CS-DS-ALGO.AE1
Beginner's Guide to Data Structures & Algorithms
As the ultimate learning manual for self-taught programmers, it bridges the gap between programming and computer science fundamentals.
- Practice in 25 Laboratorios prácticos — nothing to install
- 19 Lecciones interactivas y 95 topics mapped to the official exam objectives
- 177 Preguntas del examen de práctica
Intermediate A tu propio ritmo · 1 año de acceso
25 LiveLabs prácticos
Practice real IT tasks in guided environments.
- Entornos reales
- Calificación automática
- Sin instalación
19Lecciones interactivas
95Topics
25Laboratorio en vivo
177Preguntas del examen de práctica
154Tarjetas didácticas
154Glosario de términos
01 / Habilidades que obtendrás
What you will be able to do
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No se requiere tarjeta de crédito
This beginner-friendly course has been especially designed to strengthen the computer science fundamentals of self-taught programmers. The Data Structure and Algorithms course provides a comprehensive learning path for aspiring programmers who can build on their programming skills to create large-scale and efficient software applications. Explore the core concepts of data structure including arrays, linked lists, stacks, queues, hash tables, binary trees, binary heaps, and graphs. Study in-depth the underlying principles, operations, and trade-offs of the programming world. Learn to implement problem-solving strategies through algorithms by executing linear search, binary search, and various sorting techniques. Understand how to evaluate an algorithm’s performance by using time complexity and space complexity. By the end of this Data Structure and Algorithm course, you’ll have a strong grasp on computer science for handling complex programming challenges.
- Deep understanding of data structure fundamentals
- Master algorithm techniques like searching, sorting, and problem-solving
- Manage complex problems with step-by-step processes
- Optimize code’s performance with time and space complexities
- Learn from real-world programming challenges
- Understanding advanced computer science fundamentals
- Enhanced readiness for technical round interviews
- Ability to independently explore new programming concepts
- Writing effective and efficient codes
- Ability to identify and fix coding issues
Target Career Roles
- Programador
- Científico de datos
02 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
19 Lecciones interactivas · 95 topics01 Introduction 5 topics +
- What You Will Learn
- Who Is This Course For?
- Self-Taught Success Stories
- Getting Started
- Sticking with It
02 What Is an Algorithm 12 topics · 1 Laboratorio en vivo +
- Analyzing Algorithms
- Constant Time
- Logarithmic Time
- Linear Time
- Log-Linear Time
- Quadratic Time
- Cubic Time
- Exponential Time
- Best-Case vs. Worst-Case Complexity
- Space Complexity
- Why Is This Important?
- Challenge
1 Laboratorio en vivo in this lesson — see the labs panel →
03 Recursion 2 topics · 2 Laboratorio en vivo +
- When to Use Recursion
- Challenge
2 Laboratorio en vivo in this lesson — see the labs panel →
04 Search Algorithms 6 topics · 2 Laboratorio en vivo +
- Linear Search
- When to Use a Linear Search
- Binary Search
- When to Use a Binary Search
- Searching for Characters
- Challenge
2 Laboratorio en vivo in this lesson — see the labs panel →
05 Sorting Algorithms 8 topics · 2 Laboratorio en vivo +
- Bubble Sort
- When to Use Bubble Sort
- Insertion Sort
- When to Use Insertion Sort
- Merge Sort
- When to Use Merge Sort
- Sorting Algorithms in Python
- Challenge
2 Laboratorio en vivo in this lesson — see the labs panel →
06 String Algorithms 5 topics · 2 Laboratorio en vivo +
- Anagram Detection
- Palindrome Detection
- Last Digit
- Caesar Cipher
- Challenge
2 Laboratorio en vivo in this lesson — see the labs panel →
07 Math 7 topics · 3 Laboratorio en vivo +
- Binary
- Bitwise Operators
- FizzBuzz
- Greatest Common Factor
- Euclid's Algorithm
- Primes
- Challenge
3 Laboratorio en vivo in this lesson — see the labs panel →
08 Self-Taught Inspiration: Margaret Hamilton +
09 What Is a Data Structure 2 topics +
- Data Structure and its Types
- Challenge
10 Arrays 7 topics · 2 Laboratorio en vivo +
- Array Performance
- Creating an Array
- Moving Zeros
- Combining Two Lists
- Finding the Duplicates in a List
- Finding the Intersection of Two Lists
- Challenge
