The goal of the course is to provide students with an introduction to basic statistical techniques for analyzing numerical or quantitative data. New York City College of Technology serves the city and the state by providing technically proficient graduates in the technologies of the arts, business, communications . CUNY's online tuition for students outside New York is affordable. Students can enroll in up to three 1-credit lab courses. Students will gain a working knowledge of web mapping foundations and survey the current state of the FOSS ecosystem. Credit for Non-Collegiate Learning | CUNY School of Professional In addition, the class covers the following topics: ProfessorMichelle McSweeney Using web-based technologies including HTML, CSS, and D3.js, students will learn to create engaging and effective information displays, grounded in the science of visual perception and best practices in visual mapping and accessibility. These are typically acceptable to use for applications that ask for an unofficial or student copy of a transcript. This is an applied machine learning class, which emphasizes the intuitions and know-how needed to get learning algorithms to work in practice, rather than mathematical derivations. +1 212-817-7000, Click to expose navigation links on mobile, Collaborative and Interdisciplinary Programs, Career Planning and Professional Development, Student Consumer Information/Right to Know, More in Curriculum and Degree Information, DATA 78000 - Special Topics: Software Design Lab: Creative Computing, DATA 70600 - Special Topics in Computational Fundamentals: JavaScript (6:30 - 7:30 PM). We will explore a wide range of technological situations from design practices to public policy, research, data privacy, social justice, platform development, data visualization, and artificial intelligence and consider what it means to develop technological innovations that center the communities they are designed to serve. Students can enroll in up to three 1-credit lab courses. To achieve these goals students will be introduced to the principles of probabilistic reasoning, sampling, experimental design, descriptive statistics and statistical inference. * understand both the benefits and limitations of using quantitative methods in research; Students can enroll in up to three 1-credit lab courses. Synchronous class dates: 5/31, 6/1, 6/2, 6/6, 6/8, 6/13, 6/15, 6/21, 6/22. In-person session dates: 3/30, 4/6, 4/13, 4/27, 5/4, 5/11. Activities and Organizations. The final project will be an interactive web map.Please note: An introductory level familiarity with HTML, JS, and CSS is required. Prof. Katherine Behar (Katherine.Behar@baruch.cuny.edu) After taking this course, students will be able to: Note: DATA 70500 satisfies as a Data Analysis distribution core course. Students will become familiar with thehistory and basic concepts of the fundamental paradigms developed by modern societies to analyze patterns in datastatistics,visualization, data mining, and machine learning. It is strongly recommended that students complete Interactive Data Visualization prior to taking this course, or have comparable experience with Javascript, HTML, and CSS. In-person, June 28th - August 4th And, importantly, how do the questions we are asking align with the methods we are using? Doctoral Programs Master's Programs Certificate Programs Collaborative and Interdisciplinary Programs Interuniversity Doctoral Consortium Preparing to Teach as a Doctoral Student Academic Calendar . We'll combine a critical view of data with examples that illustrate the logic of analysis. Data is everywhere and the ability to manipulate, visualize, and communicate with data effectively is an essential skill for nearly every sectorpublic, private, academic, and beyond. These developments have also led to the emergence of a number of new research fields in the end of 2000s: social computing, computational social science, digital humanities, cultural analytics, and culturomics. Cross-listed with DHUM 73000 You will have an opportunity to work with common JavaScript libraries/tools. 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. This course will introduce students to the tools, skills, and concepts necessary for making state-of-the-art interactive data visualizations. They will learn about different data types; what constitutes a valid dataset that can be analyzed quantitatively; how data should be formatted to create a valid dataset. Hybrid,Room 3207 A portion of the semester will also consist of a series of advanced technical workshops. Social Science - Data Analytics in Economics/BS - City Tech For qualitative data, a person with content and thematic analysis experience will be very helpful in identifying themes and commonalities. . Monday, 6:30 - 8:30 PM, 3 Credits, Prof. Aucher Serr (aucher.serr@gmail.com) DATA 71200 satisfies as a Data Analysis distribution core course We will dive into cleaning and structuring unruly data sets, identify which chart types work best for different types of data, and unpack the tactics behind effective visual communication. Thursday, 4:15 - 6:15 PM It is strongly recommended that students complete Interactive Data Visualization prior to taking this course, or have comparable experience with Javascript, HTML, and CSS. Virtual session dates: 2/2, 2/9, 2/16, 2/23, 3/2, 3/9, 3/16, 3/23. Using Tableau Software, students will build a series of interactive visualizations that combine data and logic with storytelling and design. Then well take a look at some of the tools used by data analysts to produce knowledge in various settings, including survey data, demographic data, social media (text analysis), and other forms of open data relevant to public policy and other applied settings. Student Services Directory. Additionally, it is recommended that students feel comfortableworking with git-based version control (Github, Gitlab. The data revolution is here. * interact with geospatial data stored in a database; 1-877 . Students will explore how software can be used as a creative medium, and how it can be integrated into their existing research or technical practices. Students will be expected to participate in class discussions, contribute to a weekly course blog, to present an oral presentation on a data case study (e.g., Cambridge Analytica, net neutrality, EUs Right to Be Forgotten, Edward Snowden, Amazon Alexa, or the Memex), and to write a final research paper. One-Stop Services. Using Tableau Software, students will build a series of interactive visualizations that combine data and logic with storytelling and design. Certificate Programs. With an eye towards critical evaluation of both data and method, projects and discussions will be geared towards humanities and social science research. Using web-based technologies including HTML, CSS, and D3.js, students will learn to create engaging and effective information displays, grounded in the science of visual perception and best practices in visual mapping and accessibility. These readings will be