“The Murty Sunak Quantitative and Computing Lab (QCL) serves as the transdisciplinary campus hub and comprehensive support center for students, faculty, and staff seeking assistance across a broad spectrum of quantitative areas and skills, including mathematics, computation, statistics, programming, data analysis, and data visualization.”

The QCL strives to:

• Support students in applying quantitative and computational skills to their coursework and research
• Make programming more accessible and less intimidating
• Provide expert guidance on research tools, methods, and technologies
• Foster inclusion by supporting students from all backgrounds, especially those historically underrepresented in technology and data-focused disciplines

The Murty Sunak Quantitative and Computing Lab (QCL) at Claremont McKenna College is a campus-wide resource center providing comprehensive support in:

• Mathematics
• Computation
• Statistics
• Programming
• Data Analysis and Visualization

The QCL is committed to integrating computer and data science into the full range of liberal arts disciplines, including the social sciences, sciences, and humanities. We aim to help students build and apply quantitative literacy across all academic fields—from economics to biology, from political science to philosophy.

We hire and train a team of highly skilled undergraduate tutors (QCL Mentor) to support students through:

• One-on-one tutoring sessions (by appointment)
• Drop-in hours for quick help with coursework
• Support across a range of quantitative subjects and programming languages

All CMC students and 5C students enrolled in CMC quantitative courses are eligible.

We offer regular, hands-on workshops on foundational topics such as:

• Programming languages (e.g., Python, R, MATLAB)
• Data analysis techniques
• Statistical modeling and visualization tools

Our workshops are designed to be inclusive and beginner-friendly, ensuring participants learn at a comfortable pace.

QCL directors and graduate fellows provide consulting for:

• Senior thesis projects
• Faculty research
• Quantitative and computational approaches across disciplines

We also offer access to high-performance computing resources and guidance on advanced tools and methods for research and teaching.

LaTeX: Equation Writing (Level 1) https://cmc-qcl.github.io/Equation-Writing-with-LaTeX/
Python: Programming Basics Part 1 (Level 1) https://cmc-qcl.github.io/python-basics/
Python: Programming Basics Part 2 (Level 1) https://cmc-qcl.github.io/python-basics/
Python: Manipulating Data - Level 2 https://cmc-qcl.github.io/python-data-manipulation/
R: Programming Basics (Level 1) https://cmc-qcl.github.io/RProgrammingBasicsLevel1/
R: Data Exploration (Level 2) https://cmc-qcl.github.io/QCL-Workshop-Data-Wrangling-with-R-Level-2/
SQL: Setting Up Databases using DBeaver - Part 1 (Level 1) https://cmc-qcl.github.io/Introduction-to-SQL-DBeaver-Pt1/
SQL: Getting Insights from Databases using DBeaver - Part 2 (Level 1) https://cmc-qcl.github.io/Introduction-to-SQL-DBeaver-Pt2/
GIT: Version Control for Beginners (Level 1) https://cmc-qcl.github.io/Intro_GIT/
ArcGIS Online: Exploring GIS Libraries (Level 1) https://cmc-qcl.github.io/GIS/
STATA Bootcamp (Level 1)
Excel: Exploring Data (Level 1) https://cmc-qcl.github.io/Excel_Level_1/
Excel: Conditioning Data (Level 2) https://cmc-qcl.github.io/Excel_Level_2/
Tableau: Visualization (Level 1) https://cmc-qcl.github.io/Intro-Tableau-L1/

Murty Sunak Quantitative and Computing Lab
Claremont McKenna College
850 Columbia Avenue
Claremont, CA 91711

Phone: (909) 607-3666
Email: qcl@cmc.edu

Campus Location:
Kravis Center, Lower Court 26
888 Columbia Avenue
Claremont, CA 91711

Find the way to the QCL

For more information, or to schedule a consultation or workshop, please contact us at qcl@cmc.edu.