Computer Science for All MP (Eng. Prep year 2) Revision Sheets
Computer science for all in MP is a mandatory common subject (2h/week). Curriculum in Python (pivot language), centered on fundamental algorithmics and scientific computing. Modest coefficient but easy points to gain.
Computer Science for All curriculum in MP (Eng. Prep year 2)
The curriculum covers advanced algorithmics (recursion, dynamic programming, complexity), fundamental data structures (lists, dictionaries, trees, graphs), sorting and searching algorithms (quicksort, mergesort, binary search), relational databases and SQL, scientific computing with NumPy/SciPy/matplotlib (numerical equation solving, Newton's method, numerical integration).
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Tips to succeed in computer science for all MP (Eng. Prep year 2)
Invest 2-3 extra hours weekly on computer science: the UE with highest ROI in points/hour of work
Master NumPy and SciPy libraries: 90% of concours exercises depend on them
Learn SQL deeply: SELECT with joins, GROUP BY, subqueries. Tested in majority of concours
Code curriculum algorithms yourself (sort, search, tree traversal) — don't just use Python's sorted()
FAQ — Computer Science for All MP (Eng. Prep year 2)
What computer science level expected in MP?
The curriculum assumes no special prerequisites but demands rigor. By end of year two, you should master: advanced Python (OOP, modules, exception handling), classical algorithms (sorts, search, tree traversal, dynamic programming), scientific libraries (NumPy, SciPy, matplotlib), databases and SQL, numerical methods (Newton, bisection, Runge-Kutta for ODEs). Expected level is enough to enter any engineering school painlessly.
Does computer science really count for MP concours?
Yes, but with variable coefficient. At X, ENS Ulm, Mines-Ponts: ~5-10% of total coefficient, but the exam where you lose few points with regular work (past papers, exercises). At X-ENS Cachan, Télécom, ESILV: higher coefficient (15-25%). Across the entire concours, aiming for 14-16/20 in computer science is widely realistic with 3-4h/week of regular work — profitable.
Which Python IDE for MP?
Three recommended options: 1) Jupyter Notebook (ideal for scientific computing, immediate graph visualization — the expected concours environment), 2) Spyder (similar to Matlab, integrated console, graphical debugger), 3) VS Code with Python extension (more pro, ideal for long projects and development). For concours, master Jupyter AND a "normal" environment (Spyder or VS Code). In 2 months of regular practice, you'll be comfortable on both.
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