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Campus | Bryn Mawr |
Semester | Fall 2020 |
Registration ID | DSCIB100001 |
Course Title | Introduction to Data Science |
Credit | 1.00 |
Department | Neuroscience |
Instructor | Thapar,Anjali |
Times and Days | MTh 02:40pm-04:00pm
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Room Location | |
Additional Course Info | Class Number: 2129 “Data science” is a catch-all term used to describe the practice of working with and analyzing messy data sources to draw meaningful conclusions. This course provides a broad introduction to the field of data science via the statistical programming language, R. Over the semester, students will learn how to manipulate, manage, summarize and visualize large data sets. No previous exposure to programming or statistics is expected.; Welcome to Introduction to Data Science. “Data science” is a catch-all term used to describe the practice of working with and analyzing messy data sources to draw meaningful conclusions using techniques developed by computer scientists and computational statisticians. The goal of this course is to introduce students to the field of data science via the R programming environment. Over the semester students will acquire skills for working with and making informed decisions based on real-world data. Students will learn to manipulate data objects, produce advanced graphics, tidy and wrangle data, and generate reproducible statistical reports using R markdown. Students will also have the opportunity to practice professional skills such as communication, teamwork, problem solving, and critical thinking. If you are a learner who is interested in making sense of (sometimes messy) data and who has little to no background in data science, statistics, or programming, this course is for you! We will use two online free textbooks and supplemental readings uploaded to the course Moodle page. Assessment will consist of weekly low-stakes reading mastery activities to ensure that students are keeping up with the material, homework assignments, two group projects and class/collaborative participation. Participation in weekly Zoom sessions (Thursday 2:40-4:00 pm EST) is required. For more information or to see a draft of the syllabus, please email me (athapar@brynmawr.edu). Approach: Course does not meet an Approach, Quantitative Readiness Required (QR); Haverford: C: Physical and Natural Processes (C), B: Analysis of the Social World (B) Enrollment Cap: 40; Freshmen Spaces: 5; If the course exceeds the enrollment cap the following criteria will be used for the lottery: Senior; Junior; Sophomore; In fall 2020, I am offering this course in a fully remote format that includes both synchronous and asynchronous elements. I will employ a flipped classroom approach, whereby students will engage with the content (video lectures, readings) asynchronously on their own time and at their own pace. We will use the scheduled class time for synchronous meetings to complete in-class activities and exercises to facilitate mastery of skills using R. Weekly content (recorded video lectures) will be posted on Moodle for the following week. On Monday during the scheduled class time (2:40 pm EST), I will host an optional (but strongly encouraged!) synchronous Q&A session on Zoom to address any questions that students have on the assigned material. On Thursday during the scheduled class time (2:40-4:00 pm EST), I will host required synchronous sessions. We will use Zoom breakout rooms and students will work in small groups to complete application activities. It is my expectation that students will be available for synchronous gatherings on Thursdays during the scheduled class period. If this is a challenge for you because of a difference in time zone, please be in touch with me (athapar@brynmawr.edu) before registering for the course. |
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