• This course is entirely online. Links for Zoom meetings will be given in Piazza.
• Officially we meet on Thursdays, 6 - 7:30pm. Besides that meeting time, the course is considered to be asynchronous, in the sense that you may watch lecture videos any time.
• On the Resources page you can find pre-recorded (and edited) lectures from recent semesters. There are also screen recordings of the lecture notes, with narrations, created within the past year.
  You are expected to keep up with the schedule that can be found on the course Schedule page.
• The recorded videos have been edited to ensure that everything is described as efficiently as possible while minimizing distractions. That is one of the reasons I consider the recorded videos to be your primary resource.
  I will use lecture time in various ways: I might focus on answering your questions about recent material, informally recap topics, discuss recent homework, or go over some practice problems. This will work best if you come prepared with questions about the course notes, and if you do the homework. As the semester progresses and we cover more challenging topics, I may shift to a more traditional live lecture style, but the recorded videos will still be your primary resource. I will not record our Zoom meetings, but if we discuss any new practice problems they will be posted in Piazza. If you are in a time zone that prevents you from attending "normal" class time, you will have opportunities to make up for this at other hours.

Non-required textbook: Introduction to Algorithms, 3rd edition, by Cormen, Leiserson, Rivest and Stein.
This is commonly just referred to as ``CLRS". More info at MIT press.
Note: my Resources page refers to this book so you can find relevant chapters if you wish. The course doesn't explicitly rely on the book though. Also, CLRS is massive. We will not cover everything in it. See "Topics" below.

Prerequisites: Discrete math is important. Basic understanding of some data structures and probability will matter too. Overall, you should possess mathematical maturity.
See the Resources page and search for the word "prerequisite" to see when you will need to know background material.
You will probably find this course difficult if you're not comfortable with induction, recursion and proofs, or if big-O seems like a challenging concept. It is assumed that you know the basics about arrays, linked lists and trees. Knowledge of basic probability will be helpful for two or three lectures but I will recap what you need to know.
If you have not done well in discrete math or have not passed data structures, you should contact me.

Topics: This is an introduction to the design and analysis of algorithms, which involves discussing a few basic data structures as well. Many topics could fit in such a course, and not all intro courses go over exactly the same material.
We will place all emphasis on theory instead of programming. This course is about figuring out how to solve a problem before you start coding.
To see what is taught in this course, please visit the Resources page.

• If you haven't been added to Piazza via the official course roster, please let me know. Your name in Piazza should contain your name in SIS. Feel free to add a nickname as well, but your official name should be there too.
• Piazza is mainly meant for asking questions that others would benefit from seeing. If you have a question that does not affect other students, or that may reveal answers to homework questions before solutions are posted, please use email instead. Do not post questions like "I'm trying to solve homework X like this but I'm not sure it's correct". That kind of question should be asked during office hours, after others confirm that they don't mind.
• In general, do not use Piazza as a substitute for sending me private messages that relate only to your own situation.
• Always make sure that your question hasn't already been answered on the course website or in Piazza.

Grading (exams)

• We will have 4 exams. Each will be worth 25% of the final grade, and covers approximately a quarter of the course material (non-cumulative).
• See the Schedule page for dates. The duration of each exam will probably be approximately 100 minutes.
  
• On exams you may need to describe algorithms, derive proofs of correctness, or analyze time complexity, for topics found in the course notes, or for slightly modified versions. You will also need to be familiar with homework problems and other practice problems that are handed out. Occasionally there are questions that require developing algorithms for brand new problems.
• You will need to type your exam answers directly into Gradescope. (See next section, below). It will help to become familiar with very basic LaTeX (I will explain and offer assistance when the time comes).
• All exams will be open book. You may refer to my course notes and videos, the textbook, and generally any resource that I have provided. You may not use the internet in any other way. This also means that you may not refer to your own notes if they were based on material found online or other sources besides those listed above. You may not collaborate during exams. Violation of these rules will result in an F in the course and a report to administration.
  
• Homework is worth 0%. Here's why.
  If you submit it, we will grade it and provide feedback, but this is done purely so that you can practice and understand where you might have incorrect reasoning. It is not factored into your final grade in any way.
  

