Commerce Data Academy

Tools and Resources
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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

Data Science Basics (3/14/16)

Instructor Rebecca Bilbro
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
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
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
Conda: a package, dependency and environment management system for any language, including Python
Pip: the PyPA recommended tool for installing Python packages

Intro to Design and Photoshop (4/19/16)

Instructor Radhika Bhatt
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
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
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
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
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
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
GitHub
Sublime or Atom.io
Terminal or Powershell
Python
Scikit-learn

Slides N/A
Recording Watch on YouTube (open captions)
Additional resources

Step-by-step tutorial on GitHub with Titanic data
Related article by Rebecca Bilbro on District Data Labs blog
NIST Clustering Notebook on GitHub
Commerce Data Usability Project 

Intro to JavaScript (9/29/16)

Instructors Natassja Linzau, Mark Brown II
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

Git
GitHub

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
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
Packages: plyr, hexbin, corrplot

Slides N/A
Recording Watch on YouTube (closed captions) 

Deep Learning (1/10/17)

Instructor Pri Oberoi
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
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
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)

Instructor Jeff Marron, NIST
Description

The Cybersecurity Framework developed by the National Institute of Standards and Technology (NIST) with the strong involvement of the private sector and others has quickly emerged as a leading approach for organizations to understand and improve their management of cyber risks in the context of broader enterprise risk. Initially intended for use by organizations in the critical infrastructure, the Framework has been embraced by organizations in all sectors of the economy and is beginning to be used internationally. The Office of Management and Budget (OMB) has strongly encouraged federal agencies to use the Framework, too.

In this session, NIST officials will cover the basics about the Framework and share guidance, insights, and examples that will help federal managers – including but not limited to those involved with information technology policies and operations – to understand how the Framework can help their organizations. CIO officials and staff at Commerce agencies and those who work with industry constituents are invited and encouraged to participate.

Slides N/A 

Intro to Qualitative Data Collection (3/21/17)

Instructor Drew Zachary
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
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)

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Last updated: 2018-02-22 14:27

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