Educational Objectives

This course is a variant of Harvard College’s introduction to computer science, CS50, designed especially for law students. Whereas CS50 itself takes a bottom-up approach, emphasizing mastery of low-level concepts and implementation details thereof, this course takes a top-down approach, emphasizing mastery of high-level concepts and design decisions related thereto. Ultimately, it equips students with a deeper understanding of the legal implications of technological decisions made by clients.

Through a mix of technical instruction and discussion, this course empowers students to be informed contributors to technology-driven conversations. In addition, it prepares students to formulate technology-informed legal arguments and opinions. Along the way, it equips students with hands-on experience with Python and SQL, languages via which they can mine data for answers themselves, as well as HTML, CSS, and JavaScript, languages with which web and, increasingly, mobile applications are built.

Topics include algorithms, artificial intelligence, cloud computing, databases, networking, privacy, programming, scalability, security, and more, with a particular emphasis on understanding how the work developers do and the technological solutions they employ can impact clients. Students emerge from this course with first-hand appreciation of how it all works and all the more confident in the factors that should guide their decision-making.


This course is designed for future attorneys who expect to work closely with and advise decision-makers on legal matters that impact or intersect with technology.


You are expected to attend all lectures and labs and to submit all assignments, including a summative assignment.


Final grades will be based on quality of participation (20%), labs (10%), and assignments (70%), with a final assignment weighted more heavily than other assignments.


Lectures are opportunities to learn and discuss new material.

You are expected to arrive at lecture (with a laptop) having completed all prior assignments, prepared to discuss all prior classes’ material.

Lectures meet from 1pm until 4:30pm on most days.


Labs meet from 1pm until 4:30pm on some days and must be submitted by 1pm on the day due. Labs are hands-on opportunities to learn how to write code in multiple languages.


Led by the teaching staff, seminars are opportunities to dive into topics beyond the scope of the course’s lectures and labs.


Assignments are assigned daily and must be submitted by 1pm on the day due. Assignments are opportunities to introduce or reinforce material via exercises, readings, questions, and/or videos. Assignments that offer hands-on opportunities to write code may take longer than others to complete.

Many questions on the assignments in this course are out of 3 points. When you receive your feedback on these assignments, these scores translate as follows:

  • 3 is reserved for exceptional answers that demonstrate a full understanding of the material in a manner that exceeds the course’s expectations, which may sometimes involve external research. Please note that this does not necessarily mean a long answer; indeed, an overly long answer that introduces irrelevant information is not likely to receive a 3. Rather, a 3 is awarded to a thorough and well thought-out and prepared answer that focuses on the subject of the question being presented. Only a few 3s at most will be awarded per question.
  • 2 is awarded for a good to great answer that demonstrates understanding of the material in a manner consistent with the course’s expectations. Most correct answers will be graded a 2, and a score of 2 should be considered your benchmark for success.
  • 1 is awarded for a poor to fair answer that either demonstrates partial understanding of the material or otherwise contains an error that suggests a misunderstanding of a key detail.
  • 0 is given to answers that are incorrect, exceedingly brief, or blank.

Office Hours

Office hours are opportunities for guidance and feedback from the staff on assignments and projects as well as for discussion of the course’s material more generally.


Late submissions of assignments will be penalized as follows:

  • If you submit after the assignment’s deadline but before 11:59 PM on its due date, your score will be 50% of what it would have been if submitted on time. For example, if an assignment is due at 1:00 PM on January 4th, a submission after 1:00 PM and before 11:59 PM on January 4th will receive 50% of the credit it would have earned if submitted on time.
  • If you submit after 11:59 PM on the assignment’s due date, you will receive no credit. For example, if an assignment is due at 1:00 PM on January 4th, a submission any time after 11:59 PM on January 4th will receive no credit.


Extensions beyond this lateness policy are not ordinarily granted.

Academic Honesty

This course’s philosophy on academic honesty is best stated as “be reasonable.” The course recognizes that interactions with classmates and others can facilitate mastery of the course’s material. However, there remains a line between enlisting the help of another and submitting the work of another. This policy characterizes both sides of that line.

The essence of all work that you submit to this course must be your own. Collaboration on assignments and projects is not permitted except to the extent that you may ask classmates and others for help so long as that help does not reduce to another doing your work for you. Generally speaking, when asking for help, you may show your work to classmates and others, but you may not view theirs, so long as you and they respect this policy’s other constraints.

Below are rules of thumb that (inexhaustively) characterize acts that the course considers reasonable and not reasonable. If in doubt as to whether some act is reasonable, do not commit it until you solicit and receive approval in writing from the course’s instructor. Acts considered not reasonable by the course are handled harshly as academic dishonesty.

If you commit some act that is not reasonable but bring it to the attention of the course’s instructor within 72 hours, the course may impose local sanctions that may include a failing grade for work submitted, but the course will not escalate the matter further except in cases of repeated acts.


  • Communicating with classmates about assignments in English (or some other spoken language).
  • Discussing the course’s material with others in order to understand it better.
  • Helping a classmate identify a bug in his or her code at Office Hours, elsewhere, or even online, as by viewing or running his or her code, even on your own computer.
  • Incorporating snippets of code that you find online or elsewhere into your own code, provided that those snippets are not themselves solutions to assigned problems and that you cite the snippets’ origins.
  • Sending or showing an answer or code that you’ve written to someone, possibly a classmate, so that he or she might help you identify and fix a mistake.
  • Sharing snippets of your own answers or code online so that others might help you identify and fix a mistake.
  • Turning to the web or elsewhere for instruction beyond the course’s own, for references, and for solutions to technical difficulties, but not for outright solutions to assignments or portions thereof.
  • Whiteboarding solutions to assignments with others outside of your team using diagrams or pseudocode but not actual code.
  • Working with (and even paying) a tutor to help you with the course, provided the tutor does not do your work for you.

Not Reasonable

  • Asking a classmate to see his or her answer or code before (re-)submitting your own.
  • Failing to cite (as with comments) the origins of code or techniques that you discover outside of the course’s own lessons and integrate into your own work, even while respecting this policy’s other constraints.
  • Giving or showing to a classmate an answer or code when it is he or she, and not you, who is struggling with their own.
  • Paying or offering to pay an individual for work that you may submit as (part of) your own.
  • Providing or making available answers or code to individuals who might take this course in the future.
  • Searching for or soliciting outright solutions to assignments (or portions thereof) online or elsewhere.
  • Splitting an assignment’s workload with another individual outside of your team and combining your work.
  • Splitting an assignment’s workload within your team inequitably but claiming an equitable split.
  • Submitting (after possibly modifying) another’s words without attribution for some assignment.
  • Submitting (after possibly modifying) the work of another individual beyond allowed snippets.
  • Submitting the same or similar work to this course that you have submitted or will submit to another.
  • Submitting work to this course that you intend to use outside of the course (e.g., for a job) without prior approval from the course’s instructor.
  • Using AI-based software that suggests or completes answers to questions or lines of code.
  • Viewing another’s solution to an assignment and basing your own solution on it.