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Fall 2024: First half-semester: 9/4/2024 - 10/21/2024
TECH-UB 26 003 Monday-Wednesday  2:00-3:15 PM

TECH-UB 26 004 Monday-Wednesday 3:30-4:45 PM

Undergrad concentration: Computing and Data Science

Undergrad tracks:

This course is the recommended first course for undergrads who 1) want to work in the rapidly growing fields of data science and data analytics or 2) want to acquire the technical and data analysis skills needed in other disciplines, such as finance and marketing. The course covers data organization, storage, and retrieval of structured (record-based) data using SQL.

Course Objectives

The course will teach you SQL at a very high level. After this course, you should be able to:

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Module 1: Entity-Relationship Model and Relational Databases

Module 2: Selection Queries

Module 3: Filtering Queries

Module 4: JOIN queries

Module 5: Aggregate queries

Module 6: Subqueries

Module 7: Window queries

Projects follow-up course

There is a follow-up course titled “Projects in Programming for Data Science”, which covers the topics covered here in more depth as well as additional topics, such as web crawling, text analysis, regular expressions, background processing, visualizations, network analysis, etc. Those interested in deepening and broadening their programming experience are highly encouraged to take the follow on course.



Important Information

Since this is a hands-on course, you must bring your laptop to every class with sufficient battery charge. Make sure you can connect to NYU wi-fi.

Attendance and penalty for missing classes

Requiring attendance is necessary for several reasons. First, you incorrectly assume you can catch up on a missed class by watching a recording (if available). Videos do not engage your brain as much as a live class. Second, less than 20% of you watch the recording (if available). You are then lost in class, which provides wrong signals to me as an instructor. Third, your absence hurts class discussions. Fourth, you miss out on feedback if you do not work through the questions I pose in class. Fifth, I lose the feedback since there are fewer questions.

The policy below will be in effect only after the add/drop period.

Without mandatory attendance, attendance is often below 50%. Therefore, though I dislike doing this, I penalize absences. If you anticipate being absent for good reasons, please email me well in advance. Please enter "Excused" on the attendance sheet described below to avoid the penalty if I approve. If you miss a class due to emergencies and cannot tell me in advance, do not panic. Take care of the emergency first, and then email me. I will permit you to change the "Absent" to "Excused." But, if you miss a class without a valid reason, there is a penalty, as stated below.

For sections meeting in 150-190 minute sessions, you will lose one grade (A to A-, A- to B+, B+ to B, B to B-, and so on) for EVERY missed session unless you were explicitly excused via email. Thus, if you miss two class sessions, you will lose two grades, and so on.

For sections meeting in 75-80 minute sessions, you will lose one grade (A to A-, A- to B+, B+ to B, B to B-, and so on) for EVERY TWO missed sessions unless you were explicitly excused via email. Thus, if you miss four class sessions, you will lose two grades, and so on.

Please sit in the same seat in every class and display your name tags. For Zoom classes, you must keep your video on AT ALL TIMES. You must also have a good working headset or mic, as it is extremely rude to be inaudible and force me to ask you to repeat yourself. After entering the class, please mark yourself present in the first 20 minutes on the OneDrive sheet (link posted on Brightspace). You will be marked absent if you are more than 20 minutes late unless it is because of factors beyond your control (traffic, subway, interviews running late). You will also be marked absent if you leave the class early unless you have my permission or get it afterward. You will get an F in the course if you are caught cheating on the attendance sheet.


Late Assignment Submission Policy

Late submissions (even by 1 minute) will get a zero score because the answers will be posted immediately after the due date and time. No extensions will be granted except for medical or family emergencies. If you have any religious or personal conflicts, please submit the assignments beforehand since the related material will be covered well in advance of the due dates.


I will distribute Jupyter notebooks. There is no required textbook for the course, but the following books are a useful reference for some of the material that I will be covering in class.

Course policies

Unless otherwise noted, we follow the default Stern Policies. Classes are videotaped and a link is posted to NYU Brightspace under the MediaSite tab.