2 Laboratorio en vivo in this lesson — see the labs panel →
11 Linked Lists 6 topics · 2 Laboratorio en vivo +
- Linked List Performance
- Create a Linked List
- Search a Linked List
- Removing a Node from a Linked List
- Finding a Linked List Cycle
- Challenges
2 Laboratorio en vivo in this lesson — see the labs panel →
12 Stacks 6 topics · 2 Laboratorio en vivo +
- When to Use Stacks
- Creating a Stack
- Using Stacks to Reverse Strings
- Min Stack
- Stacked Parentheses
- Challenges
2 Laboratorio en vivo in this lesson — see the labs panel →
13 Queues 5 topics · 1 Laboratorio en vivo +
- When to Use Queues
- Creating a Queue
- Python's Built-In Queue Class
- Create a Queue Using Two Stacks
- Challenge
1 Laboratorio en vivo in this lesson — see the labs panel →
14 Hash Tables 4 topics · 2 Laboratorio en vivo +
- When to Use Hash Tables
- Characters in a String
- Two Sum
- Challenge
2 Laboratorio en vivo in this lesson — see the labs panel →
15 Binary Trees 6 topics · 2 Laboratorio en vivo +
- When to Use Trees
- Creating a Binary Tree
- Breadth-First Tree Traversal
- More Tree Traversals
- Invert a Binary Tree
- Challenges
2 Laboratorio en vivo in this lesson — see the labs panel →
16 Binary Heaps 4 topics · 1 Laboratorio en vivo +
- When to Use Heaps
- Creating a Heap
- Connecting Ropes with Minimal Cost
- Challenge
1 Laboratorio en vivo in this lesson — see the labs panel →
17 Graphs 4 topics · 1 Laboratorio en vivo +
- When to Use Graphs
- Creating a Graph
- Dijkstra's Algorithm
- Challenge
1 Laboratorio en vivo in this lesson — see the labs panel →
18 Self-Taught Inspiration: Elon Musk +
19 Next Steps 6 topics +
- What’s Next?
- Climbing the Freelance Ladder
- How to Get an Interview
- How to Prepare for a Technical Interview
- Additional Resources
- Final Thoughts
Laboratorios prácticos Our edge
25 Laboratorio en vivos- Iterating Through a List
- Printing the Numbers Recursively
- Calculating the Factorial of a Number Recursively
- Performing a Linear Search
- Performing a Binary Search
- Using a Bubble Sort Algorithm
- Using an Insertion Sort Algorithm
- Determining Anagrams
- Determining a Palindrome
- Implementing FizzBuzz
- Finding the Greatest Common Factor of Two Numbers
- Determining a Prime Number
- Locating All the Zeros to the End of a List
- Combining Two Lists
- Creating a Linked List
- Finding a Linked List Cycle
- Tracking Stack's Biggest Number
- Using Stacked Parentheses
- Creating a Queue Using Two Stacks
- Removing All Duplicate Words
- Counting All the Characters in a String
- Using a Breadth-First Search
- Inverting a Binary Tree
- Creating a Heap
- Implementing Dijkstra's Algorithm
Los laboratorios se ejecutan en tu navegador; no hay nada que instalar.
03 / Preguntas frecuentes
Preguntas antes de empezar
How to learn DSA as a beginner?+
Learning Data Structure & Algorithms from scratch is a daunting task especially for someone who doesn’t have any programming background. Start with mastering a programming language (Python, Java, C++). Then you’ll have to understand the algorithm concepts and how it works. Consistent practice of complex programming and coding issues will help you build your own projects. To facilitate this learning journey, uCertify provides a brilliant online platform for all learners.
What are the prerequisites for this Data Structures online course?+
None. Whether you are a beginner in the field of coding or you want to reinforce your understanding of computer science or you are preparing for a technical round coding interview, this course is suitable for you. However, some bit of experience with programming would help understand the topics better.
How will this self-taught Computer Science 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 a high-paid job.
Which is the best Data Structure and Algorithms course for beginners?+
This depends on your learning style, budget, and time constraints. However, while choosing the best course for beginners, we suggest you pick an online course like this Data Structure and Algorithm course.
Where do I get the support as a DSA self-learner?+
With uCertify, you'll have access to various support options throughout the course, such as 24/7 support team, downloadables, hands-on labs, gamified testpreps, video tutorials, and more.
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- 1 año de acceso completo
- 25 LiveLab incluido
- Certificado de finalización
No se requiere tarjeta de crédito