ESE 2040, Fall 2022
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ESE 2040, Fall 2023 – Decision Models (and Algorithms)

Instructor: Nikolai Matni, Assistant Professor, ESE Department

Teaching assistant: TBD

Graders: TBD

Lectures: Tu/Th 1:45-3:15pm ET, ANNS 111

Office hours: NM: Tu 3:30-4:30pm ET, Levine 374, TBD, TBD, TBD: TBD (check Canvas)

Syllabus: ESE2040 Fall 2023

Canvas: We will be using Canvas to manage class logistics. Please log in and register here. On Canvas, there will be a link to Ed Discussion, please register there as well.

Course description

This first course in decision making will introduce you to quantitative models for decision and design in the sciences, engineering, machine learning, data science, logistics, and economics. Through application-based case studies, you will be shown how to (i) formalize a decision problem as a mathematical optimization problem, and (ii) solve the resulting optimization problem using Python scientific computing modules. You will also be given a brief introduction to the optimization algorithms and programming tools underpinning contemporary deep learning and shown how to apply them to decision and design problems.

About the Course

Prerequisites

The only official prerequisites for this class is Math 1400. Basic familiarity with Linear Algebra (vectors, matrices) and Python and programming is helpful, but not necessary.

Tentative homework schedule

  • 09/07: Hw1 out

  • 09/14: Hw2 out, Hw1 due

  • 09/21: Hw3 out, Hw2 due

  • 09/28: Hw4 out, Hw3 due

  • 10/05: Hw4 due, midterm study break

  • 10/10: In-class midterm 1, take-home midterm out

  • 10/19: Hw5 out, take-home midterm due

  • 10/26: Hw6 out, Hw5 due

  • 11/02: Hw7 out, Hw6 due

  • 11/09: Hw8 out, Hw7 due

  • 11/16: Hw8 due, Hw9 out

  • 11/23: Thanksgiving break

  • 11/30: Hw9 due, final study break

  • 12/07: In-class midterm 2, take-home midterm out

Grading

  • Homework (50%): there will be 9 homework assignments. They will be assigned weekly, handed out on Thursday at 1pm and due the following Thursday at 1pm. There will be suitable breaks in assignments to accommodate exams and the Thanksgiving holiday weekend. Assignments will include both conceptual (written) and implementation (programming) exercises. You will be given 5 free late days which you may use as you please throughout the semester, after which no late assignments will be accepted. Each homework problem will be graded on a scale of 0-2: no points are awarded for a skipped problem, 1 point for a solid attempt, and 2 points for a mostly correct solution.

  • Midterm exam 1 (25%): the midterm will consist of an in-class written component (15%) and a take-home computational component (10%). The in-class component will be closed-book and closed-notes. However, you will be allowed a single sheet of standard-sized paper with you with anything you want written on it (double-sided). No electronic devices are allowed. The take-home component of the exam will be open book.

  • Midterm exam 2 (25%): the midterm will consist of an in-class written component on the last day of classes (15%) and a take-home computational component (10%) due one week later. The in-class component will be closed-book and closed-notes. However, you will be allowed a single sheet of standard-sized paper with you with anything you want written on it (double-sided). No electronic devices are allowed. The take-home component of the exam will be open book.

Code of Academic Integrity: All students are expected to adhere to the University’s Code of Academic Integrity.