10-Week Part-Time Or 1-Week Accelerated Course

Talk to Admissions +612 8318 2912
Communicate with stakeholders

The Big Picture

Confidently make — and defend — critical decisions using the results of your data analysis.

Collect, clean, and analyze data

Skills, Tools, & Strategies

Use Excel, SQL, and Tableau to spot trends and drive business decisions with real‐world data.

Create data visualizations

Analytics in Practice

Share your insights and tell compelling stories using data visualizations and dashboards.

Meet your support team

Our educational excellence is a community effort. When you learn at GA, you can always rely on an in-house team of experts to provide guidance and support, whenever you need it.

  • instructor


    Learn industry-grade frameworks, tools, vocabulary, and best practices from a teacher whose daily work involves using them expertly.

  • teaching assistant

    Teaching Assistants

    Taking on new material isn’t always easy. Through office hours and other channels, our TAs are here to provide you with answers, tips, and more.

  • producer

    Course Producers

    Our alumni love their Course Producers, who kept them motivated throughout the course. You can reach out to yours for support anytime.

See What You’ll Learn

Unit 1: Exploring Data with Excel

Understanding the Value of Data

  • Explore the value of data.
  • Work your way through the data analytics workflow.
  • Unlock the power of Microsoft Excel to utilize its analytical tools — no matter your experience level.

Preparing Data in Excel

  • Learn best practices for collecting and cleaning data in Excel to ensure accurate analysis results.
  • Manipulate real-world data sets using advanced nested logical functions (IF, OR, and AND).

Cleaning Data in Excel

  • Clean large, unruly data sets by removing duplicate rows and performing text manipulations.
  • Transform and rearrange columns and rows within spreadsheets to prepare data for analysis.
  • Gain insight into data analysis by manipulating data formats.

Referencing Data in Excel

  • Use the VLOOKUP and HLOOKUP functions to manipulate data sets.
  • Look up values in other tables using the functions INDEX and MATCH.

Aggregating Data in Excel

  • Summarize data using pivot tables.
  • Execute Excel aggregation commands (SUM, AVERAGE, COUNT, etc.) and their conditional variants (COUNTIF, COUNTBLANKS, etc.) to summarize data sets.

Visualizing Data in Excel

  • Derive insights from data by highlighting cells based on conditionals.
  • Use scatter plots, bar graphs, and histograms to visualize data.
  • Explore color theory and how it applies to data visualization.
  • Build your own data dashboard using industry best practices.
  • Apply visual design principles to your dashboard to present your findings clearly.

Applying Statistics for Data Analysis

  • Understand the value of descriptive and inferential statistics.
  • Learn to describe data and identify outliers using its mean, median, mode, range, and variance.
  • Make predictions about larger populations using sample data.

Building Data Narratives

  • Learn best practices for describing analysis techniques.
  • Communicate insights and implications for stakeholders.
  • Deliver short, effective presentations sharing your findings.
  • Provide context for your audience by identifying and presenting the salient statistics.

Unit 2: Managing Data with SQL

Understanding the Fundamentals of Databases and SQL

  • Practice the fundamentals of Structured Query Language (SQL).
  • Use database schema to design appropriate queries using SQL.
  • Explore the differences between relational databases (tabular data storage) and document-based databases (key-value pairs).

Querying Large Databases in SQL

  • Collect data using standard SQL commands (Create, Update, Truncate, etc.).
  • Filter data using advanced SQL commands (Where, Group By, Having, Order By, Limit).
  • Obtain data by creating relationships between tables using Joins.
  • Gather filtered data using SQL Boolean operators (AND and OR) and SQL conditional operators (=,!=,>,<,IN, and BETWEEN).

Aggregating Data in SQL

  • Create relationships between tables and data points (including has_many and many_to_many) using Join tables.
  • Write Boolean statements with SQL conditional operators (=,!=,>,<,IN, and BETWEEN) and null functions (“IS NULL,” “IS NOT NULL,” and “NVL”).
  • Clean data using SQL mathematical functions (ABS, SIGN, MOD, etc.).
  • Summarize data sets by employing aggregation commands (“Sum,” “Average,” “Count,” etc.).
  • Determine data trends by applying aggregation methods.

