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

Students learn to use AI for real work, and build a website, an app and a team product along the way.

  • 3 credits
  • No prerequisites
  • AI Literacy Minor

The course

Most people use AI as a chatbot. This course uses it as a toolkit.

Widely available generative AI puts expert-level abilities within reach of anyone who knows how to use it. DATA 2150 gives students hands-on practice using the leading AI assistants and agents for real tasks: finding accurate information, creating text and media, turning content from one form into another, analyzing data, and building things that work.

By the end, students have used AI to build and publish their own work, and know when to trust it.

Artificial Intelligence Tools course, paper collage of a delighted student as her laptop opens into search, images, web pages and a phone app
3

credits

A full Tulane course

0

prerequisites

Open to every major

5

skills

Collect, generate, transform, analyze, deploy

3

things built

A website, an app and a team product

What students learn

Five skills, practiced on real tasks

Five AI skills, paper collage of a long table with five stations: a magnifier gathering images, a quill writing, a prism transforming a page, rising bar charts, and a web page flowing out through a door to an audience
  1. 01

    Collect

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

  2. 02

    Generate

    Create professional text and media from well-built prompts and context.

  3. 03

    Transform

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

  4. 04

    Analyze

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

  5. 05

    Deploy

    Publish working sites and apps that other people can use.

Projects

Three things students build

Paper collage of a student pinning photos and pieces of her interests onto a large web page

Individual

A personal website

Each student uses an AI coding agent to build and publish a portfolio site that makes a visitor want to hire them. Classmates review it, and the site can improve after feedback.

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

Individual

An app

Each student builds a phone app with AI at its center, using the phone's camera, location or microphone, and demos it in class while classmates try it on their own phones.

Paper collage of three students assembling the panels of an interactive website together

Team

A team product

Teams build and launch an interactive website with user accounts, saved data and its own web address, then demo the working product live in class.

Past projects have ranged from health and wellness tools to finance, research and campus life platforms. Students choose what to build.

How the semester unfolds

From first prompt to a launched product

  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 students build and publish their own.

  3. Part 3

    Applied AI

    Newer capabilities such as AI agents, images and presentations, the individual app, and the start of the team build. Students vote on topics for this part, such as AI for the job and internship search.

  4. Part 4

    Launch

    Team products are finished and demoed live, followed by a look at where AI is heading next.

Hands-on AI class at Tulane, paper collage of students at tables with laptops open, comparing results from different AI tools

How class works

Watch it, then do it

  • Demo, then hands-onEach session shows a capability live, then students try it themselves in a short, low-stakes in-class assignment.
  • Screens up when it countsLaptops stay closed for discussion and open when it is time to work.
  • Build between classesProjects are built outside class, and class time goes to demos, discussion and presentations.
  • A peer mentorHolds office hours, meets with teams, and is the first stop for project and technical questions.

Using AI well

Fast is good. Right is better.

Students compare tools, check AI output against real sources, and support every claim with an inline reference to a credible source. An AI tool alone is not a credible source. Because the tools change every semester, the course teaches skills that carry over from one tool to the next.

Checking AI output, paper collage of a student holding a magnifying glass to a generated page while comparing it with an open book

What it counts for

Part of the AI Literacy Minor

AI Literacy Minor

Problem Solving with AI

An elective in Tulane’s AI Literacy Minor

What students need

A laptop and AI accounts

Accounts on the leading AI assistants, and a paid subscription to at least one of them.

Students should confirm with their advisor how the course fits their degree plan.

Also offered online in summer

DATA 2150 also runs online and asynchronously in the early summer session, with the same topics and the same three projects organized as weekly modules. There are no class meetings, so demos and discussion move online. Current sections and dates are listed on the Teaching page.

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.