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How to Win Coding Competitions: Secrets of Champions

ITMO University via edX

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  • Provider edX
  • Subject Programming
  • $ Cost Free Online Course
  • Session In progress
  • Language English
  • Effort 4-6 hours a week
  • Start Date
  • Duration 7 weeks long

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Overview

Want to be the programmer hot tech companies are looking for?

Take your programming skills to the next level and prove your excellence by learning how to succeed in programming competitions.

Besides improving your knowledge of algorithms and programming languages, you’ll gain unique experience in problem solving, thinking outside the box and meeting tough deadlines – all essential for boosting your value as a programmer and securing a coveted job in Silicon Valley (should you want one).

This computer science course is an introduction to competitive programming developed by ITMO University, the leading expert in IT and the only 7-time world champion of the Association for Computing Machinery - International Collegiate Programming Contest (ACM ICPC), the world's most prestigious programming contest.

You will learn all you need to know about the variety of programming competitions that exist, as well as basic algorithms and data structures necessary to succeed in the most popular of them.

Syllabus

Week 1: Welcome to competitive programming
Exploring different kinds of programming competitions and benefits of participating, as well as typical rules and challenges. An overview of algorithmic programming competitions. An introduction to community resources and online contests. Week 2: Computational complexity and linear data structures
An overview of computational complexity (Big O notation). Exploring linear data structures (array, list, stack, queue): operations, complexity, implementation and examples. Week 3: Sorting and search algorithms 1
An overview of sorting algorithms: insertion sort, quick sort, merge sort. Week 4: Sorting and search algorithms 2
Theoretical limitations and practical guidelines for sorting. Binary search. Binary heaps and priority queues. Week 5: Graph theory 1
Definition of graphs and examples of graph problems. Various ways of storing graphs in memory. Depth first search and its applications. Dynamic programming. Week 6: Graph theory 2
Breadth first search. Eulerian and Hamiltonian paths and tours. Shortest paths. Week 7: Final Exam
Solving a set of problems in limited time just like in a real programming competition.

Taught by

Maxim Buzdalov and Pavel Krotkov

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