DD1328 Fundamentals of Computer Science for Scientific Computing 9.0 credits

In this course, the students will build on their knowledge of algorithms, data structures and program design, learn basics of parallel and distributed programming and prepare for courses in computational mathematics, machine learning and theoretical computer science. Programming languages in the course are Python and Go, and the students who want can furthermore test on one or more of the languages Java, Julia, C, and C++.

Algorithms and data structures: A systematic overview of the concepts abstract data types, stacks, queues, lists, trees, searching, sorting and recursion based on the knowledge the students acquired in the course Fundamentals of programming. Hashing. Priority queues. Search trees. Problem trees. Text searching. Simple syntactical analysis. Algorithm analysis. Cryptography.

Program Design: Program quality. Abstraction. Modularisation. Testing. System calls. Standard modules.

Parallel Programming: Basic knowledge of how a computer is working and what it is made up of, both from hardware and software perspectives. Introduction to parallel and distributed programming with processes

After passing the course, the student should be able to

• systematically test programs to discover errors
• use abstraction as a tool to simplify the programming
• select an appropriate algorithm for a given problem
• compare algorithms with regard to time and memory usage
• describe and implement different algorithms for search and sorting
• formulate and implement recursive algorithms
• write and use simple BNF syntax
• implement, and design algorithms for, basic data structures
• design and implement simple parallel programs

in order to

• become a good problem solver using programming
• be able to use computational methods in application projects
• take advanced courses in computational mathematics, machine learning and theoretical computer science.

Knowledge and skills in programming, 5 credits, equivalent to completed course DD1337/DD1310-DD1319/DD1321/DD1331/DD100N/ID1018.

Active participation in a course offering where the final examination is not yet reported in LADOK is considered equivalent to completion of the course.

Being registered for a course counts as active participation.

The term 'final examination' encompasses both the regular examination and the first re-examination.

If the course is discontinued, students may request to be examined during the following two academic years.

• HEM3 - Take-home Assignment, 3.0 credits, grading scale: P, F
• LABA - Programming Assignment, 2.0 credits, grading scale: A, B, C, D, E, FX, F
• LABB - Programming Assignment, 2.0 credits, grading scale: A, B, C, D, E, FX, F
• LABC - Programming Assignment, 2.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Hedvig Kjellström

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

In this course, the EECS code of honor applies, see:

http://www.kth.se/en/eecs/utbildning/hederskodex.