Homework submission
This document should describe the homework submission procedure.
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This document should describe the homework submission procedure.
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This document was generated with Documenter.jl version 1.2.1 on Thursday 21 December 2023. Using Julia version 1.9.4.
This document should describe the homework submission procedure.
Settings
This document was generated with Documenter.jl version 1.2.1 on Thursday 21 December 2023. Using Julia version 1.9.4.
Before joining the course, consider reading the following two blog posts to figure out if Julia is a language in which you want to invest your time.
First and foremost you will learn how to think julia - meaning how write fast, extensible, reusable, and easy-to-read code using things like optional typing, multiple dispatch, and functional programming concepts. The later part of the course will teach you how to use more advanced concepts like language introspection, metaprogramming, and symbolic computing. Amonst others you will implement your own automatic differetiation (the backbone of modern machine learning) package based on these advanced techniques that can transform intermediate representations of Julia code.
This course webpage contains all information about the course that you need, including lecture notes, lab instructions, and homeworks. The official format of the course is 2+2 (2h lectures/2h labs per week) for 4 credits.
The official course code is: B0M36SPJ and the timetable for the winter semester 2022 can be found here.
The course will be graded based on points from your homework (max. 20 points) and points from a final project (max. 30 points).
Below is a table that shows which lectures have homeworks (and their points).
Homework | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Points | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | - | 2 | - | 2 | - |
Hint: The first few homeworks are easier. Use them to fill up your points.
The final project will be individually agreed on for each student. Ideally you can use this project to solve a problem you have e.g. in your thesis, but don't worry - if you cannot come up with an own project idea, we will suggest one to you. More info and project suggestion can be found here.
Your points from the homeworks and the final project are summed and graded by the standard grading scale below.
Grade | A | B | C | D | E | F |
---|---|---|---|---|---|---|
Points | 45-50 | 40-44 | 35-39 | 30-34 | 25-29 | 0-25 |
– | Room | Role | |
---|---|---|---|
Tomáš Pevný | pevnak@protonmail.ch | KN:E-406 | Lecturer |
Vašek Šmídl | smidlva1@fjfi.cvut.cz | KN:E-333 | Lecturer |
Matěj Zorek | zorekmat@fel.cvut.cz | KN:E-333 | Lab Instructor |
Niklas Heim | heimnikl@fel.cvut.cz | KN:E-333 | Lab Instructor |
There are no hard requirements to take the course, but if you are not at all familiar with Julia we recommend you to take Julia for Optimization and Learning before enrolling in this course. The Functional Programming course also contains some helpful concepts for this course. And knowledge about computer hardware, namely basics of how CPU works, how it interacts with memory through caches, and basics of multi-threadding certainly helps.
Settings
This document was generated with Documenter.jl version 1.2.1 on Thursday 21 December 2023. Using Julia version 1.9.4.