Mar 27, 2023  
2015-2016 Undergraduate Academic Catalog 
2015-2016 Undergraduate Academic Catalog [ARCHIVED CATALOG]

Add to Portfolio (opens a new window)

GE 1009 - Introduction to Computer Science and Software Engineering

2 lecture hours 2 lab hours 3 credits
Course Description
This course implements the College Board’s 2013 CS Principles framework. Uses Python® as a primary tool and incorporates multiple platforms and languages for computation. This course aims to develop computational thinking, generate interest in career paths that utilize computing, and introduce professional tools that foster creativity and collaboration. Helps students develop programming expertise and explore the workings of the Internet. Projects and problems include application development, visualization of data, cybersecurity, robotics, and simulation. The course aligns with Computer Science Teachers Association (CSTA) 3B standards. (prereq: None) 
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Analyze existing code
  • Create an Android application by using pair programming and by practicing the Agile software design process
  • Implement algorithms in Python using GitHub to manage the process
  • Create a graphical user interface using an application-programming interface
  • Use PHP and SQL to structure and access a database hosted on a remote server
  • Understand the role of client-side code, server-side code, and databases in delivering interactive web content
  • Examine very large data sets and utilize data visualization techniques
  • Program automated robotic behavior in C++

Prerequisites by Topic
  • None

Course Topics
  • Unit 1 Algorithms, Graphics, and Graphical User Interfaces (48%)
    • Lesson 1.1 Algorithms and Agile Development
    • Lesson 1.2 Mobile App Design
    • Lesson 1.3 Algorithms in Python
    • Lesson 1.4 Images and Object-Oriented Libraries
    • Lesson 1.5 GUIs in Python
  • Unit 2 The Internet (18%)
    • Lesson 2.1 The Internet and the Web
    • Lesson 2.2 Shopping and Social on the Web
    • Lesson 2.3 Security and Cryptography
  • Unit 3 Raining Reigning Data (17%)
    • Lesson 3.1 Visualizing Data
    • Lesson 3.2 Discovering Knowledge in Data
  • Unit 4 Intelligent Behavior (17%)
    • Lesson 4.1 Intelligent Machines
    • Lesson 4.2 Interpreting Simulations

Marvin Bollman

Add to Portfolio (opens a new window)