# Data Analysis Package (Self-Paced)

Canonical URL: <https://www.graduateschool.edu/courses/data-analysis-package-self-paced>

## Overview

This package provides a progressive learning experience in data analysis, beginning with foundational concepts and advancing to intermediate analytical techniques used to evaluate, clean, interpret, and communicate data effectively. Participants explore how data is structured, sourced, governed, and transformed across organizational systems, including transactional systems, analytical systems, and external data environments. The program introduces core concepts such as data quality, privacy, governance, visualization, reporting tools, and Excel-based analysis, then builds into more advanced topics such as data discovery, transformation, pivot tables, descriptive statistics, correlation, sampling, and interpretation of analytical results. Participants also examine practical case studies and learn how data analysis supports business, audit, and operational decision making while considering regulatory requirements, ethical responsibilities, and appropriate use of artificial intelligence in analytical workflows. By completing this package, learners strengthen their ability to work confidently with data, identify patterns and anomalies, improve data reliability, and support evidence-based decisions in professional settings.

## What you'll learn

- Explain foundational data analysis concepts, including data structures, sources, systems, and governance principles.
- Assess datasets for quality, completeness, consistency, and analytical readiness.
- Prepare and transform data using Excel tools and functions to support accurate analysis.
- Apply visualization, reporting, and Excel-based analytical techniques to identify patterns, trends, and outliers.
- Interpret descriptive statistics and other analytical outputs to support evidence-based conclusions.
- Analyze business, audit, and operational datasets using practical methods such as pivot tables, sampling, duplicate detection, and anomaly analysis.
- Apply privacy, compliance, governance, and responsible AI practices when working with data in professional environments.

## Curriculum
1. **Data Analysis Basic Course (Self-Paced)**
2. **Data Analysis Intermediate Course (Self-Paced)**

## Pricing

**Tuition:** $1049