Data Analytics Program Curriculum

A learning experience that’s as rigorous and in sync with the industry as it is suited to beginners and upskillers alike.

Curriculum overview

Part-time
Flexible
Full-time
Intro to Data Analytics
approx.
1 month
Data Analytics Immersion
approx.
7 months
Specialization
approx.
2 months
Intro to Data Analytics
approx.
0.5 months - 1 month
Data Analytics Immersion
approx.
3.5 - 7 months
Specialization
approx.
1 - 2 months
Intro to Data Analytics
approx.
0.5 months
Data Analytics Immersion
approx.
3.5 months
Specialization
approx.
1 month
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Completion times are approximations based on the progress of our current students and graduates

Intro to Data Analytics
Data Immersion
Specialization

This course will take you through ten tasks leading up to one main project: a descriptive analysis of a video game data set to inform product development and sale strategies.

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1.1 Data Analytics in Practice

Learn what data analysts do and get ready to kick off your own analysis.

1.2 Introduction to Excel

Get to know Excel and learn how to sort, filter, format, organize, and visualize data.

1.3 Understanding Your Data Set

Analyze and describe your data set, then identify sources of bias.

1.4 Cleaning Your Data

Identify errors in your data and learn how to clean your data and minimize issues.

1.5 Grouping & Summarizing Your Data

Create and manipulate pivot tables and learn more advanced Excel skills.

1.6 Introduction to Analytical Methods

Explore different approaches to data analytics and the role of statistics.

1.7 Conducting a Descriptive Analysis

Conduct a descriptive analysis by applying statistical methods in Excel.

1.8 Developing Insights

Learn how to form hypotheses about data sets, and to generate useful insights.

1.9 Visualizing Data Insights

Build helpful visualizations of your data to present findings to stakeholders.

1.10 Storytelling with Data

Learn to present the results of your analysis in compelling ways.

Immerse yourself into the mindset, processes, and tools that data professionals use every day. You’ll complete a total of six projects (achievements) consisting of several tasks each.

curriculum curriculum-box heading image
Achievement 1
Achievement 2
Achievement 3
Achievement 4
Achievement 5
Achievement 6
Preparing & Analyzing Data

Learn how to interpret business requirements to guide your data analysis and begin developing and designing your data project. Here’s what you’ll learn:

A Brief History of Data Analytics

Starting with Requirements

Designing a Data Research Project

Sourcing the Right Data

Data Profiling & Integrity

Data Quality Measures

Data Transformation & Integration

Conducting Statistical Analyses

Statistical Hypothesis Testing

Consolidating Analytical Insights

Data Visualization & Storytelling

Explore the different types of data visualization and what they can be used for, as well as some best practices to keep your visualizations accessible and easily interpretable.

Intro to Data Visualization

Visual Design Basics & Tableau

Comparison & Composition Charts

Temporal Visualizations & Forecasting

Statistical Visualizations: Histograms & Box Plots

Statistical Visualizations: Scatterplots & Bubble Charts

Spatial Analysis

Textual Analysis

Storytelling with Data Presentations

Presenting Findings to Stakeholders

Databases & SQL for Analysts

Develop database-querying skills while mastering SQL, the industry-standard language for performing these tasks in the real world.

Intro to Relational Databases

Data Storage & Structure

SQL for Data Analysts

Database Querying in SQL

Filtering Data

Summarizing & Cleaning Data in SQL

Joining Tables of Data

Performing Subqueries

Common Table Expressions

Presenting SQL Results

Python Fundamentals for Data Analysts

Get hands-on with Python—the go-to language used by data analysts to conduct advanced analyses. Here’s what you’ll learn:

Introduction to Programming for Data Analysts

Jupyter Fundamentals & Python Data Types

Introduction to Pandas

Data Wrangling & Subsetting

Data Consistency Checks

Combining & Exporting Data

Deriving New Variables

Grouping Data & Aggregating Variables

Intro to Data Visualization with Python

Coding Etiquette & Excel Reporting

Data Ethics & Applied Analytics

Learn how to identify and address data bias, data privacy, and data security. You’ll also explore big data analysis, machine learning, and data mining.

