📖 Syllabus

Table of Contents

1. About 🧐
2. Communication 💬
3. Course Materials
4. Grading & Attendance
   1. Grading
   2. Grades
   3. Regrade Policy
   4. Lecture Attendance
   5. Section Attendance
5. Course Homeworks & Topics
   1. Homeworks
   2. Quizzes
   3. Exam
6. Other Good Stuff
   1. Teamwork Expectations
   2. Class/Web Conduct
   3. Academic Integrity
   4. Disability​ ​Access
   5. Questions & Feedback

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About 🧐

In today’s data-driven world, the ability to effectively manage, manipulate, and extract insights from data is crucial for solving complex problems across various domains. As data scientists, we don’t just work with pre-processed datasets; we need to understand how data is stored, organized, and retrieved efficiently. This is where data management comes into play.

In DSC 100, we’ll explore the fundamental concepts and techniques that form the backbone of data management in the context of data science. We’ll answer the critical question: “How do we effectively manage and leverage data for analysis and machine learning?”

Course Objectives:

1. Design and interact with relational databases using SQL, the lingua franca of data.
2. Understand database design principles, including normalization and indexing, to optimize data storage and retrieval.
3. Explore data quality and integrity issues, and learn strategies to address them.
4. Compare and contrast SQL and NoSQL approaches for different data science scenarios.
5. Apply data management techniques in real-world data science projects, preparing you for internships and jobs in the field.

By the end of this course, you’ll have a solid foundation in data management that will enhance your capabilities as a data scientist. You’ll be able to efficiently organize, query, and prepare data for analysis and machine learning tasks. Moreover, you’ll gain insights into how data management systems support and integrate with various data science workflows, from exploratory data analysis to model deployment.

Whether you’re working with structured data in relational databases or unstructured data in NoSQL systems, the principles you learn here will be invaluable throughout your data science journey!

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Communication 💬

This quarter, we’ll be using Ed as our course message board. You should be added to Ed automatically; if not, a link will be provided in class. Please join right away as we’ll be making all course announcements through Ed.

If you have a question about anything to do with the course — if you’re stuck on a problem, didn’t understand something from lecture, want clarification on course logistics, or just have a general question about data science — please make a post on Ed. If your question is about an active HW problem, please make your post private so that others cannot see it and include your thoughts, parts of an answer (even if you are unsure if it is correct), or what steps you have tried.

Course staff will regularly check Ed to answer questions. You’re also encouraged to answer questions asked by other students. Explaining something is a great way to solidify your understanding of it!

Please don’t email staff members (and don’t message them on social media); just make a private or public Ed post instead! I will not answer emails regarding course material/logistics, etc.

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Course Materials

• Although a textbook is not required in the course, the following textbook is optional and recommended: Database Systems: The Complete Book, by Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom. 2nd Edition. Prentice Hall. 2008.

• Lecture slides and recorded videos would be sufficient for this class.

• All course materials are provided through this website
• All course announcements will occur through Edstem.

Grading & Attendance

Grading

Here is the breakdown:

• Final exam date: No in class final exam, this exam will be done remote. And will be done by yourselves
• Your letter grade will be determined using the standard grading scale. Grades are not rounded up, that’s why we have included bonus points.
• Grading specifics for each assignment can be found on the Assignments page

  Grades

  Grades are released often a week after the submission date, typically sooner. Ultimately it is your responsibility to check your final grade and get in touch if you believe there is a problem.

Regrade Policy

The regrade policy is here to protect students from serious issues in grading, not to provide students with a platform to argue about, or plead for an extra point. A grader may incorrectly take off 1-2 points, but they are as likely to give students 1-2 points. In our experience less than 3% of the time a regrade results in a change. When we regrade, we closely go through the entire assignment again and reevaluate it as a whole. This means your grade can either stay the same, go up, or go down. This is not to discourage students from requesting legitimate regrades, but to discourage students from arguing about 1 point (which is worth 0.05% of your grade). These discussions require a serious investment of time. We want to spend that time on regrades where a serious issue has occurred, or with helping students learn the material outside of class.

If you think a grading error has occurred please follow these steps:

• You have 72 hours to request a regrade
• Initiate the regrade through Gradescope (if it is a group project, confer w/ your team first and submit one regrade after your team comes to a consensus)
• Provide evidence for why your answer is correct and merits a regrade (i.e. a specific reference to something said in a lecture, the readings, or office hours)
• We will get back to you within 48 hours with our final decision.

Lecture Attendance

Our goal is to make lectures, section and office hours worth your while to attend, e.g. we do many in-class exercises. However, lecture attendance is not required. We will make every effort to record lectures, but things happen. These will be made available to you (UCSD podcast).

Section Attendance

Section attendance is not mandatory. Demos as well as lecture material will be reviewed in the section and it is to your benefit to go and ask questions.

Course Homeworks & Topics

This class is designed to immerse you in the foundational aspects of database systems, a cornerstone in the world of data science. Databases are the backbone of countless applications and play a pivotal role in storing, organizing, and retrieving data efficiently. Through this course, you’ll delve into the core principles of database management, understand its significance in data-driven decision-making, and develop skills essential for any budding data professional. You will alsop learn the ins and outs of writing good effecient SQL code. Homeworks will cause you to dive deeper and immerse yourselves in the material.

