NICO 101-0: Introduction to Programming for Big Data

Fall 2017 - Professors Luis Amaral and Adam Pah

Lectures: September 6-9 and 12-15 from 9:30am-12:00pm & 1:30pm-4:30pm in L361.

Overview: Our digital, connected, sensor rich world is generating extraordinary amounts of data ("Big Data") that are being used to purposes as diverse as teaching a computer to win at Jeopardy or offering taxi alternatives. The skills needed to go from data to knowledge and application, which go under the name of Data Science, are in big demand in industry, government, and academia. This course provides an introduction to the foundational skills needed by data scientists. Prior knowledge of programming is not needed.

Prerequisites: None.

Restrictions: Intended primarily for undergraduate students. Other students must contact the instructor. Students will need an up-to-date laptop running Linux, OS X, or Windows 7 or higher. Chromebooks will not be permitted. Prior to the start of the course, students must install several packages and verify that they run properly in their machine.

Texts: Lecture materials are available online.

Requirements: There will be about 6 homework assignments involving the writing of Python code for solving specific problems. Students’ solutions will be uploaded to a server where they will be unit tested. All students will be expected to attend lectures and complete in class assignments.

Visit CAESAR to register for the course.


Python for Programming and Data Science Workshops

NICO is excited to support the Python for Programming and Data Science Workshops which will run July 18 through August 17, 2017.

Being able to do programming and data science are useful interdisciplinary skills for any scientist. But learning these powerful, time-saving skills all by yourself might seem intimidating or sound like it could be a slow process. Our summer workshops will offer a concise, efficient introduction into to these skills, tailored specifically to PhD students and post-docs. At the end of our introductory series, you will be able to write your own Python code and feel comfortable manipulating and visualizing data sets and using databases. You’ll gain foundational skills as well as the confidence to do more with your data and further your research.

Our workshops aim to fill a skill gap that currently exists for PhD students and post-docs at Northwestern. We recommend undergraduates attend the two-week course NICO 101-0: Introduction to Programming for Big Data.

For more information and to register:


Data Science: A seismic shift changing how we research and learn

Northwestern News Special Feature, May 2016

A tidal wave of digital information has ushered in a new era of computing and analysis in the 21st century. Data science, or "big data," is affecting every aspect of Northwestern’s learning and research enterprises — among other things, leading to breakthroughs in precision medicine; contributing to a revolution in astronomy with profound insights about the universe; transforming the scope and depth of social science research with significant policy implications, and fueling research about consumer behavior that is affecting how companies do business.

Visit Northwestern News to read more.

Wherever you look, there is talk of the revolution being brought about by "Big Data." But is Big Data just a fad, as its critics contend, or is there something at its core that is here to stay with us?

Well before the term was coined, particle physicists were driven to Big Data challenges by the necessity of their large-scale detectors and produced datasets. Now however, we live in a world where not just the amount, but also the diversity and complexity of digital information continues to grow exponentially. Materials simulations and astronomy images are pushing the boundaries of exploration. Social networks enable the exchange of information between people; medical devices and e-commerce record the exchange of information between people and machines; GPS devices and bar code scanners allow the exchange of information between machines.