MSBA 604 — Fundamental Technologies for Business Analytics#

Gonzaga University | School of Business Administration Master of Science in Business Analytics (MSBA)

Course Information#

Course Description#

This course builds foundational programming and technical skills essential for business analytics. Students develop proficiency in Python while learning to think computationally about business problems. The course emphasizes code literacy — the ability to read, evaluate, and critique code (including AI-generated code) — over syntax memorization. All examples and applications are grounded in business analytics contexts, preparing students for advanced coursework in data analysis, machine learning, and strategic decision-making.

Four Core Principles#

Four fundamental programming principles thread through every module, helping students recognize patterns that appear across languages, tools, and analytics contexts:

1. Iteration — Repeating processes systematically across data
2. Inference — Drawing conclusions and making decisions based on conditions
3. Abstraction — Managing complexity by hiding details behind simple interfaces
4. Polymorphism — Applying the same operation to different types of data

Course Platforms#

Course Website: https://gu-msba604.netlify.app

Course Schedule#

Unit 1: Foundation (Weeks 1–3)#

Week 4: Exam 1

Unit 2: Core Programming (Weeks 5–8)#

Week 9: Exam 2

Unit 3: Data Work (Weeks 10–13)#

Unit 4: Final Project (Weeks 14–16)#

Final Project Due: End of Week 16

Module Descriptions#

Foundation#

• Variables, Expressions, and Data Types — Named containers, calculations, and information categories
• Containers — Lists, dictionaries, tuples, and sets for organizing collections of data
• Branching and Control Flow — Making decisions with conditional logic
• Loops — Repeating operations across data systematically
• Functions — Creating reusable, modular code
• Error Handling and Debugging — Writing robust code that handles the unexpected

Building Blocks#

• Classes and Object-Oriented Programming — Modeling real-world entities in code
• Files, APIs, and Data Ingestion — Bringing external data into Python
• Pandas and Data Structures — Professional-grade data manipulation
• Data Visualization — Communicating insights through charts and graphics

Integration#

• Applied Integration and Reproducibility — Combining skills into professional analytics workflows

Assessment Structure#

Final Project#

The course culminates in an applied final project where students integrate skills from across the course to solve a real business analytics problem. Students will:

• Ingest and clean data from external sources
• Apply appropriate data structures and transformations
• Create visualizations that communicate insights
• Document their work in a reproducible notebook
• Present findings with attention to ethical implications and business value

Required Materials#

• Zybooks — Interactive textbook (subscription required)
• Course Website — All learning content freely accessible

No prior programming experience is required. All necessary software is browser-based and free.

Weekly Workflow#

Each week, students should:

1. Check Canvas for the week’s schedule and any announcements
2. Visit the course website to review module content and code examples
3. Watch the weekly videos — overview and code walkthrough
4. Complete Zybooks homework by the posted deadline

Pedagogical Approach#

Code Literacy Over Syntax Memorization#

In an AI-assisted world, the ability to read, evaluate, and critique code matters more than memorizing syntax. Students learn to understand what code does and why, preparing them to work effectively with AI tools and collaborators.

Business Analytics Context#

Every example, exercise, and scenario is grounded in business analytics — customer data, sales figures, transaction analysis, operational metrics — rather than abstract computer science problems.

Jesuit-Informed Learning#

Where appropriate, modules incorporate ethical dimensions, social impact, and contributions to the common good alongside business outcomes. Technical skills connect to meaningful purpose.

Course Policies#

Academic Integrity#

Students are expected to complete their own work with integrity. AI tools may be used as learning aids where specified, but students must be able to explain and defend any code they submit.

Accessibility#

Gonzaga University is committed to providing equal access to learning opportunities. Students requiring accommodations should contact Disability Access Services.

Late Work#

Assignments submitted late will be penalized 10% per day unless prior arrangements have been made with the instructor.

Getting Help#

• Office Hours — Virtual appointments available via Calendly
• Discussion Board — Post questions in Canvas for peer and instructor support
• Email — Expect responses within 24–48 hours on business days

About the Instructor#

Dr. John Correia is Associate Professor of MIS and Faculty Lead for the MIS/ISBA program in the School of Business Administration. His teaching integrates technology, business strategy, and Jesuit values to prepare students for meaningful careers in the digital economy.

This syllabus is subject to change. Students will be notified of any modifications via Canvas announcement.