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.
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 Big Data
What is “Big Data?” What does it look like and why are companies are collecting it? What challenges do companies face when traditional data processing applications are inadequate to handle large amounts of data?
The Intro to Big Data workshop is designed for students who want to learn about big data and how it can be analyzed with big data platforms. This course will provide an overview of Hadoop, the software framework used for distributing storage and processing of large data sets. Students will learn how to deploy, configure, and monitor a Hadoop Cluster; import and export data; and how to query and explore big data using Hive and interactive SQL. Students will also be introduced to Spark, a powerful in-memory processing engine used for sophisticated analytics using Python and PySpark (Spark Python API).
Students will get hands-on experience with big data platforms working through multiple in-class exercises, including a sentiment analysis using machine learning.
Prior knowledge of SQL or Python is helpful but not expected or required.
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
Build a Text-Based Chatbot with Amazon Lex
In this workshop, you will learn how to build a text-based conversational chatbot using Amazon Lex, the same deep learning technologies and natural language understanding (NLU) that power Amazon Alexa. You will run Python code in the cloud to execute business logic using Amazon Lambda, and then integrate your chatbot with Twilio to access your bot via text messaging.
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.
Data Analysis Project: Hotel Booking Software Platform
Clientivity is a hotel booking software platform that empowers users to create, manage and earn commission from personal, group and corporate travel. During the fall of 2017, the company submitted an entry to the inaugural WCAI Analytics Accelerator Challenge because they were interested in improving the partner experience by building pipelines to increase sales volume and actively engage with partners for a longer period of time.
A student led team under the guidance of Professor Serguei Netessine reviewed the company’s large dataset which included funnel statistics, partner and end-user demographics, and hotel pricing trends. After reviewing the data, the team recommended to segment partners to identify high-performing groups, optimizing for sales efficiency. Additionally, recommendations were given to guide partners to improve performance with timely information and friendly competition; keep partners active by catering to their desires, convenience and sense of community.
This course includes all final project deliverables, including presentation materials, code, the complete dataset, and findings.
Data Collection Project: Virtual Sommelier
Coqovins is a virtual sommelier that makes personalized wine recommendations through a chatbot at participating wine stores. During the fall of 2017, the company submitted an entry to the inaugural WCAI Analytics Accelerator Challenge to help their customers simplify the wine selection process and decrease the number of customers leaving wine stores empty-handed.
A student team under the guidance of Professor Raghu Iyengar helped Coqovins build an exhaustive wine database classified by wine styles that are clustered and linked to features of the wine.
This course includes the complete wine database and the code used to scrape and classify the wines.
Forthcoming Online Courses:
- Statistical Models 101