Course curriculum

  • 1

    Module 1: Introduction to Data Analytics

    • Defining Business Analytics

    • Introduction to Data Analytics

    • Descriptive Analytics

    • Descriptive Analytics

    • Diagnostic Analytics

    • Diagnostic Analytics

    • Predictive Analytics and Prescriptive Analytics

    • Predictive and Prescriptive Analytics
  • 2

    Module 2: Descriptive Statistics

    • Basic definitions

    • Basic Definitions

    • Measures of Location and Variability

    • Measures of Location and Variability

    • Other elements of Descriptive Statistics

    • Other Elements of Descriptive Statistics

    • Basic descriptive Statistics Charts and Graphs

    • Basic Descriptive Statistics Graphs

    • Basic Descriptive Statistics Report

    • Calculating the Interquartile Range

    • Identifying Outliers

    • Identifying Outliers

    • Creating Box Plots

    • Creating Histograms
  • 3

    Module 3: Linear Regression

    • Simple Linear Regression

    • Simple Linear Regression

    • Simple Linear Regression Exercise

    • Simple Linear Regression - Another Method

    • Simple Linear Regression - Trucking Exercise

    • Multiple Linear Regression

    • Multiple Linear Regression

    • Multiple Linear Regression - Trucking Exercise

    • Multiple Linear Regression - Coasters
  • 4

    Module 4: Time Series Analysis and Forecasting

    • Foreasting using Qualitative Methods

    • Forecasting and Qualitative Methods

    • Quantitative Forecasting Methods and Forecasting Accuracy

    • Forecasting using Quantitative Methods

    • Forecast Accuracy

    • Forecast Accuracy - Sales Example

    • Forecast Accuracy - Sales Example 2

    • Course Wrap Up!

Learning Outcomes:

By the end of the class the students will be familiar with concepts of:

This course will serve as an introduction to the use of Data Analytics in the workplace. By the end of the class, the students will be familiar with concepts that are essential to creating forecasts and measuring their accuracy, as well as how to use Microsoft Excel to conduct a wide range of analyses.

About the Professor:

Javier Leon

Javier Leon is a Ph.D. Candidate in Data Science. Certified Project Manager Professional, MBA, MS Business Intelligence and Analytics, MS Food Marketing, and a Qlik Ambassador. Javier is passionate about teaching. He has developed several courses for top Universities in the United States. Some of the areas in which he has developed courses include Business Intelligence, Business Analytics, Marketing, International Business, R Programming, Python, Supply Chain Management, Business Analysis, and Data Visualization.  ​ Javier has worked with some of the largest food and beverage companies in the world as a project manager, and in his role, he has led the efforts to develop thousands of dashboards, reflecting the progress of the company toward meeting its strategy through the use of Key Performance Indicators seen in interactive and powerful graphs, charts and tables.

Target Audience

  • New Qlik Sense Users

  • College Students

  • Business Intelligence Professionals

  • College Graduates

  • Project Managers

  • Entrepreneurs wanting to visualize their business performance

  • Business Analysts

  • IT Professionals

  • Professionals who want to use data for storytelling