The ability to analyze data with Python is critical in data science. Learn the basics, and move on to create stunning visualizations.
Enhance programming skills to boost your career and win prizes led by ITMO University, the only 6-time winner of the world’s top coding cup. 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 6-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.
What you'll learn:
- The benefits of participating in programming competitions
- The algorithms and approaches you need to master the world of competitions
- Ways of self-training for further progress
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
Binary search (implementation and examples). An overview of sorting algorithms (bubble sort, insertion sort, quick sort, merge sort), including theoretical analysis and examples of use.
Week 4: Graph theory
Definition of graphs and examples of graph problems. Various ways of storing graphs in memory. DFS and related topics: connected components, detecting cycles, detecting bipartite graphs. Shortest paths: BFS, Dijkstra algorithm.
Week 5: Final Exam
Solving a set of problems in limited time just like in a real programming competition.