Scientific Programming 2
Welcome to this programming course! In the weeks ahead, you’ll use the programming language Python while learning to solve scientific problems from several fields of science. This second part is intended for students who already followed Scientific Programming 1.
If you have practical matters that you would like to discuss, always send an e-mail to the staff via email@example.com. We will answer within a couple of days, if not hours.
Your entry to the course is the sidebar, where you can leaf through all modules (levels) that you have to complete.
This course assumes that you have completed the course Scientific Programming 1. If you didn’t do this, but have equivalent programming experience, please discuss this with us before starting the course.
Other than that, some modules assume high school mathematics or physics, but many do not. If you feel overwhelmed, don’t hesitate to contact the course staff! We can explain the course’s philosophy and requirements, and make recommendations on how to approach problems.
After this course you should be able to independently tackle typically programming challenges that you might encounter in your field of studies/research. We will teach you more intermediate Python concepts. And some more advanced concepts pertaining to data analysis. After this course, we envision that you:
- can use native python data structures (like sets, dictionaries, and tuples)
- analyze the complexity of an algorithm
- quickly learn to use new python packages and know how to find documentation for them
- create your own packages
- write proper documentation
- use higher level functional programming concepts (such as map, reduce and filter)
- import and analyze data
- create advanced plots
In this course you’ll mostly work on assignments independently. But you’re not on your own! We’re here to help. There are three ways you can get help:
- Helpdesk (Programmeerbalie): Online or on campus. Book a slot to get help
- Lab sessions: Only on campus. Work in a classroom together with other students
- Forum: Only online.
See for more info: Help
Passing the course
The course’s final result will be “pass” or “fail”, which means that no grades are assigned. To earn a “pass”, you must meet the following requirements by 29 May:
- you have submitted a fully working solution for each module
- you must pass the final exam
Sufficient coursework means submitting a working solution to each problem from at least four modules of your own choosing, keeping in mind that you need to finish one module per level.
You may not re-submit (variations of) solutions that you wrote for any other course’s problems. In case you have done similar assignments before, discuss with the course staff whether this is the right course for you.
Deadlines for each level are listed below. The deadlines are our recommendation. If you follow these deadlines you’ll have all the assignments finished in time for the corresponding examination moment. You can occasionally diverge a bit from the deadlines, but if you notice that you’re structurally behind please contact us (firstname.lastname@example.org).
The deadlines depend on the period in which you start the course (4, or 5) and at what pace you’re following it (4, 8 or 16 weeks).
Start block 4 (7 Feb 2022)
|Finish course in:||4 weeks (start 2 March)||8 weeks||16 weeks|
|Level 5||Fri 11 Mar 2022||Fri 18 Feb 2022||Wed 09 Mar 2022|
|Level 6||Fri 18 Mar 2022||Tue 08 Mar 2022||Wed 13 Apr 2022|
|Level 7||Fri 25 Mar 2022||Fri 25 Mar 2022||Wed 18 May 2022|
|Exam||Wed 30 Mar 2022||Thu 2 Jun 2022||Thu 2 Jun 2022|
Start block 5 (4 Apr 2022)
|Finish course in:||4 weeks (start 29 Apr)||8 weeks|
|Level 5||Wed 11 May 2022||Wed 20 Apr 2022|
|Level 6||Wed 18 May 2022||Wed 11 May 2022|
|Level 7||Wed 25 May 2022||Wed 25 May 2022|
|Exam||Thu 2 Jun 2022||Thu 2 Jun 2022|
The exam for this course is a programming exam. You’ll make a number of smaller programming assignments in a controlled setting. This will take about 3 hours.
- There is one exam for the courses Scientific Programming 1 and 2. If you already passed the Scientific Programming 1 course before, please contact us to plan the examination.
- There is an exam at the end of each bock (block 1, 2, 4, and 5).
- You can only participate in the exam if you finished al the assignments! If you did not finish the final assignment before the exam date, you’ll have to take the exam at the next occasion.
The dates for the exams: Wed 30 March, Thu 2 June
Programming is like writing. You can gradually learn to write programs that are more beautiful, functional, short, elegant or simple. To learn this, you’ll need some feedback, and it’s mostly up to you to get it. You can show your programs in class to fellow students or your teacher; you can post a fragment of your code on Stack Overflow and ask for advice on improving; or you can send the staff an e-mail and we’ll have a look (this might take a while though!).
Doing your own work
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 problem sets 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 code to others, but you may not view theirs, so long as you and they respect this policy’s other constraints. Collaboration on the course’s test and quiz is not permitted at all.
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 heads. Acts considered not reasonable by the course are handled harshly.
Communicating with classmates about problem sets’ problems 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, compiling, or running his or her code, even on your own computer.
Incorporating a few lines of code that you find online or elsewhere into your own code, provided that those lines are not themselves solutions to assigned problems and that you cite the lines’ origins.
Reviewing past semesters’ quizzes and solutions thereto.
Sending or showing code that you’ve written to someone, possibly a classmate, so that he or she might help you identify and fix a bug.
Sharing a few lines of your own code online so that others might help you identify and fix a bug.
Turning to the course’s heads for help or receiving help from the course’s heads during the quiz or test.
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 problem set’s problems or your own final project.
Whiteboarding solutions to problem sets with others 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.
Accessing a solution to some problem prior to (re-)submitting your own.
Asking a classmate to see his or her solution to a problem set’s problem before (re-)submitting your own.
Decompiling, deobfuscating, or disassembling the staff’s solutions to problem sets.
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 a solution to a problem set’s problem when it is he or she, and not you, who is struggling to solve it.
Looking at another individual’s work during the test or quiz.
Paying or offering to pay an individual for work that you may submit as (part of) your own.
Providing or making available solutions to problem sets to individuals who might take this course in the future.
Searching for or soliciting outright solutions to problem sets online or elsewhere.
Splitting a problem set’s workload with another individual and combining your work.
Submitting (after possibly modifying) the work of another individual beyond the few lines allowed herein.
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 heads.
Turning to humans (besides the course’s heads) for help or receiving help from humans (besides the course’s heads) during the quiz or test.
Viewing another’s solution to a problem set’s problem and basing your own solution on it.
This course has been designed by Martijn Stegeman, Simon Pauw, Tim Doolan.
This work is partially based on many great programming resources that have been published as Open Courseware under a Creative Commons license. The resulting work itself is also published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Feel free to re-use! If you would like to use the work commercially, please send an e-mail for arranging a license.
We have had lots of help from students as well as teaching assistants who tried the course or added ideas of their own. We especially thank:
- Quinten Post (video)
- Natasja Wezel (video)
- Iris Luden (video)
- Marleen Rijksen (revisions)
- Vera Schild (revisions)
We have used materials from the following sources:
- 6.189 A Gentle Introduction to Programming Using Python by Sarina Canelake at MIT http://ocw.mit.edu
- 6.00 Introduction to Computer Science and Programming, Fall 2008 by Eric Grimson and John Guttag at MIT http://ocw.mit.edu
- CS50 Introduction to Computer Science I by David Malan at Harvard http://cs50.tv/
- 6.0001 Introduction to Computer Science and Programming in Python by Ana Bell, Eric Grimson and John Guttag at MIT http://ocw.mit.edu
- Think Python by Allen B. Downey http://greenteapress.com/wp/think-python/