NOTE:  This HIGH VALUE bootcamp is being offered at NO COST to you through the generosity of alumni, parents and friends of Lafayette College in conjunction with the Gateway Career Center and the Dyer Center.

Attendance is limited to 30 students** Enrolled students MUST participate in both courses (1 and 2).

  • COURSE 1:  This program begins December 8th, is a 5-week program, and will conclude January 15th.
  • COURSE 2:  The second part of the program (Data Visualization with Tableau, is a 5-week program, and will begin in Summer 2021 (Date TBD). 

If you are accepted for the program, full participation in the 10-week boot camp is expected. If you do NOT complete the boot camp in its entirety, you will be charged $200.

If you have any questions regarding the program, please contact the Gateway Career Center at 610-330-5115 or the Dyer Center prior to applying.

Application Information: You MUST apply through CareerSpot. 

All applications will be reviewed and students notified of their acceptance to the program by Wednesday, December 2nd, 2020. 

Applications must include a Resume and Essay.

Essay must be 300-400 words and answer the following questions:

  1. What interested you in this bootcamp?
  2. How do you see this experience helping you in your professional endeavors? 

Upload your essay to Writing Sample under your documents in CareerSpot. 

Applications must be submitted by Sunday November 29th. No late submissions will be accepted.

NOTE:  This course has a required number of participants.  If for some reason we should not reach the required enrollment, we will need to cancel the boot camp and all applicants will be notified.  

To learn more about the Data Analytics BootCamp Click Here 


Introduction to Applied Data Analytics

Course Description:

The goal of this course is to teach applied job skills in close connection to the concepts and theories that drive the daily decisions relevant to data analysis and business intelligence. Each module will focus on a primary theme. Students will start by grappling with real-world cases, then will methodically drill down to solve the problems from a technical approach. A few of these topics include applications of statistics, data visualization tools in Excel, linear regression, time-series, classification algorithms, and bias in data.


Course Objectives

Experiential Skills

At the completion of this course, students will be able to:

  • Understand implications of data bias in case studies
  • Understand different data types and use cases
  • Ask effective questions about the data
  • Understand business metrics and KPIs
  • Communicate technical information to business stakeholders
  • Understand the difference between supervised and unsupervised learning
  • Create a conversion rate optimization analysis
  • Create a customer experience analysis

Technical Skills

At the completion of this course, students will be able to:

  • Understand the differences between common data types in Excel
  • Demonstrate ability to calculate standard statistical measures in Excel
  • Demonstrate proficiency with common data analysis techniques in Excel, e.g., Pivot Tables and VLOOKUP
  • Create and interpret a linear regression model in Excel
  • Create and interpret a time series model in Excel
  • Implement logistic regression in Excel
  • Demonstrate ability with basic visualizations in Excel
  • Create and run a hypothesis test


Data Visualization with Tableau

Course Description

The goal of this course is to teach the skills, concepts, and theories relevant to data visualization and its applications. Students learn theoretical fundamentals and design principles of data-based visualizations, how to spot misleading and untruthful visualizations, and how to use Tableau, a leading data visualization software. Students also learn visualization best practices, how to design usable dashboards, and will sharpen their analytical skills. This course is hands-on, allowing students to merge, join, and download data from several sources for their visualizations.


Course Objectives

Experiential Skills 

At the completion of this course, students will be able to:

  • Understand business Key Performance Indicators (KPIs)
  • Communicate data effectively
  • Analyze existing data visualizations for persuasiveness and accuracy
  • Build visually compelling dashboards

Technical Skills

At the completion of this course, students will be able to

  • Understand the conceptual and technical fundamentals of data visualization
  • Employ best practices in data visualization to develop charts, maps, tables, and other visual representations of data
  • Utilize advanced Tableau features including parameters, data blending, and custom date hierarchies
  • Use Tableau’s visualization tools to conduct data analysis and explore unfamiliar datasets