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Course Description

Important: It is recommended the AI Data Science courses are taken in the following order- 1 hour, 4 hour then 15 hour.

The AI Data Science package is made up of three courses: 

  • Quick Glance at Statistical Inference- 1 hour
  • Introduction to R- 4 hour
  • Artificial Intelligence in Applied Data Science- 15 hour
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Enroll Now - Select a section to enroll in
Section Title
Quick Glance at Statistical Inference- 1 hour
Section Schedule
Date and Time TBA
Course Fee(s)
1 hour non-credit $0.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
Description & Objectives:
  •  This course is asynchronous, meaning you can sign up any time throughout the year.
  •  In this course, we cover two fundamental elements in statistical inference: confidence interval and hypothesis testing. In many applications, we use an interval estimator instead of a point estimator. For example, an election poll tells us that candidate A receives 48% of support, +/- 1.5%, which indicates that the support rate for candidate A falls into the interval (46.5%, 49.5%) with a high probability. The interval estimator takes the uncertainty of sampling into account and implies the quality of the estimator. We will learn to construct and interpret confidence intervals and the associated confidence levels.
  •  In scientific research, investigators hypothesize about relationships among factors and perform tests on them. For example, a pharmaceutical company tests if a new drug is more effective in curing a disease compared to a placebo. Then a pair of hypotheses are created with the null hypothesis indicating that the new drug is no better than the placebo, and the alternative hypothesis indicating otherwise. Then experimental data are collected, and a test statistic is constructed. We will learn to read the information the test statistic conveys and reach a conclusion based on the inclusion.
    •  By the end of this course, students will be able to:
      •  Construct confidence intervals
      •  Conduct hypothesis testing
Section Title
Introduction to R- 4 hour
Section Schedule
Date and Time TBA
Course Fee(s)
Registration fee non-credit $249.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
Description & Objectives:
  •  It is recommended you complete the 1hr course before taking the 4hr course.
  •  This course is asynchronous, meaning you can sign up any time throughout the year.
  •  R is a statistical programming language that is widely used in data science. It includes tools that support classical and advanced statistical methods, numerical optimization, simulation, and visualization. R is an open-sourced platform that has a fast-growing and committed developer base that creates software packages for state-of-art methods. In this course, we will learn this rapidly developing programming language with Rstudio, a user-friendly and integrated development environment for R. We will cover the syntax and data structures of R, as well as its powerful tools for statistical summary and graphics.
  •  After successfully completing this course, you will earn .4 CEU as well as a certificate of completion.
    •  By the end of this course, students will be able to:
      •  Work with the basics of R syntax
      •  Conduct statistical summary and graphics using R
      •  Use R functions for statistical analysis
Required fields are indicated by .