Please note that this schedule is tentative and subject to change.
|4:15 - 6:15 PM
6:30 - 8:30 PM
Data Analysis Methods
DATA 71000 - Data Analysis Methods CRN # 59983
Wednesday, 6:30 - 8:30 PM, 3 Credits, Rm. TBA, Prof. Mariya Bessonov (MBessonov@citytech.cuny.edu)
The goal of this course is to provide students with an introduction to basic statistical techniques for analyzing data. Students will develop an understanding of concepts underlying modern statistics and statistical reasoning that will equip them with tools to analyze variety of data types and data sources and also visualize it. We will first learn principles of descriptive statistics. Next, we will cover principles and techniques of inferential statistics, and design of experiments. Students will explore various statistical measures and techniques for analyzing data, and practice applying this knowledge to real-world data problems. Practical topics include: descriptive and inferential statistics, sampling, experimental design, statistical models, parametric and non-parametric tests, ordinary least squares regression, logistic regression, and explorative data analysis.
DATA 75000 - Internship CRN # 59984 (CANCELLED)
Tuesday, 4:15 - 6:15 PM, 3 Credits, Rm. TBA, Prof. Matthew Gold (firstname.lastname@example.org)
The aim of the internship course is for students to gain valuable work experience through an internship in their chosen field and to afford students an opportunity to apply their academic knowledge in a professional environment. This course is composed of an internship (140 hours over the course of the semester) with weekly class meetings (predominately in person and several online). Students will be expected to relate their internship to their program of study and career goals through a series of assignments and presentations. Students will also work on their professional development, with workshops on career planning, resumes and cover letters, and the development of a web-based portfolio. Alumni from the program and speakers from non-academic sectors will discuss the role of internships in their careers. This course is restricted and students must apply via the online form before the semester starts. All questions about this course should be directed to Prof. Matthew K. Gold (email@example.com).
DHUM 73700 - Geospatial Humanities CRN # 59981
Thursday, 6:30 - 8:30 PM, 3 Credits, Rm. TBA, Prof. Jeremy Porter (firstname.lastname@example.org)
This course aims to familiarize students with GIS and spatial analysis tools and techniques used in the visualization, management, analysis, and presentation of geo-spatial data. The course will be a hand's on applied course in which students will learn to work with publicly available geo-spatial data in open-source software packages, including but not limited too: R, Python, QGIS, and CartoDB. Topics covered include, Data Acquisition, Geo-Processing, Data Visualization, Cartography, Spatial Statistics, and Web-Mapping.