This page is an archive of content and course materials from the Commerce Data Academy, which was organized by the Commerce Data Service under the Economics and Statistics Administration. With the closure of the Commerce Data Service, the Academy does not have any planned future courses at this time. However, most of the course materials and recordings are available for viewing below.
The goal of the Commerce Data Academy (CDA) is to help educate and empower employees within the Department of Commerce to make data-driven decisions. We offer a variety of courses in state-of-the-art User Experience (UX)/User Interface (UI) Design, Software Engineering, and Data Science taught by expert instructors. We also have a leadership series that we recently started, which offers classes to upper- and senior-level management on data science and other related topics. Our in-residence program provides the most talented DOC employees with an opportunity to do a residency and work alongside the Commerce Data Service's (CDS) professional developers and data scientists.
Collaborators: General Assembly and Data Society
Past courses and materials
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Data Science Basics (3/14/16)
- Intro to Git and GitHub (3/21/16)
- Intro to Python (4/6/16)
- Intro to Design and Photoshop (4/19/16)
- Intro to R (5/2/16)
- Intro to Data Analysis with R (5/17/16)
- Data Storytelling with R (6/1/16)
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Data Wrangling with Pandas (6/13/16)
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Intro to Machine Learning (7/11/16)
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Intro to JavaScript (9/29/16)
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Intro to Design and Photoshop (10/13/16)
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Intro to Data Analysis (11/16/16)
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Deep Learning (1/10/17)
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Intro to User Experience Design (2/7/17)
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Cybersecurity for Managers: An Introduction to the NIST Cybersecurity Framework (3/7/17)
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Intro to Qualitative Data Collection (3/21/17)
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Intro to Git and GitHub (5/9/17)
Data Science Basics (3/14/16)
Instructor | Rebecca Bilbro |
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Description | What is data science? What kind of work do data scientists do? How are data products made? What is the data science pipeline? |
Topics covered |
Data Science, Data Products, Data Science Pipeline |
Software needed | None |
Slides | Download PDF (5 MB) |
Recording | Watch on YouTube (open captions) |
Intro to Git and GitHub (3/21/16)
Instructors | Rebecca Bilbro, Pri Oberoi, Sasan Bahadaran |
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Description | Learn to work effectively on a data team and never lose your project again! Introduction to version control using Git software and the GitHub website. |
Topics covered |
Version Control, Git, GitHub |
Software needed | Git GitHub Sublime or Atom.io Terminal or Powershell |
Slides | Download PDF (3.9 MB) |
Recording | Watch on YouTube (open captions) |
Additional resources | Step-by-step tutorial on GitHub |
Intro to Python (4/6/16)
Instructor | Star Ying |
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Description | Learn basic syntax and how to get up running with Python 2.7. |
Topics covered |
Basic Syntax, List Comprehension, Packages, Looping, Pickling, Package Installation, Package Importing |
Software needed | Git Sublime or Atom.io Terminal or Powershell |
Slides | Download PDF (200 KB) |
Recording | Watch on YouTube (open captions) |
Additional resources |
Python 2.7 |
Intro to Design and Photoshop (4/19/16)
Instructor | Radhika Bhatt |
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Description | Learn the basic principles and concepts of design such as color theory, typography, branding, user experience design, and mobile design. Practice what you learn in Photoshop, and walk away with a design by the end of the class. This is an introductory-level course. |
Topics covered |
Design Principles, Color Theory, Adobe Programs and their uses, PhotoShop, UX Design, Mobile Design |
Software needed | Adobe Photoshop: 30-day free trial available |
Slides | Download PDF (5 MB) |
Recording | Watch on YouTube (open captions) |
Intro to R (5/2/16)
Instructor | Star Ying |
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Description | Introductory course that covers basic R syntax, input and output, and basic statistical analysis. |
Topics covered |
RStudio, Basic Syntax, Data Frames, Loading and Writing Data, Summary Statistics, Regression |
Software needed | RStudio |
Slides | N/A |
Recording | Watch on YouTube (open captions) |
Intro to Data Analysis with R (5/17/16)
Instructor | Pri Oberoi |
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Description | Given a dataset online, use R to load the data, compute summary statistics, and investigate correlations. |
Topics covered |
Data Loading using R, Summary Statistics, Investigative Correlations |
Software needed | RStudio |
Slides | N/A |
Recording | Watch on YouTube (open captions) |
Additional resources | Step-by-step tutorial on GitHub |
Data Storytelling with R (6/1/16)
Instructors | Star Ying, Jeff Chen |
