Engineering in the World of Data

Purdue’s Engineering in the World of Data Learning Community brings together first-year engineering students & faculty who share an interest and enthusiasm for data science and its application to engineering disciplines and practices.

You will apply for learning communities at the same time that you apply for on-campus housing.

Meet the teaching team

Professor Michael Witt teaches ILS 103, Introduction to Data Lifecycle Management, and leads many of the community’s extracurricular activities such as coding challenges, Ultimate Frisbee and kickball tournaments, and field trips to local companies who hire engineers with data science skills. Professor Witt was recently recognized with the Murphy Award.
Professor Sean Brophy teaches ENGR 132, Transforming Ideas to Innovation II, and ENGR 103, Computational Methods of Data Science for Engineers, and challenges students to develop computational thinking abilities and apply data science to their future professional practice as engineers.
Professor Robert Loweth teaches ENGR 131, Transforming Ideas to Innovation I, and supports students in thinking through the broader societal implications of their engineering work.
Wendy Hammer teaches ENGL 106, First-Year Composition, with a focus on games and narrative. She encourages students to use their analytical skills, creativity, and experiences to enrich their writing—to better connect with audiences and tell compelling stories with their data.


Students accepted into the learning community will take these five courses together as a cohort. Your academic advisor can help you register for the special, data-science themed sections of these classes that are exclusive to our community.

ILS 103 – Introduction to Data Lifecycle Management

1 credit, fall semester – You’ll learn about different types of data in engineering, how to locate and evaluate data, the ethical use of data, and the basics of data management, analysis, representation, and archiving.

ENGL 108 – Accelerated First-Year Composition

3 credits, fall semester – required of all first-year students unless you have AP or transfer credit. You’ll learn how to think and write critically with an awareness of diverse audiences, engaging a variety of digital technologies.

ENGR 131 – Transforming Ideas to Innovation I

2 credits, fall semester – required of all first-year engineering students. You’ll learn systematic design processes, construct mathematical models to solve engineering problems using Excel, and develop professional habits that will benefit you now as a student and in your future as a practicing engineer.

ENGR 132 – Transforming Ideas to Innovation II

2 credits, spring semester – required of all first-year engineering students. You’ll use MATLAB and other tools to apply programming concepts to engineering, explore models in greater depth and with a variety of formats of data, and demonstrate the habits of a professional engineer working in a team environment.

ENGR 103 – Computational Methods of Data Science for Engineers

1 credit, spring semester – You’ll be introduced to programming in python and use it to explore computational solutions to engineering problems. You’ll get an overview of data science approaches related to system performance, real-time data acquisition, modeling and simulation, machine learning, and big data. This course is only available to our learning community.

Living on campus

Students in the Engineering in the World of Data Learning Community will live together in the mighty Shreve Hall. Your roommate will likely be a member of the community, too. Students who also belong to the Women in Engineering Learning Community may reside in either community’s hall.

Common questions

Is there more coursework involved?

Our community adds a one-credit hour class to your fall semester (ILS 103) and a one credit-hour class to your spring semester (ENGR 103). The other three classes are required whether you belong to our community or not.

Do I need to know how to write code?

No, we do not assume any programming experience for our courses, which are introductory. There will be a few, optional opportunities for experienced programmers to flex their chops in coding competitions.

Is it true that our faculty bring live snakes into the classroom when we introduce the python programming language?


I’m not going into ECE, so why should I care about data science?

Data are important in all disciplines of engineering, as well as our lives, and being able to mine data to effectively innovate and solve problems is a very valuable and marketable skill in nearly any professional engineering practice. Data science is cutting-edge, in demand by employers, and can make the world a better place.

Why should I join a learning community?

Purdue is a big place… nearly 50,000 students. Joining a learning community like ours will help you make friends and connect directly and personally with professors who share similar interests. Studies have demonstrated that students who participate in learning communities get better grades and report greater satisfaction with their university experience after graduation.

Plus we have a lot of fun – check out our Instagram to get a better idea of the kinds of experiences you can look forward to in our community!