Data Structures and Algorithms with C++ Training Course

Data Structure and Algorithms with C++

Build efficient programs by learning how to implement data structures using algorithmic techniques and solve various computational problems using the C++ programming language.

Course Overivew

  • Learn C++ programming language, pointers and arrays, classes, recursion, stacks, queues, lists, tables, trees, binary trees, search trees, heaps and priority queues; sorting, hashing, garbage collection, storage management; and the rudiments of the analysis of algorithms.
  • Learn How to implement linear and non-linear data structures. How to implement stack and queue abstract data types using arrays and linked lists. How to analyze the efficiency of various algorithms – time and space complexity. How to implement linear and binary search algorithms and their efficiency analysis. Different sorting algorithms and their implementations.
  • Learn Problem solving using iterative, recursive algorithms, their efficiency analysis and understand various algorithm design strategies.
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Course Benefits:

Lecture 1: Complexity Analysis & Recursion

  • Introduction to Data Structures
  • Execution Time Cases
  • Complexity Analysis Examples
  • Recursion

Lecture 2: Arrays

  • Introduction to Arrays
  • Insertion Operation
  • Deletion Operation
  • Search Operation
  • Traverse Operation
  • Time Complexity & Space Complexity

Lecture 3: Linked List

  • Introduction to Linked Lists
  • Insertion Operation
  • Deletion Operation
  • Search Operation
  • Traverse Operation
  • Time Complexity & Space Complexity

Lecture 4: Stack

  • Introduction to Stack
  • Insertion Operation
  • Deletion Operation
  • Front & Back Operation
  • Time Complexity & Space Complexity

Lecture 5: Queue

  • Introduction to Queue
  • Insertion Operation
  • Deletion Operation
  • Top Operation
  • Time Complexity & Space Complexity

Lecture 6: Deque

  • Introduction to Deque
  • Insertion Operation
  • Deletion Operation
  • Search Operation
  • Traverse Operation
  • Time Complexity & Space Complexity

Lecture 7: STL in C++ (Linear Data Structures)

  • Linear Data Structures in C++
  • Vector
  • List
  • Stack
  • Queue
  • Deque

Lecture 8: Binary Tree

  • Introduction to Binary Tree
  • Traverse Operation
  • BFS vs DFS for Binary Tree
  • Search Operation
  • Deletion Operation
  • Time Complexity & Space Complexity

Lecture 9: Binary Search Tree

  • Introduction to Binary Search Tree
  • Insertion Operation
  • Deletion Operation
  • Search Operation
  • Traverse Operation
  • Time Complexity & Space Complexity
  • Balanced Binary Tree Property

Lecture 10: Self Balancing Binary Search Tree

  • Introduction to AVL Tree
  • Insertion Operation
  • Deletion Operation
  • Search Operation
  • Traverse Operation
  • Time Complexity & Space Complexity

Lecture 11: Heap Tree

  • Introduction to Heap Tree
  • Insertion Operation
  • Deletion Operation
  • Top Operation
  • Time Complexity & Space Complexity

Lecture 12: Graphs

  • Introduction to Graphs
  • Directed vs Undirected Graph
  • Breadth First Traverse
  • Depth First Traverse
  • Cyclic vs Acyclic Graph
  • Connected vs Disconnected Graph

Lecture 13: Hash Tables

  • Introduction to Hash Tables
  • Collision Resolution
  • Separate Chaining
  • Open Addressing
  • Double Hashing
  • Rehashing

Lecture 14: STL in C++ (Non-Linear Data Structures)

  • Non-Linear Data Structures in C++
  • Set
  • Multi-set
  • Map
  • Multi-map
  • Priority Queue

Lecture 15: Analysis of Algorithms

  • Analysis Methods in Time & Space Complexity
  • Substitution Method
  • Recurrence Tree Method
  • Master Method

Lecture 16: Sorting Algorithms

  • Bubble Sort
  • Insertion Sort
  • Selection Sort
  • Shell Sort
  • Merge Sort
  • Quick Sort
  • Heap Sort
  • Counting Sort
  • Bitonic Sort
  • Radix Sort
  • Bucket Sort
  • Pigeonhole Sort
  • Tim Sort
  • Cartesian Sort

Lecture 17: Searching Algorithms

  • Linear Search
  • Binary Search
  • Ternary Search
  • Sublist Search
  • Exponential Search
  • Jump Search
  • Fibonacci Search
  • Interpolation Search

Lecture 18: Divide and Conquer Algorithms

  • Binary Search
  • Merge Sort & Quick Sort
  • Fast Power
  • Closest Pair of Points
  • Count Inversions
  • Multiply Two Polynomials
  • Strassen’s Matrix Multiplication
  • Karatsuba Algorithm for Fast Multiplication
  • Design and implement an object-oriented program in the C++ language, including defining classes that encapsulate data structures and algorithms.
  • Select and implement appropriate data structures that best utilize resources to solve a computational problem.
  • Analyze the running time and space needs of an algorithm, asymptotically to ensure it is appropriate at scale, including for huge data.
  • Prepare for advanced topics in Computer Science with the foundational knowledge of object data structures needed to implement and call advanced library functions.
  • Apply graph and string algorithms to solve real-world challenges: finding shortest paths on huge maps and assembling genomes from millions of pieces.
  • Apply basic algorithmic techniques such as greedy algorithms, searching, sorting and dynamic programming to solve programming challenges.
  • Apply various data structures such as stack, queue, hash table, priority queue, binary search tree, graph and string to solve programming challenges.
  • Solve complex programming challenges using advanced techniques in dynamic programming, complex graph problems, mathematical and geometric algorithms.
  • After completing this course, you will be equipped for the job roles like Programmer, Web/App Developer, Analyst and Software Engineer thus, you can build an outstanding career.
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Prerequisites

This course is available at :

Classroom Training

Cairo
Giza
Onsite

Online Training

Virtual Interactive Instructor LED
Self-Paced Training

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