Intro to Big Data

Data Ethics: Data Bias

Data Ethics: Security & Privacy

Intro to Data Mining

Intro to Predictive Analysis

Time Series Analysis & Forecasting

Using GitHub as an Analyst

Preparing a Data Analytics Portfolio

Advanced Analytics & Dashboard Design

Complete an analysis project using data of your choosing, and build on your advanced analytics skills by taking a dive into machine learning and regression analysis.

Sourcing Open Data

Exploring Relationships

Geographical Visualizations with Python

Supervised Machine Learning: Regression

Unsupervised Machine Learning: Clustering

Sourcing & Analyzing Time Series Data

Creating Data Dashboards

To further develop your expertise, you’ll choose one of two specialization course options: Machine Learning with Python or Data Visualizations with Python.

curriculum curriculum-box heading image
Data Visualizations with Python

Achievement 1

Achievement 2

Machine Learning with Python

Achievement 1

Achievement 2

Network Visualizations and Natural Language Processing with Python

Learn how to create network visualizations and identify the relationships between different elements of data.

Intro to Freelance and Python Tools

Setting Up the Python Workspace

Virtual Environment in Python

Accessing Web Data with Data Scraping

Text Mining

Intro to NLP and Network Analysis

Creating Network Visualizations

Dashboards with Python

Learn about the intricate functionalities and settings of Python’s core visualization libraries.

Tools for Creating Dashboards

Project Planning and Sourcing Web Data with an API

Fundamentals of Visualization Libraries Part 1

Fundamentals of Visualization Libraries Part 2

Advanced Geospatial Plotting

Creating a Python Dashboard

Refining and Presenting a Dashboard

Basics of Machine Learning for Analysts

Dive into ethics, start preparing your data for supervised and unsupervised learning, and look into optimization algorithms.

The History and Tools of Machine Learning

Ethics and Direction of Machine Learning Programs

Optimization in Relation to Problem-Solving

Supervised Learning Algorithms Part 1

Supervised Learning Algorithms Part 2

Presenting Machine Learning Results

Real-World Applications of Machine Learning

Look into more complex machine learning concepts, as well as unsupervised learning, deep learning, and visual data.

Unsupervised Learning Algorithms

Complex Machine Learning Models and Keras Part 1

Complex Machine Learning Models and Keras Part 2

Evaluating Hyperparameters

Visual Applications of Machine Learning

Presenting Your Final Results

Intro to Data Analytics

This course will take you through ten tasks leading up to one main project: a descriptive analysis of a video game data set to inform product development and sale strategies.

1.1 Data Analytics in Practice

1.2 Introduction to Excel

1.3 Understanding Your Data Set

1.4 Cleaning Your Data

1.5 Grouping & Summarizing Your Data

1.6 Introduction to Analytical Methods

1.7 Conducting a Descriptive Analysis

1.8 Developing Insights

1.9 Visualizing Data Insights

1.10 Storytelling with Data

Data Immersion

Immerse yourself into the mindset, processes, and tools that data professionals use every day. You’ll complete a total of six projects (achievements) consisting of several tasks each.

Specialization

To further develop your expertise, you’ll choose one of two specialization course options: Machine Learning with Python or Data Visualizations with Python.

Data Visualizations with Python

You’ll process data, and build polished visualizations and dashboards with Python for an academic research organization and a bike-sharing company

Machine Learning with Python

You’ll use machine learning to make long-term predictions about climate change for certain types of populations around the globe.

about ux

Built on proven learning theories and industry expertise

Dive into a comprehensive and varied learning experience designed to take you from beginner to Data Analytics pro.

Each course is packed with reading materials, supporting audio learning options, and more.

Our instructional designers work hand-in-hand with seasoned experts in the field to keep the curriculum rooted in proven learning theories, and in-sync with the latest industry practices.

Graduate portfolios

View some of the incredible work our students completed during the Data Analytics Program

Create your portfolio with industry-standard tools

Data Analysis Tools

Where needed, we’ve partnered up with industry-standard tool providers to make sure you have access to the tools you’ll likely use in your new career, although most of the tools you’ll encounter in this program are free to use. The program is continuously benchmarked to ensure you’re learning the tools you’ll be most likely to encounter in your new career.

What our graduates have to say

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