With the importance of big data and data analysis in today’s world, combing through hours of data has become a huge problem that needs to be solved. This is where Multithreading and Parallel computing can help!
Multithreading is a simple technique that simplifies and speeds up processes by allowing the use of a single set of code by several processors at different stages of execution. This reduces the time it would take to manually write and execute these codes by hand. On the other hand, parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously. What it basically does is divides larger problems into smaller and executable ones that can be solved at the same time.
If you want to master Multithreading and Parallel Computing in an easy and simple manner, then this is the PERFECT course for you!
Our Multithreading and Parallel computing course has been designed for Java newbies who understand Java, but have not yet succeeded with this complex process that can help simplify their lives. Designed by industry veteran Holczer Balazs, who has a world of knowledge when it comes to Java, this course will help you break down these two difficult process into simple and easy to learn concepts. The best part is that this video comes packed with examples so you know exactly how to get about working with multithreading and parallel computing.
In this course, you will learn:
Basic multithreading including concepts such as process vs thread, threads, runnables, volatile, join(), notify (), low and high level concurrency
Solve complex problems with multithreading such as library project, dining-philosophers problem, etc
How to work with different parallel algorithms such as data structure, graph or sorting algorithms and how to boost these algorithms with parallel computing
Enroll now and join the big leagues of multithreaders with this Java course!
About the Instructor
My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist and later on I decided to get a master degree in applied mathematics. 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. Quantitative analysts use these algorithms and numerical techniques on daily basis so in my opinion these topics are definitely worth learning.
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