by Tomasz Lelek | Released December 2017 | ISBN: 9781788624428

A comprehensive guide to the algorithms and data structures used when designing architectural solutions and big data applications About This VideoGet acquainted with the core and advanced data structures and algorithms used for day to day applicationsMake your programs work faster and more efficientlyA practical guide with examples to demonstrate how efficient algorithm design principles improve your programming experienceIn DetailPrograms are created from algorithms and data structures. Mastering these is an essential part of your development as a Java programmer. They are the main building blocks for each architectural pattern. Many courses treat data structures and algorithms as a theoretical computer science topics. This course relates every technique back to real-world problems and situations you will face working as a programmer. You will start off with data structures before diving deeper into hash tables and hash functions. This will allow your programs to find the in-memory data they need, even with huge quantities of records stored in the memory. You'll learn to use querying binary search trees. The course will take you through heapsort, quicksort, recursion, and tail recursion algorithms. You'll get familiar with multithreading algorithms and probabilistic algorithms. You'll also understand the importance of advanced data structures and graph algorithms. This will help you to build priority queues and save your time by keeping disgruntled users at bay.User databases and minimal computing requirements are on the rise. It's important to write sophisticated applications and run them with improved performance, and this course helps you write these applications. It will help you to gain in-demand knowledge of key data structures and algorithms and prepare you for the next stage in your career as a developer. Show and hide more Publisher resources Download Example Code

1. Chapter 1 : Basic Data Structures
   • The Course Overview 00:04:12
   • Big O Notation — How to Analyze Algorithms 00:06:23
   • Stacks — Basic Building Blocks of Every Program 00:10:15
   • Linked Lists — When We Need Fast Insertion 00:09:46
   • Arrays — When We Need Fast Lookup 00:06:25
2. Chapter 2 : Hash Tables and Binary Search Trees
   • Hash Tables and Hash Functions — Fast Lookup 00:09:46
   • Hash Functions — How to Distribute Data into Buckets 00:05:27
   • What is a Binary Search Tree? 00:04:18
   • Querying Binary Search Tree — When to Use It Effectively 00:08:31
   • Binary Search Tree — Removing Nodes 00:10:31
3. Chapter 3 : Sorting and Recursion
   • Bubble Sort — Simple Method of Sorting 00:07:25
   • Heapsort — Sorting Using Heap 00:05:12
   • Understanding Recursion 00:06:57
   • Tail Recursion 00:08:24
4. Chapter 4 : Multithreading Algorithms and Probabilistic Data Structures
   • Map/Reduce Paradigm 00:07:40
   • Producer/Consumer Pattern 00:08:17
   • HyperLogLog for Estimating Cardinality of Dataset 00:07:53
   • Bloom Filter for Testing If Sets Contains Element 00:07:53
5. Chapter 5 : Graph Algorithms and Advanced Data Structures
   • How to Represent Graph? 00:05:50
   • Breadth-First Search for Searching in Graph 00:06:45
   • Depth-First Search for Searching in Graph 00:06:26
   • Heaps 00:07:26
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