Knud Berthelsen
DATA 2150 Artificial Intelligence Tools at Tulane, paper collage of a student at a worktable directing floating panels that gather documents, make images, lay out a web page and build charts

DATA 2150 · Tulane University

Artificial Intelligence Tools

Learn how AI works, how to work with it, and how to build with it.

  • 3 credits
  • No prerequisites
  • AI Literacy Minor

What can you actually do with AI?

In DATA 2150, you learn to use current AI tools and agents, with hands-on practice in every class. You find out what each tool does well, where it fails, and how to check its work.

Artificial Intelligence Tools course, paper collage of a student at a laptop as research, audio and a phone app flow out of it
5

skills

Collect, generate, transform, analyze, and deploy

3

things you build

A website, an app, and a team product

4.7

out of 5

Student course evaluations

4.8

out of 5

Instructor evaluations

Five skills

Five AI skills, paper collage of a shelf with a magnifier over documents, a drawing and pencil, a page turning into a sound wave, bar charts, and a web page in an open doorway
  1. 01

    Collect

    Run the same research question through several AI tools, then check their sources.

  2. 02

    Generate

    Create text, images, and other media, and learn which prompts and context improve the results.

  3. 03

    Transform

    Turn a dense reading into a new format without losing accuracy.

  4. 04

    Analyze

    Analyze a dataset with two tools and find at least one thing the AI got wrong.

  5. 05

    Deploy

    Publish sites and apps that other people can use.

What you build

Paper collage of a student arranging his portrait and interests on a personal web page

Individual

A personal website

You use an AI coding agent to build and publish a portfolio site that makes a visitor want to hire you. Then you compare it with your classmates’ sites and revise and improve it.

Paper collage of a student holding an app sketch while pointing at the same design on a large phone

Individual

An app

You build an app with AI at its center that runs in a phone's browser and uses the camera, location, or microphone, then demo it in class while classmates try it on their own phones.

Paper collage of three students assembling a website with a map, a calendar and audio features

Team

A team product

Your team builds and launches an interactive website with user accounts, saved data, and its own web address, then demos it live in class.

The four parts of the semester

  1. Part 1

    Foundations

    How generative AI works and where it fails, personalizing AI, generating and transforming content, research, and data analysis.

  2. Part 2

    Build a website

    Professor Berthelsen builds and publishes a site live in class from scratch. Then you build and publish your own.

  3. Part 3

    Applied AI

    Newer capabilities such as AI agents, images, and presentations, plus your app and the start of the team build.

  4. Part 4

    Launch

    Team products are finished and demoed live, and the course ends with a look at where AI is heading.

Hands-on AI class at Tulane, paper collage of four students at tables with laptops open, comparing charts and results

How class works

  • Demo, then hands-onEach session shows a capability live, then you try it yourself in a short, low-stakes in-class assignment.
  • Screen down and screen upLaptops stay closed unless screen up is announced, and phones are not used at any time.
  • Build between classesYou build projects outside class, and class time goes to demos, discussion, and presentations.
  • No final examGrades come from in-class assignments, the three projects, participation, and peer assessment.
  • A peer mentorA student peer mentor holds office hours, meets with teams, and is your first stop for project and technical questions.
  • What you needA laptop, accounts on the major AI tools, and a paid subscription to at least one of them.

Using AI in this course

You are expected to use AI, and to talk about which tools you used, how, and how well they worked. You also compare tools, check AI output against other sources, and back every claim with credible data and an inline reference to its source. An AI tool alone is not a credible source.

Checking AI output, paper collage of a student holding a magnifying glass to a generated page, with threads linking it to an open book and other sources

What it counts for

DATA 2150 is part of Tulane’s AI Literacy Minor (Problem Solving with AI). Confirm with your advisor how the course fits your degree plan.

When it’s offered

DATA 2150 runs in person during the regular semester. In Spring 2027 it meets Tuesdays and Thursdays at 9:30.

Also offered online in summer

DATA 2150 also runs online and asynchronously in the early summer session. There are no class meetings, so demos, discussion, and presentations move online. Current sections and dates are listed on the Teaching page.

Fitting DATA 2150 into your degree plan, paper collage of a student placing a course card with an AI spark into a semester board, beside a two-day week and a laptop under a summer sun
Paper collage of a student walking out onto a bright path with the website, app and charts she built floating beside her

The instructor

Knud E. Berthelsen

Knud Berthelsen is a Professor of Practice at Tulane University and Senior Advisor for AI Literacy at the Connolly Alexander Institute for Data Science. He also teaches SLAM 3111 AI and Society and SLAM 2031 Applied Data Analysis, and consults for and trains organizations on how AI works and how to work with it. Before focusing on AI, he spent a decade teaching international strategy and new venture management at Tulane's Freeman School of Business.

More in his CV and on the Teaching page. Questions about the course? Contact Professor Berthelsen.