Artificial Intelligence I: Basics and Games in Java (Udemy.com)

A guide how to create smart applications, AI, genetic algorithms, pruning, heuristics and metaheuristics

Created by: Holczer Balazs

Produced in 2021

icon
What you will learn

  • 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

icon
Quality Score

Content Quality
/
Video Quality
/
Qualified Instructor
/
Course Pace
/
Course Depth & Coverage
/

Overall Score : 88 / 100

icon
Course Description

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.
Section 1:
  • path findinf algorithms
  • graph traversal (BFS and DFS)
  • enhanced search algorihtms
  • 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.
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!Who this course is for:
  • This course is meant for students or anyone who interested in programming and have some background in basic Java

icon
Instructor Details

placeholder

Hi!
My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model.
Take a look at my website if you are interested in these topics!

icon
More courses by Holczer Balazs

Basics of Software Architecture & Design Patterns in Java

$11.99

Artificial Intelligence II - Neural Networks in Java

$11.99

Quantitative Finance & Algorithmic Trading in Python

$11.99

Introduction to Collections & Generics in Java

$11.99

Multithreading and Parallel Computing in Java

$11.99

Introduction to Machine Learning & Deep Learning in Python

$11.99

icon
More artificial intelligence courses

Convolutional Neural Networks

Free

AI For Everyone

Free

A Crash Course in Data Science

Free

Sequence Models

Free

Open Source tools for Data Science

Free

icon
Reviews

4.4

50 total reviews

5 star 4 star 3 star 2 star 1 star
% Complete
% Complete
% Complete
% Complete
% Complete

By Matthew

I found the topics did not provide enough detail, and what was provided was slow and dry.

The video examples are not all provided in the example code. An example of this, as of 21/08/18 the A Star video code is completely difference to the source code. In addition the source code is broken and not implemented correctly.

By John Chapman

easy paced and concepts described well

By Cody L. Nicholson

The instructor explains the algorithms well by using demos that make them easy to understand.

By György Beszedics

Great course from Balazs as always. I would have appreciated a bit more real-world examples of the use of the algorithms instead of just finding the min or max value of a function.

By Keith Emery

Nice, fast-paced course with useful objectives.

By Bohdan Kripak

I'm getting LOLs on your "lots of lots of ...". Great course!

By Murali

course is good.But in the source code i see difference between what author explains in video and attachment.Being from no computer science background it's difficult sometimes to understand the logic in source code.

By José Esteves de Souza Neto

The guy is a genius! Besides he explains everything with such a clearness of mind that even if he speeds up the pace you can follow along! Definitely I will take ALL the courses by this Author!

By AKM Islam

All of his courses are awesome.I highly recommend anybody to take the course for learning AI.

By Kashif Nazir

This course was absolutely fantastic. Great instructor and very interesting, well-organized content. Thanks a lot!

By Lawrence Hope

Very good explanation of optimization problems and methods. Familiarity with Java and Eclipse helps a lot.

By John Lavelle

Content is good, however, references are made to content that is not available (e.g. Dijkstra's Algorithm in the Graph Search section).