# Data Analytics Foundations

Canonical URL: <https://www.creativelive.com/classes/data-analytics-foundations>

## Overview

This beginner-friendly course introduces the core concepts of data analytics, from descriptive and inferential statistics to data distribution and modeling techniques. You will explore how organizations use predictive and prescriptive analytics to support decision-making, gain insight into the tools and methods applied across industries, and understand the growing role of big data in today's business landscape.

## What you'll learn

- Understand core statistical concepts such as measures of central tendency, data dispersion, and the normal distribution
- Explore descriptive and inferential statistics, including probability distributions such as binomial and Poisson
- Learn to analyze and forecast data using correlation, linear regression, and multiple regression models
- Apply predictive analytics using tools such as trendlines, moving averages, and scenario modeling
- Create clear data visualizations with charts, histograms, icon sets, color scales, sparklines, and pivot tables
- Discover prescriptive analytics methods like Solver and linear programming to support optimized 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

## Schedule
- Jun 16, 2026 – Jun 25, 2026 — Live Online
- Jul 13, 2026 – Jul 14, 2026 — Live Online
- Aug 31, 2026 – Sep 1, 2026 — Live Online
- Sep 29, 2026 – Oct 8, 2026 — Live Online
- Oct 18, 2026 – Oct 25, 2026 — Live Online
- Oct 19, 2026 – Oct 20, 2026 — Live Online
- Nov 16, 2026 – Nov 17, 2026 — Live Online

## Pricing

**Tuition:** $595