# Data Analytics Foundations Course Online

Canonical URL: <https://vdci.edu/courses/data-analytics-foundations-course-online>

## Overview

This self-paced, beginner-friendly course is designed to give a clear picture of how data analytics works in practice, from initial data review through analysis and decision making. Rather than jumping straight into tools, it starts by explaining key ideas like data distributions, descriptive and inferential statistics, and how organizations use analytics to understand patterns, predict outcomes, and plan next steps. You’ll also explore how Big Data and modern analytics tools are shaping the way decisions are made across industries.

Hands-on exercises are used throughout the course to help you apply what you’re learning to realistic problems. You’ll practice working with statistical concepts such as probability distributions, correlation, and regression, then move into forecasting with trendlines, moving averages, and scenario analysis. The course also covers data visualization and prescriptive techniques, including charts, Pivot Tables, and optimization tools like Solver, so you can turn analysis into insights that support smarter decision making.

## Prerequisites

Students should feel comfortable using Excel at a basic level. Experience equal to our [Excel Level II: Intermediate](https://www.nobledesktop.com/classes/intermediate-excel-classes) class is strongly recommended, but not required.

## Curriculum

### Basic Data Analysis

- Measures of Central Tendency
- Measures of Position
- Measures of Dispersion
- The Normal Curve
- Descriptive Statistics

### Predictive Analytics I

- Forecasting
- Series Forecast

### Data Visualization I

- Charts
- Icon Sets
- Histograms
- Moving Average

### Predictive Analytics

- Correlation
- Regression - overview
- Regression - analysis
- Linear regression
- Multiple regression

### Probability

- Probability I
- Probability II
- Binomial Probability
- Poisson Probability

### Prescriptive Analytics I

- What If Analysis
- Data Table (3 variables)
- Scenario Manager
- Scenario Manager - Pivot

### Data Visualization II

- Sparklines
- Color Scales
- Drawing Shapes
- Pivot Tables
- Pivot Charts

### Prescriptive Analytics II

- Solver - overview
- Linear Programming
- The Solver model
- Non-Linear Programming
- Evolutionary Solver

## Instructors

### Garfield Stinvil — Instructor

Garfield is an experienced software trainer with over 16 years of real-world professional experience. He started as a data analyst with a Wall Street real estate investment company & continued working in the professional development department at New York Road Runners Organization. He enjoys bringing humor to whatever he teaches and loves conveying ideas in novel ways that help others learn more efficiently.

Since starting his professional training career in 2016, he has worked with several corporate clients including Adobe, HBO, Amazon, Yelp, Mitsubishi, WeWork, Michael Kors, Christian Dior, and Hermès. 

Outside of work, his hobbies include rescuing & archiving at-risk artistic online media using his database management skills.

### Colin Jaffe — Instructor

Colin Jaffe is a programmer, writer, and teacher with a passion for creative code, customizable computing environments, and simple puns. He loves teaching code, from the fundamentals of algorithmic thinking to the business logic and user flow of application building—he particularly enjoys teaching JavaScript, Python, API design, and front-end frameworks.

Colin has taught code to a diverse group of students since learning to code himself, including young men of color at All-Star Code, elementary school kids at The Coding Space, and marginalized groups at Pursuit.

Colin lives in Brooklyn with his wife, two kids, and many intricate board games.

### Brian McClain — Instructor

Brian McClain is an experienced instructor, curriculum developer, and web developer. Brian served as Director for a coding bootcamp, where he is now a lead instructor and course developer for both JavaScript and Python. He teaches Web Development, JavaScript, Python for Data Science, Machine Learning, and AI. He taught Python Data Science and Machine Learning as an Adjunct Professor of Computer Science at Westchester County College.

Brian is also an active industry professional in the field of generative AI app development. His website and iOS app, Artmink, provide appraisals of art and antiques from user-uploaded images.

## FAQ

### Who is the target audience for this course?

Participants with basic Excel skills who want to develop foundational data analytics and statistical modeling capabilities, including:

- Those working in or aiming for roles in business, marketing, operations, or analytics that require proficiency in descriptive and inferential statistics, forecasting, visualization, and basic predictive modeling techniques.
- College or graduate students in business, engineering, data science, economics, or related fields who want hands-on experience applying statistical concepts like regression, probability, and Solver to real-world problems using project-based training.
- Professionals across industries—such as operations, finance, or project management—looking to enhance decision-making skills by understanding how data informs strategic forecasting, modeling, and visualization workflows.

### Are there any additional fees or expenses?

There are no extra fees or taxes for our courses. The price you see on this page is the maximum you’ll pay us.

## Pricing

**Tuition:** $595