Gradescope: How to submit homework. How to take exams.

• You will find homework problems posted in Piazza, in a tab called Resources. Solutions will be posted on the same page.
• Homework can be submitted in Gradescope. The access code can be found in Piazza. It is up to you to sign up, using your full name as it appears in SIS. Feel free to add a nickname as well, but your official name should be there too.
• When submitting homework in Gradescope, there is a straightforward way to tag your pages. Essentially you tell Gradescope which pages of your uploaded file relate to each problem. If you don't do this, we will not evaluate your work. Pages should appear in order and should not be rotated. Leave enough space so we can provide comments. Each problem should be on a different page (but subproblems can appear without breaks). Do not submit blank pages if you haven't solved a problem.
• Ideally your submissions should be typed, but you may also submit exceptionally clear handwritten scanned assignments. If your work is not clear, you will be asked to type the rest of your assignments. Either way, you may include figures, in fact you are encouraged to do so. If the figures are photographs or scans of work done on paper, it is your responsibility to make sure that they are clear, with proper contrast and resolution. There should be no shadows, coffee mugs, pets, body parts, etc, visible in your figures.
  
• Exams appear in the same list as homework assignments in Gradescope, but they are timed and you must type your answers. An example will be provided well before your first exam. In general I tend to create exam questions that don't require excessive writing.
• You can make regrade requests within Gradescope in a straightforward way, for homework and exams.

Tips for doing well in this course, if you find it challenging:

• Use the full version of the course notes when studying, not the condensed version. Try to anticipate what is coming next. Try to re-prove things. Derive on your own, rather than verifying what is written. When you simply verify what's there, it is easy to overestimate what you've understood.
• When you watch videos of lectures at home, use the pause button. If you don't understand something, watch again before proceeding. If the issue remains then get in touch with me or the TAs (or your classmates), or ask during the upcoming class time.
• Don't cram. The most common reason students don't do well on the exams in this course is that they think they can learn the material for an exam in two days. Spend time on this course regularly. Many students underestimate how much time is required to truly understand some of these topics.
• Use all resources available: class notes, the summary PDF document at the top of the Resources page, the videos, the book, and any links provided. Do practice problems from the book, starting with the more basic ones. In many cases you can make your own practice problems (e.g. draw an arbitrary graph and find shortest paths).
• As much as possible, don't memorize. Instead, understand. I do realize that some basic memory is required in any case. But if you think you need to memorize how algorithms work, why they are correct, or what their time complexities are, then you're not approaching this course correctly and should talk to me.
• Pretend that you will have to teach the material that you're reading, to 100 people.
• Try to do the homework on your own. If you are entirely stuck, get only basic hints from your classmates and TAs, but don't rush to do this if you've only spent an hour or two on a problem. If you have no idea how to approach a problem, then you probably need to study the basics a bit more: take the time to review the material from the corresponding lectures, and solve some easier exercises on your own. Then think about what tools you have just learned about, and whether they might help. If none of this works, then get some hints. Homework sometimes requires multiple hours of work.
• When stuck solving homework problems, see how you'd handle a made-up example. Think about whether your example is oversimplified, whether you've made unnecessary assumptions, and whether your solution is generalizable (if applicable). Also, sometimes it's a good idea to add extra assumptions, thus making the problem easier to solve, and gradually remove the assumptions.
• Read the homework solutions even if you got a good score. Sometimes graders don't notice subtle mistakes on homework submissions. Reading the solutions might help you avoid repeating such mistakes on an exam. Also, even if your ideas worked, the solutions might have a more efficient idea or description that will end up worth knowing about. In any case, it is your responsibility to be familiar with homework solutions, because they might appear on exams.
• Don't hesitate to talk to me and to the TAs.

Everyone involved in this course is to respect the following:

• Tufts academic integrity policy
• Tufts non-discrimination policy
• Basically, be nice.

• If you cheat on an exam in any way whatsoever, you will not pass the course and will likely face suspension.
• It is not acceptable to copy answers from any source or to distribute or receive solutions.