Homeworks

There will be 5 homeworks consisting of written problem-solving and programming assignments. The purpose of the homeworks is to provide students with the opportunity to apply and practice the concepts and skills learned in the lectures. Homeworks will be rigorous and require students to demonstrate a deeper understanding of the material.

Late Day Policy: You have up to 3 late days to use on homework assignments. These late days can be used in 24-hour chunks. Late days are meant to be a safety net and should not be used as a convenience. It is expected that you will not need to use your late days and that you will submit all assignments on time. If you use all of your late days, it is likely that you are not managing your time effectively and will need to adjust your study habits. Please note that no excuses for not submitting assignments on time will be accepted once you have exhausted your late days. There is no need to inform us you will be using them. When we calculate your grade we will see how many late submissions you have, and how many days each submission is late. We will then provide you credit from your “3 late day pool”.

Note: Homework assignments can be completed in groups of 2 students. This means that you can work with one other student to complete the HW and submit a single solution. It is expected that each member of the team will contribute equally to the solution and have a thorough understanding of the material. Collaboration is encouraged as it can help deepen understanding and facilitate learning, but it is important that all team members understand the work being submitted and are able to explain it if necessary. Plagiarism and cheating will not be tolerated and will result in disciplinary action.

Quizzes

These will be short 8 question quizzes to ensure material is sticking and provide more opportunities to interact with the material. These should be straightforward if you are keeping up with your studying and are not intended to punish you. Quizzes are just our way to make sure you keep up with studying and do not fall too far behind. As this class really builds on each previous week.

Exam

The midterm exam will cover all topics up until Formal Query Languages. It will be held remote. There will be a review session with your TA/IAs. You must work alone.

The final exam will be comprehensive and will be held remote. You must work alone.

No late exams are permitted, except for extenuating circumstances. Please reach out to staff as early as possible if you know something will prevent you from taking the exam on time. The later you wait… the less likely we are to accept your request. We always consider “acts of God”, “family emergencies”, and situations completely out of your control, when providing extensions.

Other Good Stuff

Teamwork Expectations

Class/Web Conduct

In all interactions in this class, you are expected to be respectful. This includes following the UC San Diego principles of the community.

This class will be a welcoming, inclusive, and harassment-free experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), political beliefs/leanings, or technology choices.

At all times, you should be considerate and respectful. Always refrain from demeaning, discriminatory, or harassing behavior and speech. Last of all, take care of each other.

If you have a concern, please speak with Kyle or your TAs. If you are uncomfortable doing so, that’s ok! The OPHD (Office for the Prevention of Sexual Harassment and Discrimination) and CARE (confidential advocacy and education office for sexual violence and gender-based violence) are wonderful resources on campus.

Academic Integrity

Don’t cheat.

You are encouraged to (and at times will) work together and help one another. However, you are personally responsible for the work you submit (quizzes/exams). For assignments, it is also your responsibility to ensure you understand everything your group has submitted and to make sure the correct file has been uploaded, that the upload is uncorrupted and that it renders correctly. HW may include ideas and code from other sources—but these other sources must be documented with clear attribution. Please review academic integrity policies here.

We anticipate you all doing well in this course; however, if you are feeling lost or overwhelmed, that’s ok! Should that occur, we recommend: (i.) asking questions in/after class, (ii.) attending office hours, and/or (iii.) reaching out to course staff.

Cheating and plagiarism have been and will be strongly penalized. If, for whatever reason, this website, or Gradescope is down, or something else prohibits you from being able to turn in an assignment on time, immediately contact course staff via email (attach your assignment/quiz/exam answers) or else it will be graded as late.

Disability​ ​Access

Students requesting accommodations due to a disability must provide a current Authorization for Accommodation (AFA) letter. These letters are issued by the Office for Students with Disabilities (OSD), which is located in University Center 202 behind Center Hall. To arrange accommodations please contact Kyle kshannon@ucsd.edu privately, I will loop in the appropriate course staff to act as a liaison.

Contacting the OSD can help you further: 858.534.4382 (phone) osd@ucsd.edu (email) http://disabilities.ucsd.edu

Questions & Feedback

How to Get Your Question(s) Answered and/or Provide Feedback It’s great that we have many ways to communicate, but it can get tricky to figure out who to contact or where your question belongs, or when to expect a response. These guidelines are to help you get your question answered as quickly as possible and to ensure that we’re able to get to everyone’s questions.

That said, to ensure that we’re respecting their time, TAs and IAs have been instructed they’re only obligated to answer questions between normal working hours (M-F 9am-5pm). However, I know that’s not when you may be doing your work. So, please feel free to reach out whenever is best for you while knowing that, you may not get a response until the next day. As such, do your best not to wait until the last minute to ask a question. If there is an emergency and you need to contact staff immediately, email Kyle and put “EMERGENCY-DSC100” in the subject line. I will get back to you ASAP.

If you have…

• questions about course content - these are awesome! We want everyone to see them and have their questions answered, please post questions, or ask during class/office hours.
• questions about course logistics - first, check the syllabus. If the answer is not there, ask in Section, ask a classmate, or ask during class/office hours.
• something super cool to share related to class - feel free to email Kyle kshannon@ucsd.edu) or come to office hours. Be sure to include your full name in your message.
• something you want to talk about in-depth - meet in person/digitally during office hours or schedule a time to meet 1:1 by email. kshannon@ucsd.edu.