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Data Analytics Courses

Data analytics and data science are popular terms, and skills in these areas are in great demand.  But what do these terms mean?  Below is an overview and a listing of related courses. For information about our certificate programs in data science and analytics, click here. →Test Yourself Take a 10-question quiz on analytics Data PrepContinue reading “Data Analytics Courses”

Latin hypercube

In Monte Carlo sampling for simulation problems, random values are generated from a probability distribution deemed appropriate for a given scenario (uniform, poisson, exponential, etc.).  In simple random sampling, each potential random value within the probability distribution has an equal value of being selected. Just due to the vagaries of random chance, clusters of similarContinue reading “Latin hypercube”

Oct 14: Statistics in Practice

This week we look at several ways to fool yourself, statistically – variants of the “Gambler’s Fallacy.” Gambling is all about accurately assessing risk, so, naturally, our featured course is: Nov 15 – Dec 13: Risk Simulation and Queuing See you in class! – Peter Bruce, Chief Academic Officer, Author, Instructor, and Founder The Institute forContinue reading “Oct 14: Statistics in Practice”

Regularize

The art of statistics and data science lies, in part, in taking a real-world problem and converting it into a well-defined quantitative problem amenable to useful solution. At the technical end of things lies regularization. In data science this involves various methods of simplifying models, to minimize overfitting and better reveal underlying phenomena. Some examplesContinue reading “Regularize”

Machine Learning and Human Bias

Does better AI offer the hope of prejudice-free decision-making?  Ironically, the reverse might be true, especially with the advent of deep learning.   Bias in hiring is one area where private companies move with great care, since there are thickets of laws and regulations in most countries governing bias in employment.  The total cost of recruiting,Continue reading “Machine Learning and Human Bias”