Graph Algorithms, Genetic Algorithms, Simulated Annealing, Swarm Intelligence, Minimax, Heuristics and Meta-Heuristics
Get a good grasp of artificial intelligence
Understand graph search algorithms - BFS, DFS and A* search
Understand meta-heuristics
Understand how AI algorithms work
Testing Concept
Preview 00:30
This course is about the fundamental concepts of artificial intelligence. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detecting cancer for example. We may construct algorithms that can have a very good guess about stock price movement in the market.
Preview 00:20
In the first chapter we are going to talk about the basic graph algorithms. Several advanced algorithms can be solved with the help of graphs, so as far as I am concerned these algorithms are the first steps.
Second chapter is about local search: finding minimum and maximum or global optimum in the main. These searches are used frequently when we use regression for example and want to find the parameters for the fit. We will consider basic concepts as well as the more advanced algorithms: heuristics and meta-heuristics.
The last topic will be about minimax algorithm and how to use this technique in games such as chess or tic-tac-toe, how to build and construct a game tree, how to analyze these kinds of tree like structures and so on. We will implement the tic-tac-toe game together in the end.
Thanks for joining the course, let's get started!
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Cras luctus ultrices lorem quis tempus. Donec sed nunc faucibus, pellentesque ligula eget, congue augue.