Writing Efficient, Dynamic Queries

  • Use CASE statements to structure data and create new attributes.
  • Combine multiple subqueries into one using “WITH AS.”

Creating a Local Database

  • Create a local database using data sets you bring into the classroom.
  • Upload and export data using a local database.

Unit 3: Communicating Data Analysis with Tableau

Exploring the Fundamentals of Tableau

  • Get hands-on, practical experience navigating the Tableau software interface.
  • Connect your data to Tableau and identify the best ways to visualize and display your results.

Visualizing Data and Mapping in Tableau

  • Use bubble graphs to visualize data.
  • Display geocoded information for your data.

Designing Data Dashboards in Tableau

  • Contextualize analysis results by creating Tableau dashboards.
  • Incorporate charts and conditional formatting into your dashboard using supporting information specific to a particular data set.

Working with Data Across Excel, SQL, and Tableau

  • Understand the use of specific data analysis software.
  • Apply all the tools and skills you’ve acquired in Excel, SQL, and Tableau to analyze a data set from start to finish.

Final Project Presentations

  • Identify strengths and areas for improvement in your analytical skills with feedback from peers, instructors, and guest panelists.

Request a Detailed Syllabus

Get Syllabus

The goal of analysis is to find information in the data that’s going to help people make a better decision. This course is a powerful and accessible way for students to learn how to go from data to decisions.

Jim Byers / Business Intelligence Manager, HTC

Jim Byers, Business Intelligence Manager, HTC

Meet your instructors

Learn from skilled instructors with professional experience in the field.

Dave Bredesen

New York City

Dave Bredesen

Senior Product Manager,


Carey Anne Nadeau

Washington, D.C.

Carey Anne Nadeau

Founder and CEO,

Open Data Nation

Irene Rix


Irene Rix

Analytics Consultant, Founder,

Jim Byers


Jim Byers

Technical Program Manager - Big Data and Data Science Projects,


Roger Woodley

San Francisco

Roger Woodley

Senior Data Solutions Manager,

Cornerstone OnDemand

Learn In

Set as default location

Aug 20 – Oct 24

Except: Oct 1

Mon & Wed

6:30pm - 8:30pm

$4,500 AUD

Sep 22 – Oct 27


9:30am - 5:30pm

$4,500 AUD


Dec 15 – Feb 2

Except: Dec 29, Jan 5


10am - 6pm

$4,500 AUD

vdata analytics student working

Financing Options

Need payment assistance? Our financing options allow you to focus on your goals instead of the barriers that keep you from reaching them.

Let us figure out the best option for you.

⁶ Must be 18 years or older and an Australian citizen or permanent resident.

Financing options differ in each market and are only available to students accepted into our courses. Contact a local admissions officer for more info.

Get Answers

Have questions? We’ve got the answers. Get the details on how you can grow in this course.

  • Why is this course relevant today?

    Data is now an integral part of every business. To be successful in today’s business landscape, all companies need to learn how to leverage data to make critical business decisions. It is a requirement for every employee to know how to analyze data. In this course, you will learn how to use large amounts of data to help your company make those critical decisions about strategy.

  • What practical skill sets can I expect to have upon completion of the course?

    This course will teach you how to use large amounts of data to make business decisions. Using Excel and Sql, you will learn how to collect, clean and analyze data from multiple sources including the web, a local file and a relational database. Additionally, you will be able to use this analysis to make business decisions. In this course, you will practice with real world data sets and problems to contextualize how analytics fit into the business world.

  • How does this course differ from the Data Science course?

    Unlike Data Science, students can come to Analytics with little-to-no programming skills and learn how to apply analytic skills to solve real world business problems. In Data Science, students need to have experience with a programming language prior to taking the course.

  • Are there any prerequisites for the course?

    No, there are no prerequisites for the course.

Dig Deeper Into The Curriculum

By providing us with your email, you agree to the terms of our Privacy Policy and Terms of Service.

Speak with admissions about your options.

By providing us with your email, you agree to the terms of our Privacy Policy and Terms of Service.

Let’s keep you updated.

By providing us with your email, you agree to the terms of our Privacy Policy and Terms of Service.