supplemented with articles, white papers, and project reports on the economics and politics of public infrastructures and funding (e.g. Sample topics include artificial intelligence, database management, algorithms for big data, social network analysis, and natural language processing. Contact. The emphasis throughout will be on the development of statistical reasoning, i.e., thinking like a data scientist. This course will introduce students to the tools, skills, and concepts necessary for making state-of-the-art interactive data visualizations. We will also discuss possibilities, limitations, and implications of using big data-centric methods in social science and humanities research, and the already developed work in computational social science, digital humanities and cultural analytics fields. Cross-listed with DHUM 70600 These assignments will bediscussed and analyzed in class. It is strongly recommended that students complete Interactive Data Visualization prior to taking this course, or have comparable experience with Javascript, HTML, and CSS. In-person Topics covered include, Data Acquisition, Geo-Processing, Data Visualization, Cartography, Spatial Statistics, and Web-Mapping. Regardless of academic concentration, students develop a portfolio of interactive and dynamic data visualization dashboards and an interdisciplinary skill set ready to leverage in academic and professional work. In addition to readings and models of newperspectives on data visualization, students will complete experimental projects visualizing a variety oftexts, which may include condensing feature films to single images, comparative movie barcodes,glitching historical images, and other experimental exploratory data visualization. Courses | CUNY Graduate Center In Person,Room 5382 The GIS for Public Health course will offer students an opportunity to gain skills in using GIS software to apply spatial analysis techniques to public health research questions. We will ask questions such as, "Can you 'lead a feminist life' (Ahmed) that is heavily mediated by methods of text analysis?" Google is offering its Data Analytics Certificate program to help students prepare for jobs in one of the nation's fastest growing fields . This course has a very hands-on approach, and students are expected to engage with exploratory analysis both in the class and out of the class. , students will begin with basics of working with data"cleaning" data, preparing it for analysis, and working with a variety of data formats. * use cartographic theory to design effective graphical representations of geospatial data; Build interactive data visualization dashboards that answer a clear and purposeful research question; Choose which chart type works best for different types of data; Iterate with fluidity in Tableau Software leveraging visualization, aesthetic, and user interface best practices; Structure thoughtful critiques and communicate technical questions and solutions; Leverage collaborative tools, including Tableau Public, Wordpress, and repositories of public data sets; Contribute to the broader conversation about digital practices in academic research; Critically read a wide range of chart types with an eye for accuracy, audience, and effectiveness; Identify potential weaknesses in the collection methods and structure of underlying data sets Locate the original source of a visualization and its data. Practical topics will include: descriptive and inferential statistical methods, sampling and data collection, and an array of statistical modeling techniques such as correlational analysis, multivariate regression, logistic regression, and exploratory data analysis. We will also discuss possibilities, limitations, and implications of using big data-centric methods in social science and humanities research, and the already developed work in computational social science, digital humanities and cultural analytics fields. The course's main text will be the O'Reilly book "Introduction to Machine Learning with Python" by Sarah Guido and Andreas C. Mller, along with the book's corresponding Jupyter notebooks. Note: This is a 1-credit summer lab course. We will first learn principles of descriptive statistics. and "What does it mean to do computational text analysis in a humanities context?" Tuesday, 6:30 - 8:30 PM, 3 Credits. GRE is not required, but can be submitted in . The courses's main text will be the O'Reilly book "Introduction to Machine Learning with Python" by Sarah Guido and Andreas C. Mller, along with the book's corresponding Jupyter notebooks. DATA 71200 satisfies as a Data Analysis core course. Department: Data Analysis and Visualization - Graduate Center Catalog The Data Science and Engineering (DSE) program at CCNY provides a solid foundation in core data science and engineering skills . By the end of this class, students will be able to: Texts:Mastering ArcGISby Maribeth H. Price Seventh Edition. An associate's degree requires approximately 60 college credits while a bachelor's typically requires 120 college credits. prior to starting this course. Large language models (LLMs) such as ChatGPT and Bard have demonstrated an uncanny ability to interpret and generate text, and with that, the potential to revolutionize industries and reshape society. Cross-listed with DHUM 70600 Well begin with a broader examination of data and society. Data Science and Engineering are multidisciplinary fields that apply tools and methods from computer science and statistics to other knowledge domains. Topics covered include: HTML/CSS/Javascript, interactivity, and APIs. The data revolution has transformed the way we understand and interact with the world around us. Advanced Certificate in Disability Services in Higher Education. IS 210, IS 211, IS 361, IS 362. Follow me Online. prior to starting this course. This course combines an introduction to basic cartographic theory and techniques in humanities contexts with practical experience in the analysis, manipulation, and the graphical representation of spatial information. As employers in every sector continue to search for candidates that can turn their data into actionable information, this course is designed to demystify data analysis by approaching it visually. The goal of the course is to provide students with an introduction to basic statistical techniques for analyzing numerical or quantitative data. Google. Students will complete a total of 12 credits across four courses: +1 877-428-6942 Throughout the semester, students will work towards creating a portfolio of beautiful and analytically sound data visualizations, while also developing their own iterative design process. Using Tableau Software, students will build a series of interactive visualizations that combine data and logic with storytelling and design. CUNY 2800 Victory Boulevard Staten Island, NY 10314 US. Data visualization techniques allow people to use perception and cognition to see patterns in data, and form research hypotheses.
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