Syllabus
Computer Programming: Scientific Python

Computer Programming: Scientific Python

ITSE-1302

Credit Spring 2021
01/19/2021 - 05/16/2021

Course Information

Section 001
Distance Learning
MW 09:00 - 10:00
DLS DIL
Rudy Martinez

Section 001
Laboratory
MW 10:00 - 10:45
DLS DIL
Rudy Martinez

Section 002
Distance Learning
ONL DIL
Rudy Martinez

Office Hours

  • --- - ---
    Email Professor to Confirm Appointment.
  • M T W Th F
    7:30am - 8:30am
    Use Google Meet audio.

ITSE 1302 Syllabus

getting Started

  1. Set a timer for one hour to read the Syllabus (including links), Schedule (see link below), and Blackboard (Bb) content.
  2. In Bb, select the Resources tab on the left. Watch the Orientation Video.
  3. In Bb, select the Assignments tab on the left. Complete the Orientation Exam
  4. Begin work on the first assignment.
  5. Maintain a daily commitment to studying and coding.

Course Description/Rationale

Official description:

This course is an introduction to scientific computer programming including design, development, testing, implementation, and documentation. It may include: Python Fundamentals, functions, data structures, classes, objects, statistical programming, data visualization with MatPlotLib and Programming with the NumPy library.

 

Prerequisites:

COSC 1336 or department chair approval.

Student Learning Outcomes/Learning Objectives

Learning Objectives:

To obtain introductory-to-intermediate knowledge and practical skills applying the following concepts and technologies.

  • Descriptive Statistics
  • Python for Data Science
  • Jupyter Notebook
  • SciPy
  • NumPy
  • Matplotlib
  • Pandas
  • Seaborn

Readings

Course Content: 

OER (Open Educational Resources) are used in this course and are listed in the Blackboard classroom.

Purchase of a textbook is not required.

Course Requirements

 

*** Schedule ***

 

Course Requirements and Grading Rubric:

Tutoring Services (generally intended for entry-level subject material)

Course Subjects

Three Major Units

The course is structured into three major units:

  • Introduction to Descriptive Statistics
  • Whirlwind tour of Python
  • Data Science Handbook

Blackboard Access

Blackboard (Bb) course access 1st week of class:

Students must access the course in Bb during the 1st week of class to be counted as "Attending".  If a student does not access the course in Bb during the 1st week of class s/he will be classified as "Never Attended" and will be ineligible for financial aid and automatically dropped from the course.