Over the course of the past decade, the explosion of data has transformed nearly every industry
known to man. Whether it’s in marketing, healthcare, government, or activism -- the ability to translate
data into insights has quickly become a highly in-demand skill by all. The GW Data Analytics Boot
Camp is a part-time 24 week program that will empower you to gain the knowledge and skills to
conduct robust analytics on a host of real-world problems.
The program is designed to fit into your life, whether you’re employed or attending college full-time,
with convenient weekend and evening sessions.
The program is rigorous, fast-paced, and focused on the practical technical skills needed to solve
data problems. Throughout the course, you’ll be gaining proficiencies on a host of marketable
technologies like Excel, Python, JavaScript, SQL Databases, Tableau, and more. Plus, you’ll have an
impressive Professional Portfolio and the confidence you need to succeed in the data driven economy.
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Are you a creative, curious, and ambitious professional looking to join the data
revolution? If so--or if any of the following describes your situation--enrolling in our Data
Analytics Boot Camp could be a smart career move:
You are currently a professional doing work with data, but are looking to advance
your career by building technical skills.
You are a manager or professional in a business where data can be used to boost
your company’s bottom line.
You have interests in visualizing social, consumer, or popular trends.
You are looking to enter a new field in healthcare, government, or media and are
looking for a way to jump in.
You are a full-time student, hungry to learn more and expand your skill set.
Is This Program Right For You?
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You will graduate with skills in Data Visualization and Analytics, including*:
Advanced Excel
• Pivot Tables
• VBA Scripting
Fundamental Statistics
• Modeling
• Forecasting
Python Programming
• Python 3
• NumPy
• Pandas
• Matplotlib
• API Interactions
• Social Media Mining
Databases
• MySQL
• MongoD
• ETL
Front-End Web Visualization
• HTML
• CSS
• Bootstrap
• Dashboarding
• JavaScript Charting
• D3.js
• Geomapping with Leaflet.js
Business Intelligence Software
• Tableau
Advanced Topics
• Big Data Analytics with Hadoop
• Machine Learning
- Note: These topics are subject to change based on local market demand and the input of hiring partners.
The Skills You’ll Gain
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Building On The Basics
For those first entering the field of Data Analytics, knowing where to start can be
a daunting task. That’s why our curriculum is designed to provide you with a deep
foundation on the core technical skills needed to succeed in the field. Throughout the
program, expect to learn brand new skills and be challenged in completing difficult
“real-world” problems to demonstrate your new abilities. By the program’s end, you will
have a strong professional portfolio showcasing your work.
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Our graduates will be qualified for many different roles, including:
Data Analyst Data Engineer
Data Scientist Data Journalist
Business Analyst SQL Developer
Systems Engineer Database Administrator
Big Data Engineer Business Intelligence Analyst
Research Analyst Software Engineer
Real Projects, Real Jobs
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By the time you graduate, you can expect to be able to:
Employ statistical analysis to model, predict, and
forecast trends
Expertly build VBA scripts in Excel to automate tedious
manual processes
Use geographic data to create visually exciting,
interactive, and informative maps
Utilize real-world data sources to showcase social,
financial, and political phenomena
Create in-depth graphs, charts, and tables utilizing a
wide-variety of data-driven programming languages
and libraries
Create Python-based scripts to automate the cleanup,
re-structuring, and rendering of large, heterogeneous
datasets
Interact with RESTful APIs using Python Requests and
JSON parsing techniques
Use ETL process (Extract, Transform, Load) to transform
and consolidate data from multiple sources
Build custom interactive data visualizations using D3.js
and other JavaScript libraries
Write SQL commands to perform Create, Read,
Update, and Delete commands
Use advanced SQL and Mongo techniques to combine
multiple datasets into one so as to create even more
impressive and comprehensive databases
Create basic interactive websites and applications to
show your work to the entire world
Work with and lead small-scale teams in order to
create applications and visual datasets
Scrape information from web pages in order to collect
data from a wide-variety of online sources
Communicate and glean new business insights using
enterprise-grade tools like Tableau
Analyze social media trends using automated
programs
Work independently or in a group on complex datamining projects
Understand the basics of troubleshooting and
enhancing legacy code
What You Will Learn
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Course Structure
Over the course of 24 weeks, you’ll attend informative lectures and take part in a
variety of individual and team exercises, working independently and in groups, in
the classroom and at home. Homework assignments provide an opportunity to apply
what you’ve learned and build on it. The goal is to give you a comprehensive learning
experience and true insight into a “day in the life” of a data professional.
