges and opportunities in almost every industry: what kind of data do you need to collect to compete, and how can you make sense of it once you have collected it? As technology evolves and the volume of data increases, how can you make the best use of all this information? How can you use the data to help drive your decision-making? How can you make data work for you? How can you ensure your data accurately reflects the population in which you're interested?
In this course, you will determine the types of engineering and business questions you can answer, the kinds of problems you can solve, and the decisions you can make, all through using data analytics. You will explore best practices for collecting information so that you can make informed predictions, develop insights, and better inform organizational decision-making. You will see real-world examples that demonstrate how those tools work. Additionally, you will have a chance to apply some of the concepts to your own work. You will explore best practices for sampling and examine how different types of sampling are each suited for different situations. Finally, you will see real-world examples that demonstrate how those tools work and have a chance to practice sampling techniques in some case study scenarios.
Key Course Takeaways
- Explore how big data relates to your industry and can transform your business
- Identify best practices for sampling and how bias can affect sampling
- Compare advantages and disadvantages of measurement methods
- Examine types of decision-making based on model data, insights, and outputs
- Construct confidence intervals for sample means of randomly sampled data
- Apply sampling techniques to estimate the mean, approximate the number of samples, and construct a 90% confidence interval
How It Works
Who Should Enroll
- Current and aspiring data scientists
- Technical managers