CADS Semester Project | Intro to Data Science and Visualization
Are you interested in data science and looking for a way to add to your technical portfolio? Are you interested in learning the basics of working with data sets in R, Tableau, and SQL? Then consider joining our CADS Semester-long Project Team! The CADS Semester Project in Data Science will take place during the current Spring 2021 semester. All freshmen and sophomores who are interested in data analytics and visualization are encouraged to apply! This project will require a time commitment of 1-2 hours per week. We will hold bi-weekly lecture meetings to teach material on the basics of using R. Some of the topics that we will cover include:
- Setting up your Working Directory and working with the R interface
- Importing data sets into R -Introductory regression and statistics
- Modifying data frames in R
- Cleaning Data -Data Visualization using ggplot2
After every lecture, your team will be assigned a specific task to complete for the week. Students will be encouraged to ask questions during the meetings, come to our office hours, and hold their own team meetings to work on their projects. The expected final product is a completed report that will be added to your personal technical portfolios. These portfolios will be very important for your internship interviews!
Please note that the content that will be covered in this project will be introductory material. If you have already taken STOR 320 or STOR 445, you will already be familiar with most of the material that will be taught. If you have any further questions, please email email@example.com or firstname.lastname@example.org
Applications are now closed.
Data Journalism Mentorship Program | DJMP
The Data Journalism Mentorship Program is a collaborative between CADS and the Hussman School of Journalism and Media. Directed by Professor Ryan Thornburg, CADS Co-President Amber Amparo, and CADS Social Chair Manas Takalpati, this mentorship program grants students the opportunity to participate with peers under numerous roles (data cleaning, visualization, analytics, synthesizing conclusions in writing) as they bring the hidden stories of a data set to light. This semester-long program allows participants of all levels of knowledge in data science and/or journalism to hone in and develop technical and collaborative skills essential for future endeavors.
Ben Lu | Project Lead
- Provide a learning platform for all skill-levels in a team-learning environment
- Teach useful python techniques and apply them to the data set for hands-on experience
- Take on projects you are interested in to learn new concepts as well as apply old ones
- Provide a curriculum with less intimidating schedule for members to learn Python
Tar Heel Reader
Jacob McCright | Project Lead
Tar Heel Reader is a web-based accessibility reader located at tarheelreader.org. The website aims to help children, the developmentally disabled, and foreign-language speakers learn to read. Each “book” is user-created with a picture per page accompanied by 1-3 sentences. There are roughly 60,000 books currently on Tar Heel Reader being read by users world-wide. Recently THR surpassed 10 million reads!
The THR project has many possibilities. There is a massive wealth of data which we have access to thanks to its creator, Dr. Gary Bishop, a professor at UNC. The team has finished the first iteration of a recommendation system to recommend books to readers kind of like how Netflix recommends movies. Now we are trying to measure the quality of these recommendations and find a way to auto-tag the genre or category of the books to help search functionality. The directions you can go with this project are broad and up to you if you would like. From natural language or image processing, to search optimization, and machine learning classification this project is very exciting!
This project is about learning by doing and we are always happy to welcome new members to the team! This is a great opportunity to have something real and tangible to show your passion and hard-work in Data Science.
High School Outreach
Kunal Lodaya and Vikram Aikat | Project Leads
The High School Outreach program consists of a series of workshops developed and taught by current UNC students, and is intended for high school students with an interest in mathematical modeling competitions. Specifically, we are aiming to prepare current sophomores and juniors to compete in the High School Mathematical Contest in Modeling this upcoming fall.
This spring, we plan to host high school students on UNC campus for a series of workshops; these will focus on team-based problem solving, developing computational and analytical models, and writing rigorous solution papers. In particular, emphasis will be put on communication – both in technical paper writing, and non-technical summarization of models. All of these skills will apply directly to competitions in mathematical modeling, and will be supplemented by additional material for the summer and a series of shorter workshops in the fall.