Hello and welcome to this Artificial Intelligence 1 course currently trending online today that will show you step by step approach on how to create smart apps, AI, genetic Algorithm, pruning, heuristics and also metaheuristics.
Do you wish to create super-smart applications? Understand the fundamental concepts of Artificial Intelligence? Know-how AI Algorithm works? Then this Artificial Intelligence 1 course is for you.
Artificial intelligence is taking over today, your ability to understand the concepts of AI will give you an upper hand or an edge in the world’s market.
ThisArtificial Intelligence 1 course is getting interesting day after day because these learning algorithms can be used in several fields from software engineering to investment banking.
Learning algorithms can identify patterns that can help detect cancer, for example. We can build algorithms that can have a very good assumption about the movement of stock prices in the market.
4 SECTIONS OF THIS COURSE
There are 4 different sections, the first section will show you pathfinding algorithms, graph traversals, enhanced search and also A search algorithm.
The second section will teach you basic optimization algorithms, brute-force search and also stochastic search and hill-climbing algorithm.
The third section will show you heuristics and meta-heuristics, tabu search, simulated annealing, genetic algorithms and also particle swarm optimization and lastly the 4 section will teach you minimax algorithm, games tree, applications of games trees in chess and also tic tac toe game and its implementation.
In the first chapter we will talk about basic graphical algorithms. Many advanced algorithms can be solved with the help of graphics. As far as I’m concerned, these algorithms are the first steps.
The second chapter on local research: mainly finding the global minimum, maximum or optimum. These searches are often used when we use regression, for example, and we want to find parameters for the fit. We will examine the basic concepts and the most advanced algorithms: heuristics and meta inference.
The last topic will be about the minimax algorithm, how to use this technique in games such as chess or tic-tac-toe, how to build and create a game tree, how to analyze this type of tree-like structure, etc. We will implement Tic-Tac-Toe together at the end.
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