Math 398

2026-08-25

Introductions

  • Introductions

  • Class Setup

  • Final Project

  • Generative AI

  • Field Trip

Introductions

  • San Bernardino, CA

  • CSU Monterey Bay

    • BS Biology
  • San Diego State University

    • Master’s in Public Health
  • UC Riverside

    • PhD in Applied Statistics

Introductions

  • Name

  • Year

  • Major

  • Fun Fact

  • Career Goal

Class Setup

  • Introductions

  • Class Setup

  • Final Project

  • Generative AI

  • Field Trip

Class Setup

  • Homework Assignments
  • Video Assignments
  • Progress Reports
  • Final Presentation
  • Final Write Up

Syllabus

m398.inqs.info/syllabus

Course Website

m398.inqs.info

Tools

IDE

Final Project

  • Introductions

  • Class Setup

  • Final Project

  • Generative AI

  • Field Trip

The Final Project

The final project is designed for you to demonstrate your understanding of machine learning.

You may …

Build a machine learning model related to any data you are interested in predicting the outcome.

You may …

Use existing machine learning models for classification, transcription or any other purpose.

You may …

Explore advance topics related to machine learning.

For each project

You will need to describe

  • The model used
  • Type of input data
  • Output of interest
  • A working example
  • Model Diagnostics

Final Poster Presentation and Report

You will demonstrate your results during a poster presentation on December 8, 2026.

You written report will be due on December 5th, 2026 @ 11:59 PM

More information will be provided on a later date.

Final Report Extensions

For those that need an extension in completing your final report, you may obtain up 7 days extension for every appointment you meet with the Writing and Multiliteracy Center to work on your report.

  • 1 Meeting = 24 hour extension
  • Each meeting must be 1 week apart minimum
  • No double dipping between Math 398 and Data 300

Final Report Guidelines

Report Guidelines

Generative AI

  • Introductions

  • Class Setup

  • Final Project

  • Generative AI

  • Field Trip

Use of Generative AI Policy

The use of generative artificial intelligence (AI) to complete any part or all of an assignment/exam is strictly prohibited in this class. This includes, but not limited to, ChatGPT, Claude, Meta AI, and Google Gemini.

You may use AI to enhance you understanding of the material.

You may not use AI to complete assignments.

You may not upload any course material to any AI platforms such as ChatGPT, Claude, Meta AI, and Google Gemini. Exceptions are allowed for DASS-approved services.

Use of AI

There are consequences when you use of AI:

  • Educational Mislearning
  • Trusting AI
  • Stolen Work
  • Privacy Concerns
  • Environmental Impacts
  • Working Exploitation

Educational Mislearning

The purpose of this class, and college, is for you to learn about critical thinking skills and perseverance. Using AI will only teach you how to get an answer, which may or may not be correct.

You will not develop the skills needed to problem solve a challenge. Additionally, developing grit is essential to become successful in college and life. There is no easy way out and AI is an illusion to your success in life.

To learn something, it requires hours of work! If not years!

Trusting AI

When using AI, you must acknowledge its limitations:

  • Responses provided may be incorrect

  • Responses may not be fair

  • Companies may manipulate responses and/or terms of service for their benefit

  • Companies may not have your best interst in mind

You should always proceed with caution utilizing these tools!

Stolen Work

Additionally, all these individuals are not receiving any royalties for the work to be used in creating generative AI models.

Inside Higher Ed and The New Yorker highlight individual’s concern of their work being used to train AI models.

Privacy Concerns

The use of generative AI raises concerns of what data is being harvested from us, possibly without informed consent or knowledge of impacts.

When you use any large language models, you do not know what information is being harvested from you.

Do you want to upload your thoughts and ideas to a company that can monetize, and possibly exploit you.

Does your Professors consent with you uploading their assignments to large language models?

Stanford provided a report highlighting the risks of our personal data use in large language models.

Environmental Impact

In order to run these large language models, companies need to use a large amounts of energy. This is because large servers are needed to both train and execute a model.

The LA Times reports the potential impact that running AI models in California.

Additionally, Time reports that a ChatGPT query uses ten times more energy than a Google search query, and global AI demands can consume of 1 trillion gallons of water by 2027.

There are also environmental justice questions about where these data centers are constructed.

Worker Exploitation

The Washington Post and Time (Article 1 and Article 2) reported that AI companies utilize “digital sweatshops” to classify data points for model training.

There is a human cost from the Global South, both financially and mentally, to develop the AI models for users in the United States and Europe.

We must be conscious consumers and demand more from these companies to provide safe working conditions and livable wages.

Is Using AI Bad?

Yes/No/I don’t know

Environmental Costs

Field Trip

  • Introductions

  • Class Setup

  • Final Project

  • Generative AI

  • Field Trip