PORTFOLIO PROJECTS
Your portfolio signals to employers
that you are ready for primetime!
You’ll build a substantial portfolio
of projects that demonstrate your
abilities across a wide variety of
technologies.
PROJECT WORK
You’ll put classroom teaching into
practice individually and with a team
to work on timed in-class exercises
and projects.
DISCUSSION
Instructor-led discussions cover the
background, history, and use of a new
technology or concept.
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We’re Here To Help
As you move up the learning curve, you’re likely to have questions around many of the concepts
covered in class. We’re here to help—through in-person and virtual office hours, as well as a
dedicated #slack channel where you can get assistance from instructors, support staff and your
fellow students. All work is done via Github, so you can create issues directly on your own projects
for instructors to assist you in a truly asynchronous fashion. In addition to learning to code, you will
have access to career services that will help you prepare for technical roles after graduation such as:
Career Content and Practice Sessions
Database of Customizable Tools and Templates
• Multiple Technical Resume Templates
• Github Best Practices
• Guidelines To Building A Portfolio
• Creating an Elevator Pitch
• Developing a Bio
Online Career Events With Industry Professionals
Soft Skills Training
One-on-One Career Coaching
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Building Your Portfolio
It’s a fact: Companies care about what you can do, not what you say you can do. For that
reason, our curriculum teaches you how to put what you’ve learned to work on real-world
data projects, ranging from visualizing bike sharing data in New York City to mapping
worldwide earthquakes in real-time.
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Bank Deserts
Social economists have long noted a trend that in geographic areas with higher poverty rates, there is often a dearth of reputable
banks or financial services. The shortage leads to higher rates of financial victimization in these areas. But how could we show this
trend using data? In this activity, you’ll learn how to combine data from the US Census, Google Maps, and Google Places to visualize
the relationship between various socioeconomic factors and the number of banks in a given zip code.
Earthquake History
Data isn’t just about finance and numbers. It can also be used for good as well. In this activity, you will create an interactive
visualization of historic earthquakes over time using Leaflet.js, a popular JavaScript geo-mapping library. Your final application will
provide a near-live feed of global earthquakes and their relative magnitudes.
Skills Needed
• HTML
• CSS
• Javascript
• Leaflet.js
• APIs
• JSON
Skills Needed
• Python
• Pandas
• Google Maps
• Google Places
• Matplotlib
• APIs
Objectives
• Harness the power of APIs and JSON to gather
earthquake data from USGS datasets
• Utilize Leaflet.js library to create visually compelling,
animated maps
• Embed the created map onto a live web page using
HTML and CSS
Objectives
• Utilize the Python Requests library to make hundreds of
API calls to the US Census and Google Maps datasets
• Utilize the Python pandas library to organize the retrieved
information by zip code and socioeconomic factors
• Build scatter plots to easily communicate the Banking
Desert phenomena
Building Your Portfolio
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Web Scraping Application
Sometimes, the data we need is just out of reach. Whether it’s a social media website that is guarding it’s information, a government
agency that has poorly organized records, or a cookbook website filled with secret recipes -- data isn’t always accessible by external
applications. This is where data scraping comes in. Utilizing Python libraries like Beautiful Soup, you will learn to convert data straight
from raw HTML into a queryable and storable form, opening up troves of data for your future applications.
Data Journalism and D3
In this activity, you will be taking on the role of a data visualization specialist working for a major metropolitan newspaper. Your editor
wants to run a series of feature stories about the health risks facing particular demographics of the United States. Using the latest
information from two government databases and the D3 JavaScript library, you will be creating charts and interactive graphs for this
important news article.
