Lecture 1

Introduction

MCS 275 Spring 2024
Emily Dumas

Lecture 1: Introduction

Things to do ASAP

• Check the Getting started section on Blackboard.
• Read the syllabus.

About me

they/them

I'm a professor of mathematics, 15 years at UIC.

Research in differential geometry.

I use lots of Python in my work and in projects I supervise, and I enjoy teaching intro MCS courses.

Email: edumas@uic.edu

MCS 275

• Intro to additional CS topics
• Deeper study of Python language
• Some algorithms and data structures

If you miss a lecture

This is an on campus class.

But there are backup participation options for cases of illness, delayed train, blimp accident, AI rebellion, etc.

• Live stream on Blackboard (Echo 360)
• Watch recording when posted to Blackboard

Don't rely on the backup options regularly!

Documents from lecture

• Slides go on Blackboard
• Code goes on GitHub

Teaching assistants

• Karoline Dubin <kdubin3@uic.edu>
• Patrick Ward <pbward2@uic.edu>

Run Tues/Thurs lab, do some of the grading.

Lab

• Essential practice/learning time: You complete a worksheet with guidance and help from TA.
• Attendance is taken every time (drop 2).
• Prepares you for the week's homework.

MCS 275 has entered the chat

You can contact me by email or join the course Discord.

Discord invitation link is on Blackboard. Keep usernames and avatars work-appropriate!

Schedule

All topics, dates, and deadlines are in the syllabus.

Grading

• 45% homework
• 45% projects
• 10% lab attendance

I use a fixed grading scale where A=85% to 100%, B=75% to 84.99999%, C = 65% to 74.99999%, etc (see syllabus), with no rounding.

Homework

Weekly, 14 in total.

Twice in the semester, you can be excused from a homework assignment just by asking your TA before the deadline.

Of the 12-14 homework you are not excused from, we'll also drop the two lowest grades.

Projects

Bigger programming tasks where you get a detailed formal specification.

Due on Feb 9, Feb 23, Mar 15, Apr 26.

Graded by automated tests + manual review.

Late or missed work

See the syllabus for the full policy.

Essential to get in touch with me as soon as you can.

Software

You need access to such a computer with:

• Python 3, version 3.10 or later
• Microsoft VS Code (a programming editor)

These are free.

Textbooks

None required.

Some books you can read online that I'll cite:

• Learning Python, 5th Edition, by Mark Lutz
• Think Python, 2nd edition, by Allen B. Downey
• Python Data Science Handbook by Jake VanderPlas

Working together

Collaborate freely on the worksheets and studying.

Do the homework and projects on your own.

Generative AI

Don't use it for graded work in MCS 275.

Old course materials

I make all my old course materials publicly available on my web site. E.g.

• MCS 260:   2020,   2021
• MCS 275:   2021,  2022,   2023

Next

A "tour" of Python: Quick summary of the basics.