Advanced Algorithmics and Graph Theory with Python
link Source: www.edx.org
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assignment Level : Intermediate
chat_bubble_outline Language : English
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Key Information

credit_card Free access
verified_user Fee-based Certificate
timer 12 hours in total

About the content

Algorithmics and programming are fundamental skills for engineering students, data scientists and analysts, computer hobbyists or developers.

Learning how to program algorithms can be tedious if you aren’t given an opportunity to immediately practice what you learn. In this course, you won't just focus on theory or study a simple catalog of methods, procedures, and concepts. Instead, you’ll be given a challenge wherein you'll be asked to beat an algorithm we’ve written for you by coming up with your own clever solution.

To be specific, you’ll have to work out a route faster than your opponent through a maze while picking up objects.

Each week, you will learn new material to improve your artificial intelligence in order to beat your opponent. This structure means that as a learner, you’ll confront each abstract notion with a real-world problem.

We’ll go over data-structures, basic and advanced algorithms for graph theory, complexity/accuracy trade-offs, and even combinatorial game theory.

This course has received financial support from the Patrick and Lina Drahi Foundation.

  • Ways to express a computational problem (such as pathfinding) using graph theory
  • How to choose the appropriate algorithm to solve the given computational problem
  • How to code the algorithmic solution in python
  • Methods for evaluating the proposed solution in terms of its complexity (amount of resources, scalability) or performance (accuracy, latency)

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Prerequisite

Some familiarity with Python 3 and basic mathematics.

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Syllabus

Week 1:Fundamentals of Graph Theory, Problem Solving, Good Programming Practices
Week 2: Graph Traversal, Routing, Queuing Structures
Week 3:Shortest Paths, Min-Heaps, Algorithmic Complexity
Week 4:NP-Completeness, Traveling Salesman Problem, Backtracking
Week 5:Heuristics, Greedy Approaches, Accuracy/Complexity tradeoff
Week 6:Combinatorial Game Theory, Winning Strategies

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Instructors

Vincent Gripon
Associate Professor
IMT Atlantique

Patrick Meyer
Professor
IMT Atlantique

Nicolas Farrugia
Associate Professor
IMT Atlantique

Carlos Eduardo Rosar Kos Lassance
Ph.D. Student
IMT Atlantique

Ghouti Boukli Hacene
Ph.D. Student
IMT Atlantique

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Content Designer

Institut Mines-Télécom

Institut Mines-Télécom is France’s premier group of engineering and management graduate schools. Closely connected to industry, Institut Mines-Télécom is focused on the transformations of the 21st century in 4 key areas: Digital technologies, Energy, Ecology and Production. We train the engineers, managers, and PhDs who will be tomorrow’s leaders in these transformations.

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