ENGI 212 Applied Coding for Engineers and Scientists

This course is an introduction to programming fundamentals. It will cover the basics of scripting languages, good algorithm design, and code development. Topics include types, data structures, and objects. The course includes hands-on programming in a variety of applications from multiple application areas. Major general-purpose modules including numeric and graphing modules as well as data acquisition and reduction are explored. Prior programming experience is not required.


Credits

3 Credits

Semester Contact Hours Lecture

45

Semester Contact Hours Lab

0

Prerequisite

MATH 143 or equivalent

ENGI 212Applied Coding for Engineers and Scientists

Please note: This is not a course syllabus. A course syllabus is unique to a particular section of a course by instructor. This curriculum guide provides general information about a course.

I. General Information

Department

Engineering, Physical, and Computer Sciences Academic

II. Course Specification

Credit Hours Narrative

3 Credits

Semester Contact Hours Lecture

45

Semester Contact Hours Lab

0

Prerequisite Narrative

MATH 143 or equivalent

Repeatable

No

III. Catalog Course Description

This course is an introduction to programming fundamentals. It will cover the basics of scripting languages, good algorithm design, and code development. Topics include types, data structures, and objects. The course includes hands-on programming in a variety of applications from multiple application areas. Major general-purpose modules including numeric and graphing modules as well as data acquisition and reduction are explored. Prior programming experience is not required.


IV. Student Learning Outcomes

Upon completion of this course, a student will be able to:

  • Demonstrate the ability to write efficient and well-structured code, utilizing libraries for data manipulation and visualization
  • Apply various data acquisition methods, including interfacing with sensors and hardware, including microcontrollers, to collect and process real-time data relevant to scientific or engineering applications
  • Employ statistical techniques and data analysis methods to interpret acquired data, enabling them to draw meaningful conclusions and make informed decisions
  • Work in teams to design and implement a project that involves modeling and analysis, demonstrating the ability to integrate programming skills with scientific principles
  • Effectively communicate findings through reports and presentations, including clear documentation of code and methodologies used

V. Topical Outline (Course Content)

VI. Delivery Methodologies

Assessment Strategy Narrative