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Description | Overview of internal R data visualization tools as well as use of Shiny, Leaflet, and Plotly for interactive visualizations. |
Topics covered |
GGPlot2, Shiny, Plotly, Leaflet, RMarkDown, RStudio |
Software needed | Git GitHub Sublime or Atom.io Terminal or Powershell R and RStudio GGPlot2 Shiny Plotly Leaflet RMarkDown |
Slides | N/A |
Recording | Watch on YouTube (open captions) |
Additional resources | Step-by-step tutorial |
Data Wrangling with Pandas (6/13/16)
Instructors | Star Ying, Jeff Chen |
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Description | Overview of internal R data visualization tools as well as use of Shiny, Leaflet, and Plotly for interactive visualizations. |
Topics covered |
GGPlot2, Shiny, Plotly, Leaflet, RMarkDown, RStudio |
Software needed | Git GitHub Sublime or Atom.io Terminal or Powershell R and RStudio GGPlot2 Shiny Plotly Leaflet RMarkDown |
Slides | N/A |
Recording | Watch on YouTube (open captions) |
Intro to Machine Learning (7/11/16)
Instructors | Rebecca Bilbro, Star Ying |
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Description | Basic introduction to machine learning: what it is, how it works, and how to get started with machine learning in Python using the Scikit-learn API. |
Topics covered |
Supervised Learning, Unsupervised Learning, Scikit-Learn, Dimensionality Reduction, Preprocessing |
Software needed |
Git |
Slides | N/A |
Recording | Watch on YouTube (open captions) |
Additional resources |
Step-by-step tutorial on GitHub with Titanic data |
Intro to JavaScript (9/29/16)
Instructors | Natassja Linzau, Mark Brown II |
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Description | Introductory course that covers basic JavaScript concepts and makes use of free online tools for programming in JavaScript with real-life examples. |
Topics covered |
Strings, Integers, Floats, Equality, Loops, Methods, Functions, jQuery, Classes, Objects |
Software needed | |
Slides | N/A |
Recording | Watch on YouTube (closed captions) |
Additional resources | Eloquent JavaScript, by Marijn Haverbeke (free online textbook) |
Intro to Data Analysis (11/16/16)
Instructor | Jeff Chen |
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Description |
This course provides a brief overview of data analysis, focusing on developing a workflow that teases out generalizable insight. Starting from posing a data-actionable question, participants will be taken through basic steps of data cleansing, pattern identification with a particular emphasis on graphing, and communicating insight. |
Recommended pre-requisite | Intro to R |
Software needed |
R and RStudio |
Slides | N/A |
Recording | Watch on YouTube (closed captions) |
Deep Learning (1/10/17)
Instructor | Pri Oberoi |
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Description |
This class will cover deep learning, the concepts behind it, what kind of questions deep learning answers best, and a few real-life examples of deep learning models. Although we will be using the Caffe deep learning framework, the concepts we cover will be framework-agnostic and the goal will be to give attendees a better grasp of the fundamentals of deep learning and the ability to assess how good a model actually is. |
Slides | Download PDF (10.8 MB) |
Recording | Watch on YouTube (closed captions) |
Intro to User Experience Design (2/7/17)
Instructor | Radhika Bhatt |
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Description |
In this course, we will discuss the theory and practice of user experience design. We will go over how to complete user research, how to create personas, and how to conduct usability testing. |
Topics covered | User Experience Design, Usability Testing, User Research, Personas |
Slides | N/A |
Recording | Watch on YouTube (closed captions) |
Intermediate JavaScript and Intro to jQuery (2/21/17)
Instructor | Mark Brown II |
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Description |
Continuing on from Introduction to JavaScript, we will quickly review previous material (data types, arrays and objects, looping) and head into the wonderful world of functions and using JavaScript to interact with HTML and CSS. We will start by coding using vanilla JavaScript, move into using the jQuery library, and introducing intermediate topics in JavaScript including accessing APIs, scope, closure, hoisting, and the keyword 'this'. |
Topics covered | Functions, jQuery, APIs, Scope, Closure, Hoisting, 'this' |
Slides | Download PDF (15.2 MB) |
Recording | Watch on YouTube (closed captions) |
Additional resources | Class materials on GitHub |
Cybersecurity for Managers: An Introduction to the NIST Cybersecurity Framework (3/7/17)
Intro to Qualitative Data Collection (3/21/17)
Instructor | Drew Zachary |
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Description |
Introduction to qualitative data collection for design research, including in-depth interviewing, focus groups, and participant observation. |
Slides | Download PDF (3.3 MB) |
Recording | Watch on YouTube (closed captions) |
Intro to Git and GitHub (5/9/17)
Instructor | Sasan Bahadaran |
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Description |
Learn to work effectively on a data team and never lose your project again! Introduction to version control using Git software and the GitHub website. |
Topics covered | Version Control, Git, GitHub |
Software required | Git GitHub Sublime or Atom.io Terminal or Powershell |
Slides | Download PDF (3.3 MB) |