DS-ALGO-CPLUS.AP1
Data Structure and Algorithm with C++
Master your coding skills with C++ programming for Data Structures. Get ready to ace those technical rounds of job interviews.
- Practice in 36 Laboratorios prácticos — nothing to install
- 14 Lecciones interactivas y 128 topics mapped to the official exam objectives
- 180 Preguntas del examen de práctica
Intermediate A tu propio ritmo · 1 año de acceso
36 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
14Lecciones interactivas
128Topics
36Laboratorio en vivo
180Preguntas del examen de práctica
53Tarjetas didácticas
53Glosario de términos
01 / Habilidades que obtendrás
What you will be able to do
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No se requiere tarjeta de crédito
The Data Structure and Algorithm with C++ course offers a comprehensive learning of the advanced topics along with a rich collection of practice exercises for deeper understanding. Besides learning the fundamentals of basic data structures like arrays, linked lists, stacks, and queues, you’ll also be working with advanced data structures trees (binary, binary search, AVL, and heap), graphs, and hash tables. Learn how to measure the efficiency of an algorithm using time(how long it takes) and space(space/memory) complexity metrics. For the practical implications, you’ll be sorting algorithms (bubble, insertion, selection, merge, quick, heap) and searching techniques (linear, binary). The course further extends to dynamic programming, greedy algorithms, and advanced tree structures like B-trees. Get access to the C++ Standard Template Library (STL) that features containers (vector, list, deque, stack, queue, priority queue, map, set) and iterators. The course includes exercises and solutions that are useful for both students and professionals. It aims to help you prepare for technical job interviews that typically involve coding questions.
- Implementing various data structures including arrays, linked lists, stacks, queues, trees, graphs, and hash tables
- Optimizing algorithms through time and space complexities
- Enhanced problem-solving skills
- Sorting, searching, and computing via algorithms
- Enhanced C++ programming skills
- Using the Standard Template Library (STL)
- Gain confidence to answer coding questions during technical interviews
- Applying data structures and algorithms for analytical thinking.
Target Career Roles
- Ingeniero de software
- desarrollador web
- desarrollador de aplicaciones
- científico de datos
- analista de sistemas
- ingeniero de control de calidad
- desarrollador de juegos
- administrador de bases de datos
- ingeniero de aprendizaje automático
- programador informático.
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
14 Lecciones interactivas · 128 topics01 Preface 5 topics +
- Purpose/Goals
- Approach
- Summary of the Most Significant Changes in the Fourth Edition
- Overview
- Exercises
02 Programming: A General Overview 10 topics · 2 Laboratorio en vivo +
- What’s This Course About?
- Mathematics Review
- A Brief Introduction to Recursion
- C++ Classes
- C++ Details
- Templates
- Using Matrices
- Summary
- Exercises
- References
2 Laboratorio en vivo in this lesson — see the labs panel →
03 Algorithm Analysis 7 topics · 3 Laboratorio en vivo +
- Mathematical Background
- Model
- What to Analyze
- Running-Time Calculations
- Summary
- Exercises
- References
3 Laboratorio en vivo in this lesson — see the labs panel →
04 Lists, Stacks, and Queues 9 topics · 7 Laboratorio en vivo +
- Abstract Data Types (ADTs)
- The List ADT
- vector and list in the STL
- Implementation of vector
- Implementation of list
- The Stack ADT
- The Queue ADT
- Summary
- Exercises
7 Laboratorio en vivo in this lesson — see the labs panel →
05 Trees 11 topics · 11 Laboratorio en vivo +
- Preliminaries
- Binary Trees
- The Search Tree ADT—Binary Search Trees
- AVL Trees
- Splay Trees
- Tree Traversals (Revisited)
- B-Trees
- Sets and Maps in the Standard Library
- Summary
- Exercises
- References
11 Laboratorio en vivo in this lesson — see the labs panel →
06 Hashing 12 topics · 4 Laboratorio en vivo +
- General Idea
- Hash Function
- Separate Chaining
- Hash Tables without Linked Lists
- Rehashing
- Hash Tables in the Standard Library
- Hash Tables with Worst-Case O(1) Access
- Universal Hashing
- Extendible Hashing
- Summary
- Exercises
- References
4 Laboratorio en vivo in this lesson — see the labs panel →
07 Priority Queues (Heaps) 12 topics · 2 Laboratorio en vivo +
- Model
- Simple Implementations
- Binary Heap
- Applications of Priority Queues
- d-Heaps
- Leftist Heaps
- Skew Heaps
- Binomial Queues
- Priority Queues in the Standard Library
- Summary
- Exercises
- References
2 Laboratorio en vivo in this lesson — see the labs panel →
08 Sorting 15 topics · 3 Laboratorio en vivo +
