This course is about data structures and algorithms. We are going to implement the problems in Java, but I try to do it as generic as possible: so the core of the algorithms can be used in C++ or Python. The course takes approximately 11 hours to complete. I highly recommend typing out these data structures several times on your own in order to get a good grasp of it.
In the first part of the course we are going to learn about basic data structures such as linked lists, stacks and queues, heaps and some advanced ones such as AVL trees, red-black trees or hash tables. We will try to optimize each data structure ( for example avoiding obsolete references ) as much as possible.
In each chapter I am going to talk about the theoretical background of each algorithm or data structure, then we are going to write the code on a step by step basis in Eclipse, Java.
Most of the advanced algorithms relies heavily on these topics so it is definitely worth understanding the basics. These principles can be used in several fields: in investment banking, artificial intelligence or electronic trading algorithms on the stock market.
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.