Competitive Programming for Beginners (Coursera)

Competitive Programming for Beginners (Coursera)

This online course will help you to join the world of competitive programming and even become worldwide competitions participant! The course includes theoretical and practical aspects that are necessary to solve problems of any difficulties. After this course, you will learn what types of problems you will have to solve at the competitions, what is the effective program, how to estimate the algorithms efficiency, how to use basic algorithms and ideas during the problems solution.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

You will also learn how to submit your solution to the testing system.
What You Will Learn

  • Basic Algorithms
  • Number and Graph Theories
  • Dynamic Programming

Syllabus

WEEK 1
Basic Algorithms
In this first module of our course we will: talk about how to measure efficiency of the developed algorithm; learn what is asymptotics; learn how to implement some simplest algorithms.

WEEK 2
Number Theory
In this module of our course we will: talk about integer data types in existing programming languages, limitations of these types and ways to pass those limitations in competitive programming tasks; look at some applications of the modulo calculations related to the calculation of the greatest common divisor; learn what the regular and extended Euclid's algorithm is and how they are used in math (to prove important theorems) and in programming.

WEEK 3
Dynamic Programming
In this module we will talk about the dynamic programming. You surely have been faced with it when you implemented prefix sums or the sieve of Erathosphenes. Also it turns out to be a part of a large number of algorithms, so it’s extremely important to learn the topic in small details.

WEEK 4
Graph Theory
In this closing part of our course we shall get acquainted with the basic definitions and algorithms of graph theory in regard to competitive programming in general

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Algorithms, Part II (Coursera) Coursera
Princeton University

Algorithms, Part II (Coursera)

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.

Jul 20th 2026
5-12 Weeks
NLP Modelos y Algoritmos (Coursera) Coursera
Universidad Austral

NLP Modelos y Algoritmos (Coursera)

Este curso te brindará los conocimientos necesarios para la implementación de algoritmos de NLP. Mediante el uso de los últimos algoritmos más populares en NLP se procederá a dar solución a un conjunto de problemas propios del área. Para realizar este curso es necesario contar con conocimientos de programación de nivel básico a medio, deseablemente conocimiento básico del lenguaje Python y es recomendable conocer los Jupyter Notebooks en el entorno Anaconda.

Aug 3rd 2026
4 Weeks
Approximation Algorithms (Coursera) Coursera
EIT Digital

Approximation Algorithms (Coursera)

Many real-world algorithmic problems cannot be solved efficiently using traditional algorithmic tools, for example because the problems are NP-hard. The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. These techniques apply when we don't require the optimal solution to certain problems, but an approximation that is close to the optimal solution. We will see how to efficiently find such approximations.

Jul 24th 2026
4 Weeks
VLSI CAD Part I: Logic (Coursera) Coursera
University of Illinois at Urbana-Champaign

VLSI CAD Part I: Logic (Coursera)

A modern VLSI chip has a zillion parts -- logic, control, memory, interconnect, etc. How do we design these complex chips? Answer: CAD software tools. Learn how to build thesA modern VLSI chip is a remarkably complex beast: billions of transistors, millions of logic gates deployed for computation and control, big blocks of memory, embedded blocks of pre-designed functions designed by third parties (called “intellectual property” or IP blocks). How do people manage to design these complicated chips? Answer: a sequence of computer aided design (CAD) tools takes an abstract description of the chip, and refines it step-wise to a final design.

Jul 27th 2026
5-12 Weeks
Mathematical Biostatistics Boot Camp 1 (Coursera) Coursera
Johns Hopkins University

Mathematical Biostatistics Boot Camp 1 (Coursera)

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

Jul 20th 2026
4 Weeks
AI and the Illusion of Intelligence (Coursera) Coursera
Copenhagen Business School

AI and the Illusion of Intelligence (Coursera)

Will AI soon be surpassing humans? This is rapidly becoming one of the central questions of our time -- but it is the wrong question. In this course, we will provide a non-technical look at where AI has come from, and where it is going. We will see that there is no reason to expect that AI will be surpassing humans. Instead, what we are learning to create with AI is the illusion of intelligence.

Aug 3rd 2026
4 Weeks
Approximation Algorithms Part I (Coursera) Coursera
École normale supérieure

Approximation Algorithms Part I (Coursera)

How efficiently can you pack objects into a minimum number of boxes? How well can you cluster nodes so as to cheaply separate a network into components around a few centers? These are examples of NP-hard combinatorial optimization problems. It is most likely impossible to solve such problems efficiently, so our aim is to give an approximate solution that can be computed in polynomial time and that at the same time has provable guarantees on its cost relative to the optimum.

Aug 3rd 2026
5-12 Weeks
Ethical Issues in Data Science (Coursera) Coursera
University of Colorado Boulder

Ethical Issues in Data Science (Coursera)

Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more. In many cases, they are affected by techniques in artificial intelligence and machine learning.

Aug 3rd 2026
5-12 Weeks
An Introduction to Logic for Computer Science (Coursera) Coursera
University of Leeds

An Introduction to Logic for Computer Science (Coursera)

Logic plays a fundamental role in computer science. This course is designed to equip you with a solid understanding of the fundamental principles of logic and their relevance in the field of computer science. In this course, you'll explore proposition logic and discover its practical applications in problem-solving, algorithm design, and the development of intelligent systems. By engaging in hands-on exercises, exploring real-world examples, and participating in discussions, you'll develop strong logical reasoning and critical thinking skills.

Jul 27th 2026
2 Weeks
Cloud Computing Concepts, Part 1 (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cloud Computing Concepts, Part 1 (Coursera)

Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies—all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing. Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more!

Jul 20th 2026
5-12 Weeks