Artificial Intelligence I Basics and Games in Java udemy course

Artificial Intelligence I: Basics and Games in Java

Download this Udemy course guide on how to create smart applications, AI, genetic algorithms, pruning, heuristics and metaheuristics which is Udemy free download course.

 

What you’ll learn

After downloading this course you will:-

  • Get a good grasp of artificial intelligence
  • Understand how AI algorithms work
  • Able to create AI algorithms on your own from scratch
  • Understand meta-heuristics

Requirements

  • Basic Java (SE)
  • Some basic algorithms ( maximum/minimum finding )
  • Basic math (functions)

Description

This course is all about the fundamental concepts of artificial intelligence. This field is getting very popular & hot nowadays because these learning algorithms are being used in several fields from software engineering to banking investments plans. By use of learning algorithms can be used to recognize patterns, in this case, it can help us detecting cancer just an example. We can also con instruct algorithms that can help guess about stock price movement in the market.

In this course, it is divided into the following sections and their respective topics are also listed beneath them.

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Section 1:

  • pathfinding algorithms
  • graph traversal (BFS and DFS)
  • enhanced search algorithms
  • A* search algorithm

Section 2:

  • basic optimization algorithms
  • brute-force search
  • stochastic search and hill-climbing algorithm

Section 3:

  • heuristics and meta-heuristics
  • tabu search
  • simulated annealing
  • genetic algorithms
  • particle swarm optimization

Section 4:

  • minimax algorithm
  • game trees
  • applications of game trees in chess
  • tic tac toe game and its implementation

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.

The 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 a 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!

Who this course is for:

  • This course is meant for students or anyone who interested in programming and have some background in basic Java





 

Created by Holczer Balazs
Last updated 4/2019
English
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Size: 1.24 GB

https://www.udemy.com/artificial-intelligence-games-in-java/.

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