Technical Workshops & Online Courses

WCAI offers a range of free, extra-curricular technical workshops and self-guided online courses for MBAs & undergrads to hone their data management skills for internships and future employment.

 Check our events page for any upcoming workshops

currently available online courses:

Intro to SQL Bootcamp

Analytics is expanding at exceptional rates, with implications across all industries. SQL is the back-end language for direct data manipulation for many major websites, databases, and computer systems around the world. This course is intended to give you a good understanding of basic SQL and database concepts, and opportunities to practice the running different kinds of queries on databases. No prior knowledge of SQL is expected or required.

Intro to Python Bootcamp

Whether you have experience in programming or are looking to get started for the first time, getting involved in the Python community will put you on the fast track to honing your skills as a programmer. In this class, you’ll learn all about Python – including how to get started, what advantages and disadvantages Python provides as a programming language, the essentials of programming, and what tools are available to build applications in Python. You’ll learn best practices, code reuse, and how to write good clean programs.

Intro to R Bootcamp

Because the R programming language facilitates and enhances the process of getting insights from data, R has become one of the core skills for the Data Science field. Developing an understanding of its functions and capabilities is critical for anyone who works with data. This open source software offers lots of power with relatively little code, a large user community, robust add-on packages for specialized analyses, and parallelization to make full use of multiple cores/cluster environments. It can also be plugged into a complex workflow or an analytics engine.

This course was designed to give you a basic familiarity with, and understanding of, this high-level programming language. By the end of this course, you’ll be able to understand syntax and idioms for writing R code, and explore the add-in packages that can expand R’s repertoire and enhance your productivity. You’ll become familiar with RStudio, the Integrated Development Environment (IDE) we’ll use, and ultimately make a decision as to whether you (or your team) could benefit from learning more about R.

This course is offered through Coursera and is available to current Penn students and Alumni for free.

Instructor: Richard Waterman, Practice Professor of Statistics at The Wharton School

Intro to Data Visualization

This course is organized into two modules:

  • Data Visualization Concepts: An overview covering the What and the Why questions around visualizing data, broadly, as well as guidelines for best practices. Some formats and tools will be demonstrated in preparation for students to begin to lead their own explorations
  • Introduction to Tableau: This is a hands-on introduction to the widely used and user-friendly visualization tool, using sample data provided within the software

Introduction to Python with Marketing Applications

Python is becoming the common language for business analytics, data science and artificial intelligence. This workshop will introduce the basics of Python, presented using the example of solving a common business problem, grouping customers into market segments. Attendees will take away an understanding of the basic concepts of computer programming in general as well as Python in particular; moreover, they will gain the ability to write simple but useful programs and to continue learning on their own.

Instructor: Nathan Grossman, data scientist at Ruckus Wireless, working on a cloud-based, wireless network management service.  He has an MBA from Wharton, an MS in Electrical Engineering from Michigan, and a BS in Mechanical Engineering from Illinois.

Online Survey Design

People are often poor participants in research. They are inconsistent, complex, and biased. Unfortunately, people are also often poor authors of research surveys. They write items that are inconsistent, complex, and biased. This workshop, developed by Jacob Levernier, will address the latter in the hope of minimizing the effects of the former.

Is My Advertising Working?

This tutorial gives marketing analytics students a hands-on introduction to attribution rules like last-click, holdout experiments, marketing mix modeling, and algorithmic attribution.  All examples are worked on the same (synthetic) dataset, so that students can see how the results compare to each other and the true data-generating process. To make the material accessible, all the modeling examples are pretty basic and use standard R regression functions. While it won’t make any student an expert in advertising response, they will walk away with a better understanding of what the real experts do. 

Author: Elea Feit, Assistant Professor of Marketing at Drexel University. Fellow at the Wharton Customer Analytics Initiative. Co-author of R for Marketing Research and Analytics.

Forthcoming Online Courses:
  • Intro to Big Data Bootcamp
  • Statistical Models 101

Online Courses Enrollment Form

  • To enroll, you must provide a valid UPenn email address.