Programming & Algorithms BUT Computer Science Revision Sheets
The core of BUT Computer Science: mastery of algorithmic fundamentals and several programming languages. Essential for all specialization paths in years two and three.
Programming & Algorithms curriculum in BUT Computer Science
The curriculum covers algorithmics (control structures, functions, recursion, complexity), data structures (arrays, linked lists, stacks, queues, trees, graphs, hash tables), object-oriented programming (encapsulation, inheritance, polymorphism), paradigms (procedural, object, functional), and several languages (Python as pivot language, Java, JavaScript, C/C++ depending on IUT).
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Tips to succeed in programming & algorithms BUT Computer Science
Code EVERY DAY — minimum 1h. Programming is learned through practice, not classes
Do Codingame, LeetCode, HackerRank exercises from year one: the real training expected in placement and engineering school
Master algorithmic complexity (O(n), O(log n), O(n²), O(n log n)): tested in every evaluation and essential in job interviews
Learn Git in depth from L1: branches, merge, rebase. Non-negotiable in professional environment
FAQ — Programming & Algorithms BUT Computer Science
Which programming language to learn first in BUT Info?
Python is generally the entry language in BUT Info: accessible syntax, rich ecosystem, versatile (web, data, scripting, AI). You then learn Java (industrial OOP, Android), JavaScript (full-stack web), sometimes C/C++ (systems, performance). At BUT graduation, you should master 3-4 languages in depth. Tip: don't disperse efforts across 10 languages superficially — prefer 3-4 mastered ones.
What is algorithmic complexity and why does it matter?
Algorithmic complexity measures the time (or memory space) an algorithm takes based on input data size. Common notations: O(1) constant, O(log n) logarithmic (binary search), O(n) linear (list traversal), O(n log n) loglinear (efficient sorts), O(n²) quadratic (bubble sort, nested double loop). Understanding complexity lets you choose the right algorithm: for 1 million data points, O(n²) takes 1M × 1M = 10^12 operations — too long. O(n log n) takes ~20M — feasible.
Should I do engineering school after BUT Info?
Not mandatory but often profitable. BUT Info (bac+3) directly opens to the market (developer, integrator, junior data analyst, N2/N3 support) with starting salaries of €28-38k. Continuing in engineering school (EPITA, EPITECH, INSA, ESILV, ECE) via parallel admission adds 2 years but allows access to software engineer/architect/lead positions at €45-60k starting, with faster progression. ROI calc: 2 years of study + costs (~€25k) vs +€10-15k/year salary from graduation → ROI at 2-3 years.
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