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Course Description

Data scientists work in teams and it's important for each team member to understand software engineering processes and practices. From requirements gathering to agile development to testing and deployment, the ability to go beyond writing macros and simple scripts is key to both more sophisticated analyses and building reproducible and scalable data investigations and data products. This course, based in Python, will cover fundamental aspects of computer science, good practices in software engineering, and practical aspects of deploying code in production environments. To do this, we will use the Python language, a simple yet elegant general purpose programming language that is well-suited for data analysis and visualization.

Course Objectives

Upon successful completion of the course, students will:

  • Understand software architecture and design
  • Examine agile and hypothesis-driven software development processes
  • Identify team roles and workflows in software engineering
  • Conduct requirements gathering
  • Use Git and Github for version control and collaboration
  • Recognize the importance of testing and building test suites
  • Understand the legal aspects of software development
  • Apply software engineering practices to your data science project

Notes

Enrollment in this course is restricted. Students must submit an application and be accepted into the Certificate in Data Science in order to register for this course.

Current Georgetown students must create an application using their Georgetown NetID and password. New students will be prompted to create an account.

Course Prerequisites

Course prerequisites include:

  • A bachelor's degree or equivalent
  • Completion of at least two college-level math courses (e.g. statistics, calculus, etc.)
  • Successful completion of Foundations of Data Analytics and Data Science (XBUS-500)
  • Basic familiarity with programming or a programming language
  • A laptop for class meetings and coursework

Students with little or no programming experience are strongly encouraged to complete Python Basics for Data Analysis before enrolling in this course.

Applies Towards the Following Certificates

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Type
Class
Days
F
Time
6:30PM to 9:30PM
Dates
Mar 05, 2021 to Mar 12, 2021
Type
Class
Days
Sa
Time
9:00AM to 4:00PM
Dates
Mar 06, 2021 to Mar 13, 2021
Schedule and Location
Contact Hours
18.0
Course Tuition
Tuition non-credit $1,249.00 Click here to get more information
Instructors
Section Notes

Welcome to the Flex Learning Experience - Real-time learning using live Zoom video conferencing— mirroring a more traditional classroom with regular interaction, - engaging activities, and the dynamic exploration of topics and concepts.

  • Dynamic exploration of topics, ideas and concepts with the instructor and students in the class
  • Interact regularly and frequently with your instructors and other students
  • Comparable level of accountability and engagement as classroom attendance
  • Lectures, discussions, and presentations occur at a specific hour
  • Face-to-face discussion, individual guidance, speed and immediacy to synchronous online learning
  • Immediate feedback - encouraging quick feedback on ideas, and support consensus and decision making
  • Pacing - encouraging students to keep up-to-date and provide a discipline to learning
  • Spontaneity - making it easy to add new ideas to the conversation, brainstorming or decision making
  • Familiarity - simulating a more traditional face-to-face environment

 

Computing Requirements

Students will be expected to use a personal laptop to complete analytics and programming workshops and a Capstone project. Students should have administrative access and be able to install required course software and libraries. We recommend the following minimum computing requirements:

  • A laptop with at least a dual-core 1.8 GHz processor, 4GB of RAM, and 20 GB free hard disk space (e.g. a laptop purchased in the past two years).
  • A modern operating system: Windows 10 or newer (updated to the latest semi-annual channel version), OS X 10.15 Catalina or newer, or Ubuntu 20.04 or newer (or an equivalent Linux distribution). OS X and Linux are strongly encouraged.
  • Administrator access on your system to install new software.
  • Python 3.8 (or later) or Anaconda 2020.07 (or later) installed on your system.
  • A command prompt available (Powershell on Windows, Terminal on OS X or Linux).

Please note that computing requirements and software dependencies may change. 

Type
Class
Days
F
Time
6:30PM to 9:30PM
Dates
Jun 04, 2021 to Jun 11, 2021
Type
Class
Days
Sa
Time
9:00AM to 4:00PM
Dates
Jun 05, 2021 to Jun 12, 2021
Schedule and Location
Contact Hours
18.0
Course Tuition
Tuition non-credit $1,249.00 Click here to get more information
Instructors
Section Notes

Welcome to the Flex Learning Experience - Real-time learning using live Zoom video conferencing— mirroring a more traditional classroom with regular interaction, - engaging activities, and the dynamic exploration of topics and concepts.

  • Dynamic exploration of topics, ideas and concepts with the instructor and students in the class
  • Interact regularly and frequently with your instructors and other students
  • Comparable level of accountability and engagement as classroom attendance
  • Lectures, discussions, and presentations occur at a specific hour
  • Face-to-face discussion, individual guidance, speed and immediacy to synchronous online learning
  • Immediate feedback - encouraging quick feedback on ideas, and support consensus and decision making
  • Pacing - encouraging students to keep up-to-date and provide a discipline to learning
  • Spontaneity - making it easy to add new ideas to the conversation, brainstorming or decision making
  • Familiarity - simulating a more traditional face-to-face environment

 

Computing Requirements

Students will be expected to use a personal laptop to complete analytics and programming workshops and a Capstone project. Students should have administrative access and be able to install required course software and libraries. We recommend the following minimum computing requirements:

  • A laptop with at least a dual-core 1.8 GHz processor, 4GB of RAM, and 20 GB free hard disk space (e.g. a laptop purchased in the past two years).
  • A modern operating system: Windows 10 or newer (updated to the latest semi-annual channel version), OS X 10.15 Catalina or newer, or Ubuntu 20.04 or newer (or an equivalent Linux distribution). OS X and Linux are strongly encouraged.
  • Administrator access on your system to install new software.
  • Python 3.8 (or later) or Anaconda 2020.07 (or later) installed on your system.
  • A command prompt available (Powershell on Windows, Terminal on OS X or Linux).

Please note that computing requirements and software dependencies may change. 

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