- Preliminaries
- Insertion Sort
- A Lower Bound for Simple Sorting Algorithms
- Shellsort
- Heapsort
- Mergesort
- Quicksort
- A General Lower Bound for Sorting
- Decision-Tree Lower Bounds for Selection Problems
- Adversary Lower Bounds
- Linear-Time Sorts: Bucket Sort and Radix Sort
- External Sorting
- Summary
- Exercises
- References
3 Laboratorio en vivo in this lesson — see the labs panel →
09 The Disjoint Sets Class 10 topics · 1 Laboratorio en vivo +
- Equivalence Relations
- The Dynamic Equivalence Problem
- Basic Data Structure
- Smart Union Algorithms
- Path Compression
- Worst Case for Union-by-Rank and Path Compression
- An Application
- Summary
- Exercises
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
10 Graph Algorithms 10 topics · 3 Laboratorio en vivo +
- Definitions
- Topological Sort
- Shortest-Path Algorithms
- Network Flow Problems
- Minimum Spanning Tree
- Applications of Depth-First Search
- Introduction to NP-Completeness
- Summary
- Exercises
- References
3 Laboratorio en vivo in this lesson — see the labs panel →
11 Algorithm Design Techniques 8 topics · 1 Laboratorio en vivo +
- Greedy Algorithms
- Divide and Conquer
- Dynamic Programming
- Randomized Algorithms
- Backtracking Algorithms
- Summary
- Exercises
- References
1 Laboratorio en vivo in this lesson — see the labs panel →
12 Amortized Analysis 8 topics +
- An Unrelated Puzzle
- Binomial Queues
- Skew Heaps
- Fibonacci Heaps
- Splay Trees
- Summary
- Exercises
- References
13 Advanced Data Structures and Implementation 9 topics +
- Top-Down Splay Trees
- Red-Black Trees
- Treaps
- Suffix Arrays and Suffix Trees
- k-d Trees
- Pairing Heaps
- Summary
- Exercises
- References
14 Appendix A: Separate Compilation of Class Templates 2 topics +
- Everything in the Header
- Explicit Instantiation
Laboratorios prácticos Our edge
36 Laboratorio en vivos- Using Recursive Function
- Resizing a Matrix
- Implementing the Bisection Method
- Finding Minimum Subsequence Sum
- Implementing Binary Search
- Implementing the STL find Routine
- Working with Lists
- Converting an Infix Expression to Postfix
- Checking for Balancing Brackets
- Reversing a Singly Linked List
- Implementing a Stack Class
- Implementing a Dequeue using a Linked List
- Implementing a Depth-First Traversal in the Child-Sibling Tree
- Converting a Tree into Graph-Assembler Instructions
- Using the findMax Function
- Generating an AVL Tree
- Inserting a Node into an AVL Tree
- Implementing a Splay Tree
- Working with Binary Tree
- Implementing a B-Tree
- Inserting Keys into the B-Tree
- Implementing the map Class
- Implementing a Splay Tree
- Counting Number of Collisions
- Implementing Hopscotch Hashing
- Implementing Cuckoo Hashing
- Implementing Extendible Hashing
- Merging Two Max Heaps
- Implementing Insert Operation in a Binomial Queue
- Implementing Insertion Sort using STL
- Implementing Mergesort without Recursion
- Implementing the Selection Sort Algorithm
- Printing a Maze
- Implementing a Topological Sorting Algorithm
- Solving a Single Source Shortest Path Problem
- Implementing Union Function in Kruskal's Algorithm
- Solving the Longest Common Subsequence Problem
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03 / Preguntas frecuentes
Preguntas antes de empezar
What are the implications of Data structure and Algorithms in C++?+
Data structure refers to the organization and arrangement of data in an IT setup whereas Algorithm is the step-by-step process of using this stored data for desired results. Deep understanding of both the concepts will enable you to write efficient, scalable, and well-structured C++ programs.
Is C++ good for handling data structure and algorithms?+
Yes, with C++ you can access the standard template library (STL) that facilitates the creation and manipulation of complex data structures.
How to choose the right data structure for C++?+
This would typically depend on the type of data, operations, memory constraints, and time complexity. Once you have an understanding of these factors, you can choose the most appropriate data set for your application.
How will the Data structure and Algorithms (DSA) in C++ course benefit me?+
It will improve your problem-solving skills and enhance your C++ programming skills. With a solid foundation in DSA you’ll be able to crack the coding job interviews with ease and confidently place yourself in high-paid jobs.
Which is the best DSA course on uCertify?+
Essential Algorithms: A practical Approach to Computer Algorithms Using Python and C#. It teaches you how to write codes in both the programming languages.
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Enhance your problem-solving skills to ace those job interviews.
- 1 año de acceso completo
- 36 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito