Algorithms and Data Structures in Java

Curriculum:
– Introduction
– Arrays
– Linked Lists
– Stacks & Queues
– Binary Search Trees
– Balanced Trees: AVL Trees
– Balanced Trees: Red-Black Trees
– Splay Trees
– B-Trees
– Binary Heaps
– Hashtables
– Source Code & Slides

Algorithms and Data Structures in Java Part II
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 7 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.

First, we are going to discuss prefix trees: modern search engines for example use these data structures quite often. When you make a google search there is an autocomplete feature because of the underlying trie data structure. It is also good for sorting: hashtables do not support sort operation but on the other hand, tries do support.

Substring search is another important field of computer science.You will learn about Boyer-Moore algorithm and we will discuss brute-force approach as well as Raabin-Karp method.

The next chapter is about sorting. How to sort an array of integers, doubles, strings or custom objects? We can do it with bubble sort, insertion sort, mergesort or quicksort. You will learn a lot about the theory as well as the concrete implementation of these important algorithms.

The last lectures are about data compression: run-length encoding, Huffman encoding and LZW compression.

Hope you will like the course, let’s get started!

Who is the target audience?
This course is meant for university students with quantitative background (mathematics, computer science) but anyone with core java knowledge can get a good grasp of the lectures.

Curriculum:
– Introduction
– Prefix Tree – Tries
– Ternary Search Tree
– Substring Search
– Strings
– Basic Sorting Algorithms
– Data Compression
– Source Code & Slides