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Course Objectives

After completing this course, students should be able to:

create a simple webpage;
store and access data in JavaScript arrays and objects;
write programs that include for loops, if statements, functions, and events;
create circles, rectangles, groups and paths with SVG;
create circles, rectangles, groups, paths, and axes with D3;
find areas under normal curves;
generate samples of normal random variables;
plot points;
graph lines;
find distance of a point to a line;
fit a line to a collection of points;
recognize overfitting;
predict with linear regression;
employ a test set to evaluate model effectiveness;
classify with confusion matrix;
create a ROC Curve;
calculate probability, odds, and log-odds;
predict probabilities with logistic regression;
calculate log-loss.

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Tentative Schedule

Date	Topic
August 19 Via Zoom	Intro to Observable Notebooks
August 21 A	Intro to HTML
August 24 B	Intro to CSS
August 26 A	Arrays and Javascript Objects
August 28 B	`for` Loops
August 31 A	Intro to SVG
September 2 B	More on SVG
September 4 A	Intro to D3
September 7 B	More on D3
September 9 A	Inputs
September 11 B	Scales and Axes
September 14 A	Functions
September 16 B	Events
September 18 A	`if` Statements
September 21 B	Transitions
September 23 A	More on Randomness
September 25 B	Normal Curves
September 28 A	Midterm Practice
September 30 B	Midterm Practice
October 2	Midterm 1
October 5	Midterm 2
October 7 A	Plotting Points
October 9 B	Lines
October 12 A	Vertical Distance to a Line
October 16 B	Linear Regression
October 19 A	How Close is the Line?
October 21 B	Overfitting
October 23 A	Test Sets
October 26 B	Prediction
October 28 A	Classification Vs. Regression
October 30 B	Logistic Regression
November 2 A	Confusion Matrix
November 4 B	Confusion Matrix
November 6 A	AUC-ROC Curve
November 9 B	AUC-ROC Curve
November 11 A	Logarithms
November 13 B	Probability, Odds, Log-Odds
November 16 A	Sigmoid Function
November 18 B	Log-Loss
November 20 A	Final Practice
November 23 B	Final Practice

`33:[] 2f:{"title":"Intro to Data Science Syllabus (Full Semester)","cells":[{"id":0,"value":"md`# Intro to Data Science Syllabus (Full Semester)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"html`\n

Instructor Information

Name: Dr. Charles Redmond
Phone: 814-969-2269
Email: credmond@mercyhurst.edu
Office Hours: By Appointment via Zoom

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Course Description

For students in any discipline wishing to develop data science skills. We will examine several aspects of the data science workflow, including transformation of data, exploration of data, data modeling, and data visualization. Participants will gain experience with a variety of data science technology. Possible topics include basic programming, data visualization, and machine learning.

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Software and References

There is no textbook for the course. If you need references, I can provide them upon request.

Our major software tool for the course will be Observable Notebooks. You will not need to install anything on your computer.

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Grading

\n\n

We will have homework assignments, each of which will be a JavaScript Observable Notebook which you will construct. We will also have a midterm and a final. Each exam will consist of three programming challenges of varying difficulty level. You will be given a grade between 0 and 3, based on the highest level question you complete. The exams will be open note. You can use the sliders below to determine what must be accomplished to achieve each letter grade.

\n ${viewof hw}\n ${viewof midterm}\n ${viewof final}\n

\n${grade}\n

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ADA

Mercyhurst University is committed to making reasonable accommodations for qualified students, and employees with disabilities as required by law. Individuals seeking an accommodation for a disability must submit a written request outlining the specific accommodation request being made. Supporting documentation may also be required. To request an accommodation, contact Alice Agnew, Director of Equal Opportunity Programs, 311 Egan Hall, aagnew@mercyhurst.edu, 814-824-2362.\n.

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Title IX

Sexual Misconduct/Sexual Harassment Reporting—Mercyhurst is committed to providing an environment free from sex discrimination, including sexual harassment and sexual violence. Please refer to the Title IX – Sexual Respect button on the HUB for more information. If you would like to file a sexual misconduct complaint, please contact Mercyhurst Title IX Coordinator Alice Agnew, 311 Egan Hall, aagnew@mercyhurst.edu, 814-824-2362. Please be aware that in compliance with Title IX educators must report incidents of sexual assault/harassment, stalking, and domestic/dating violence. If you disclose any of these situations in class, in papers, or to me personally, I am required to report it to the Title IX Coordinator (or any of the Deputy Title IX Coordinators).

