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NTIN061: Algorithms and Data Structures 1
NTIN061: Algorithms and Data Structures 1
Semester: Summer
Semester: Summer
Offered: 2025
Time: Mondays, 15:40
Place: N6
Office hours: Set upon agreement, if you need to discuss something, email me.
Offered: 2025
Time: Mondays, 15:40
Place: N6
Office hours: Set upon agreement, if you need to discuss something, email me.
Introductory lecture on the basic types of algorithms and data structures necessary for their implementation. It follows the lecture NPRG062 Algorithmization in the previous semester. To submit homeworks, you can enroll into my tutorial on the Postal Owl using the link https://owl.mff.cuni.cz/join/0023f000eb71 or the token 0023f000eb71.
You can find the problem sheets below:
Tutorial 1.pdfTutorial 2.pdfTutorial 3.pdfTutorial 4.pdfTutorial 5.pdfTutorial 6.pdfTutorial 7.pdfTutorial 8.pdfTutorial 9.pdfTutorial 10.pdfTutorial 11.pdfTutorial 12.pdfTutorial 13.pdfCOURSE INFORMATION
To get the tutorial credit, you must obtain at least 100 points from the homework and quizzes.
Homework:
- There will be a total of 4 homeworks, worth a total of 120 points.
- Deadlines will be ≈ 3 weeks from the time they are published.
- Submissions will be done through the Postal Owl system.
- Once you receive feedback for your homework, you may have up to two chances to fix any mistakes.
- You may ask for extensions for the homework deadlines only with a valid excuse.
- Unless the point above applies, you can submit a homework up to 2 weeks late for 2/3 of its points.
- I will give my first feedback a week after publishing the homework.
- Do not cheat. This includes using AI, copying from MathStackExchange and similar sites, as well as submitting identical solutions as your colleagues. You can discuss the homework with your friends, but please write down solutions on your own. I will report any and all suspicious behavior.Quizzes:
- Starting from Week 2, there will be a quiz at the beginning of each tutorial.
- Quizzes will be worth a total of at least 30 points.
- What to expect: definitions, parts of algorithms, propositions from the lecture.I don’t require attendance. If you feel that you can benefit more from self-study or anything else, go for it.
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