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Late assignments, exams, or projects are not accepted.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},430094,1791155961,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":39,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":46},13056703020460,"https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923","Fall Quarter 2020 Mak Ahmad  \nBAX 431: Data Visualization  \nInstructor: Mak Ahmad, Adjunct Professor  \nPhone: (415) 935-3188  \nEmail: [shahmad@ucdavis.edu](shahmad@ucdavis.edu)  \n[Office Hours:](Office Hours: By appt)[ By appt](Office Hours: By appt) (over VC)  \nCourse Description  \nCourse topics include an overview of vocabulary, theory and principles as well as the algorithmsand methods for structured and unstructured data visualization. The course will teach students how to present information in an understandable and efficient way for the purposes of data analysis and effective communication of results. The course also empowers students to critically analyze good and bad visualizations, and develop ways to improve on them.  \nCourse Objectives  \nData visualization is a particularly broad field of study, with research areas ranging from computer science to human-computer interaction to visual design. The goal of this course is to offer students a solid foundation in visualization theory and principles, and then help them apply this knowledge in weekly projects and workshops aimed at developing their skills in creating and evaluating data visualizations. Sessions will cover major areas of visualization including studies of visual perception; time-based, categorical, and geospatial analysis; graphs and networks; and visual storytelling, as well as the practical creation of visualizations using tools including Tableau, Salesforce Einstein Analytics, Python and Looker.  \nLearning Objectives  \n● Understand basic principles of data visualization  \n● Evaluate and think critically about data visualization examples  \n● Create effective visualizations for data analysis and presentations using a range of tools  \nClass Rules  \nAcademic Honor Code: All students are expected to adhere to the University of California, Davis’Code of Conduct as noted here: [http://sja.ucdavis.edu/fi](http://sja.ucdavis.edu/fi)les/cac. pdf. Please also note that if“academic misconduct is admitted or is determined by adjudication to have occurred,” per Regulation 550 the student could potentially receive a grade of “F” not only for the assignment or project in question, but also for the entire course.  \nFall Quarter 2020 Mak Ahmad  \nUse of Electronics in Class: You are allowed to use your laptop/tablet in class – however this use is conditional. You cannot use your laptops for any other activity other than those pertaining to the class. Hence, surfing, emailing, chatting, facebook visits and other related activities are not allowed. If such activity is observed in class, then laptop privileges will be revoked – for the entire class. Smartphone/phone use is not allowed in class – you are welcome to step out of class, with my permission, if you need to answer a call. Failure to comply with this policy will result in the creation of ‘laptop zones’ (e.g., only the first two rows will be allowed to use laptops) .  \nCourse Material  \nOptional Texts  \n● Now You See It, Stephen Few  \n● The Visual Display of Quantitative Information, 2nd Ed, Edward R Tufte  \n● Information Visualization, Perception for Design, Colin Ware  \n● Visualizing Data, Ben Fry  \n● The Functional Art, Alberto Cairo  \n● How Maps Work, Alan M. MacEach ren Grading  \n● 10% Class Participation  \n● 50% Assignments  \n● 25% Team Project  \n● 15% Final Exam  \nNOTE: Late assignments, exams, or projects, will not be accepted.  \nAssignments  \nSee Canvas for details.  \nTeam Project  \nSee Canvas for details.  \nFall Quarter 2020 Mak Ahmad  \nLecture Outline  \nLecture \\#1: Introduction to Data Visualization  \nTheory  \n● We will cover principles of data visualization, including how to model human perception in information visualization research, mapping from data types to visual marks and channels, and a taxonomy of visualizations, the process of visualization ( Ben Fry, Visualizing Data, 2018), and laying out the fundamentals for the rest of t he course.  \nPractice  \n●  Download and install Tableau Desktop  \n●  Dow","cbCaifZTsYDzkYdU","https://ap.wps.com/l/cbCaifZTsYDzkYdU","pdf",103390,"English","# Course Description\n## Course Objectives\n## Learning Objectives\n## Class Rules\n## Course Material\n## Grading\n## Assignments\n## Team Project\n## Lecture Outline","[{\"question\":\"What topics are covered in BAX 431 Data Visualization?\",\"answer\":\"The course covers visualization theory and principles, mapping data types to visual marks and channels, and visual analytics areas such as visual perception, time-based/categorical/geospatial analysis, graphs and networks, and visual storytelling.\"},{\"question\":\"Which tools will students use to create visualizations?\",\"answer\":\"Students will work with tools including Tableau, Salesforce Einstein Analytics, Python, and Looker, along with practical creation and evaluation of visualizations through weekly projects and workshops.\"},{\"question\":\"How are students assessed and what are the late submission rules?\",\"answer\":\"Grading includes class participation (10%), assignments (50%), team project (25%), and a final exam (15%). Late assignments, exams, or projects are not accepted.\"}]","BAX 431: Data Visualization - Fall Quarter 2020 | PDF",1790651899]