Skills Used
• JavaScript & D3 Library
• HTML/CSS
• Bootstrap
• Microsoft Excel
Portfolio continued…
Skills Needed
• Python
• Beautiful Soup
• HTML
• CSS
• MongoDB
Objectives
• Scrape your favorite social media website for otherwise
inaccessible data
• Parse through the retrieved information and store it into a
MongoDB database
• Create new representations of the data using
HTML and CSS
Objectives
• Collect data from two government databases
• Store the data within a series of .CSV files
• Create fully interactive graphs that alter with button-clicks
• Place all of your information into a mobile-responsive
webpage
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Game Studio Analytics
Congratulations! You have landed a job as the Lead Analyst for an independent game company and for your first assignment you
have been given the difficult task of analyzing data and creating a report for their latest smash hit release. You will be using the
Python Pandas Library and Jupyter Notebook to create demographic and other financial reports.
Skills Used
• Python
• Jupyter Notebook
• Pandas Library
Objectives
• Use Python and the Pandas library to create a report
containing a vast amount of data
• Make the data viewable using Jupyter Notebook
• Find, analyze, and write up descriptions of observable
trends in the data
Classifying Yelp Reviews
A Nielsen report concluded that 82% of visitors to Yelp intended to make a purchase, so it’s no surprise that companies take online
customer reviews and ratings seriously. In this section of the course, you’ll build an application that can analyze reviews, and tell
you through Natural Language Processing whether it’s negative or positive. This means you don’t have to have a human read every
review that gets posted and respond accordingly. You can instead have a machine flag negative reviews for you so you can trigger an
action like outreach and more.
Skills Needed
• PySpark
• Machine Learning
• Natural Language Processing
Objectives
• Perform Natural Language Processing with PySpark-ML
• Establish a big data processing pipeline to clean and
process data
• Train and validate a Naive Bayes machine learning model
that can make predictions from customer reviews
Portfolio continued…
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Module Description What You’ll Learn
Module 1:
Excel Crash Course
Learn to do more with Microsoft Excel! In this module
we’ll be covering advanced topics like statistical
modelling, forecasting, and prediction; pivot tables,
and VBA scripting. You will even learn to model historic
stock trends -- and hopefully, learn to beat the market!
» Microsoft Excel
» VBA Script
» Statistics Modeling
Module 2:
Python Data Analytics
Gain a strong foothold in one of today’s fundamental
programming languages. In the course of this module,
you’ll gain deep proficiencies with core Python, data
analytic tools like NumPy, Pandas, Matplotlib, and
specific libraries for interacting with web data like
Requests and BeautifulSoup.
» Python
» APIs
» JSON
» NumPy
» Pandas
» Matplotlib
» Beautiful Soup
» Tweepy
Module 3:
Databases
Dive deep into the most prolific database languages:
SQL and NoSQL. Work with MySQL and MongoDB
to organize data into well-structured and easily
retrievable data formats. Work on a case study
to combine data from different sources into one
database.
» SQL
» NoSQL
» MySQL
» MongoDB
» ETL process
Module 4:
Web Visualization
(Weeks 13-19)
Building visualizations are of little benefit without a way
to communicate the message. In this module, you’ll be
learning the core technologies of web development
(HTML, CSS, and JavaScript) to create new and
interactive data visualizations that you can share with
everyone on the web!
» HTML
» CSS
» JavaScript
» AJAX
» D3
» Leaflet
Module 5:
Advanced Topics
By program’s end, you’ll be immersed in new and
in-demand topics like Tableau, Hadoop, and Machine
Learning.
» Tableau
» Hadoop
» Machine Learning
Module 6:
Final Project
Bring everything that you have learned in the class
altogether to create an impressive data-visualization
application with a small team! Get creative and come
up with something cool to show off to the whole world!
» Dreaming up
something fantastic
and understanding the
bounds of reasonable and
achievable
Course Curriculum By Module