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This book will take you through basic to advanced data structures and algorithms. Data structures define how data is arranged in memory for fast and efficient access. An algorithm is a finite set of unambiguous instructions to solve problems by manipulating various data structures. Designing an efficient algorithm is a very important skill that all software companies pursue. Most of the interviews for software companies are focused on knowledge of data structures and algorithms. Apart from knowing a programming language, you also need to have a good command of these key computer fundamentals to not only crack the interview but also excel in your jobs as a software engineer.
You should have a working knowledge of Visual Basic programming language. You are not an expert in the Visual Basic language, but you are well familiar with concepts of classes, functions, references and recursion.
Who should take this course?
If you’re planning to pursue a career in the Visual Basic language, get better at it and apply for a job, this book is best for you. If you can put a reasonable amount of time into this book by reading various concepts and solving the various problems on data structures, you can become an expert in data structures and algorithms.
You can download the code of solved examples in the book from the author's GitHub repositories at https: GitHub.com/Hemant-Jain-Author. Hear the author had solved examples in various programming languages like C, C  , C#, Java, Python, javascript, Swift, GoLang, Ruby, etc.
CHAPTER 0: ABOUT THIS BOOK
CHAPTER 1: ALGORITHMS ANALYSIS
CHAPTER 2: APPROACH TO SOLVE PROBLEMS
CHAPTER 3: ABSTRACT DATA TYPE
CHAPTER 4: SORTING
CHAPTER 5: SEARCHING
CHAPTER 6: LINKED LIST
CHAPTER 7: STACK
CHAPTER 8: QUEUE
CHAPTER 9: TREE
CHAPTER 10: PRIORITY QUEUE / HEAPS
CHAPTER 11: HASH TABLE
CHAPTER 12: GRAPHS
CHAPTER 13: STRING ALGORITHMS
CHAPTER 14: ALGORITHM DESIGN TECHNIQUES
CHAPTER 15: BRUTE FORCE ALGORITHM
CHAPTER 16: GREEDY ALGORITHM
CHAPTER 17: DIVIDE AND CONQUER
CHAPTER 18: DYNAMIC PROGRAMMING
CHAPTER 19: BACKTRACKING
CHAPTER 20: COMPLEXITY THEORY
APPENDIX