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DS103 Metrics and Data Processing

Course Description: The Metrics and Data Processing course will prepare students to be able to create new metrics that directly answer or monitor business questions. This module will also teach the theory and practice of statistical process control. Upon completion of this module, students will be equipped to help businesses monitor their processes and know when a process is out of control and needs to be fixed.
Quarter Credit Hours: 4.5
Course Length: 60 hours
Prerequisites: DS101 & DS105
Proficiency Exam: No
Theory Hours: 30
Laboratory Hours: 30
Externship Hours: 0
Outside Hours: 15
Total Contact Hours: 60

Required Resources:

  • Ground-based students are required to bring a late model laptop computer (either PC or MacBook) to class every day.

  • Online students are required to have a late model laptop or desktop computer with internet access.

  • Minimum: PC (Windows 10/11) or Mac (Big Sur or Monterey) laptop. 8GB ram, 512GB HD, Intel Core i5, AMD Ryzen 5, or Apple Intel or M1 Chipsets.

  • Recommended: PC (Windows 10/11) or Mac laptop(Big Sur or Monterey). 16GB ram, 1TB SSD, Intel Core i7, AMD Ryzen 7, or Apple M1/M1 Pro Chipsets.

  • Professionals: PC (Windows 10/11) or Mac(Big Sur or Monterey). 32-64 GB ram, 2-8TB SSD, Intel Core i9, AMD Ryzen 9/Threadripper, or Apple M1 Max Chipsets.

  • It is a requirement that you are able to download programming resources to your laptop/desktop for this class. (This means you need a steady internet high bandwidth connection.)

  • You are required to have a quiet place to study and to be able to focus on the material.

  • You are required to have uninterrupted weekly 1:1 video meetings with your mentor.

  • You are required to log into the Learning Management System (LMS) daily for at least 20 minutes.

  • Please follow and review each lesson page by page coding examples provided as this will ensure you have a full understanding for your final hands-on assignments.

Course Outline:

Module Lesson Number Lesson Name
DS103 Metrics and Data Processing 1 Metrics in the Business World
2 Statistical Process Control
3 Process Capability
4 Survey Design
5 Reliability and Validity (Principal Components Analysis)
DS103 Project Management 6 Introduction to Agile Project Management
7 Goals of Project Management and Agile
8 Scrum
9 Kanban
10 Project Planning

Educational Objectives:

Upon successful completion of this Program, students will be able to:

  1. Explain how to use existing metrics to monitor business processes
  2. Uncover metrics
  3. Create new metrics
  4. Explain the theory and rules of statistical process control (SPC)
  5. Explain the difference between control limits and spec limits, and how to fix both types of limits violations
  6. Use capability indices
  7. Use several of the most common types of control charts
  8. Use various analytical tools included with the Pandas package for Python

Points Distribution:

Exam Points Activity
L1 13
L2 10
L3 12
L4 23
L5 23
L6 23
L7 23
L8 23
L9 23
L10 12 Agile Final Exam

Points Total:

Type Points
Professionalism, Attendance and Class Participation*: 20 points (5%)
Assignment/Hands-On/Homework: 90 points (25%)
Exam/Quiz Average: 90 points (25%)
Projects/Competencies/Research: 200 points: (45%)
Total points: 400 (100%)

Final Project:

Create three new small data frames and explore the functions of concatenation, merging, and joining the tables. Create a large data frame that includes HPI data from all 50 states.