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Masks

As per the COVID-19 Prevention, Mitigation, and Response Policy, Mercyhurst University is requiring that all members of the campus community wear a cloth or disposable face covering over their nose and mouth when on campus. Please refer to the policy for specific details as to where and when face coverings are required. Students may use their own face coverings or those provided by the University. A student in need of a face covering should email covid19@mercyhurst.edu or call 814-824-3600 to find \n\nthe nearest location where face coverings are available. The University’s Mask/Face Coverings Policy will be enforced in this class.

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Sanitation and Safety

In keeping with the COVID-19 Prevention, Mitigation, and Response Policy, students are expected to use hand sanitizer and to wipe down their desks using disinfectant wipes when they enter and exit the classroom. Classrooms have been provided with sanitizer and disinfectant wipes for student and faculty use.

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Eating and Drinking in the Classroom

In light of the COVID-19 situation, Eating is not permitted in classrooms, labs, or other academic spaces. A water bottle or cup with a lid, and straw preferably, is permitted to be used in classrooms and labs to help prevent a student from becoming uncomfortably parched. Masks should be pulled only slightly away from the bottom of the face to take a quick drink and immediately replaced to covering the mouth and nose.

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Class Dismissal/Congestion Prevention

In keeping with the COVID-19 Prevention, Mitigation, and Response Policy, faculty members and students should take steps to avoid crowding outside of classrooms, in hallways, and any enclosed area in university buildings. All rooms will be designated with signs indicating maximum capacity for specific instructional use. These must always be adhered to. Students waiting to enter classrooms or exiting classrooms should always maintain a minimum of 6 feet of distance from others. Class time endings may be adjusted when necessary to minimize overcrowding or congestion.

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Seating Chart

In compliance with federal and state regulations, the University must be able to conduct contact tracing if there is a positive test or an outbreak; therefore, seating charts are mandatory for all in-person classes. Students will be required to sit in the same seat in the classroom each time they attend class. The seating chart will be available for review for purposes of contact tracing.

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Missed Classes

All class material, including lectures, will be available online. If you miss class, you can access the information online.

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A/B Days

Each student will be assigned to either the A group or the B group. You may only attend class face-to-face on the days designated for your group. These are indicated on the schedule.

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Paper Sharing

No paper will be shared in this course, whether it be between students or student and professor. Everything will be submitted digitally.

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Academic Honesty

Academic Honesty\n- Students are required to uphold academic integrity\nthroughout the course. In particular, plagiarism of any sort, unauthorized collaboration on exams, quizzes and other assignments, and other incidences of\nacademic dishonesty will be handled according to the policies set forth in the\nStudent Handbook.

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Student Ratings of Instruction

Near the end of the semester, you will be asked to complete an online course\nevaluation. The evaluation will be completed in class during the last two weeks\nof the semester using any laptop, tablet, or mobile device. The response tool\nallows you to note aspects of the course that helped you learn, as well as aspects\nthat might be modified to help future students learn more effectively. You will\nreceive an email letting you know when the evaluation window for our class is\nopen. Please note that these course evaluations are anonymous and instructors\ndo not see the results until after the grades for the course are submitted.

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Appendix

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"import {slider,button,select,text,radio,checkbox,number} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":39,"value":"viewof hw = slider({min:0,max:1,step:.01,format:\".0%\",description:\"homework\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":41,"value":"viewof midterm = slider({min:0,max:3,step:1,description:\"midterm\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"viewof final = slider({min:0,max:3,step:1,description:\"final\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":45,"value":"grade = {\n const assignments = hw\n const exams = (midterm + final)*.1\n const score = assignments + exams\n let grade = \"\"\n if(score >= 1.5){grade = \"A\"}\n else if(score>=1.3){grade = \"B+\"}\n else if(score>=1.1){grade = \"B\"}\n else if(score>=.9){grade = \"C+\"}\n else if(score>=.8){grade = \"C\"}\n else if(score>=.7){grade = \"D+\"}\n else if(score>=.6){grade = \"D\"}\n else{grade = \"F\"}\n return grade\n}","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}