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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.

(CS-DS-ALGO.AE1) / ISBN : 978-1-64459-429-2
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About This Course

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.

Skills You’ll Get

  • 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
Download Course Outline

1

Introduction

  • What You Will Learn
  • Who Is This Course For?
  • Self-Taught Success Stories
  • Getting Started
  • Sticking with It
2

What Is an Algorithm

  • 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
3

Recursion

  • When to Use Recursion
  • Challenge
4

Search Algorithms

  • Linear Search
  • When to Use a Linear Search
  • Binary Search
  • When to Use a Binary Search
  • Searching for Characters
  • Challenge
5

Sorting Algorithms

  • 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
6

String Algorithms

  • Anagram Detection
  • Palindrome Detection
  • Last Digit
  • Caesar Cipher
  • Challenge
7

Math

  • Binary
  • Bitwise Operators
  • FizzBuzz
  • Greatest Common Factor
  • Euclid's Algorithm
  • Primes
  • Challenge
8

Self-Taught Inspiration: Margaret Hamilton

9

What Is a Data Structure

  • Data Structure and its Types
  • Challenge
10

Arrays

  • Array Performance
  • Creating an Array
  • Moving Zeros
  • Combining Two Lists
  • Finding the Duplicates in a List
  • Finding the Intersection of Two Lists
  • Challenge
11

Linked Lists

  • Linked List Performance
  • Create a Linked List
  • Search a Linked List
  • Removing a Node from a Linked List
  • Finding a Linked List Cycle
  • Challenges
12

Stacks

  • When to Use Stacks
  • Creating a Stack
  • Using Stacks to Reverse Strings
  • Min Stack
  • Stacked Parentheses
  • Challenges
13

Queues

  • When to Use Queues
  • Creating a Queue
  • Python's Built-In Queue Class
  • Create a Queue Using Two Stacks
  • Challenge
14

Hash Tables

  • When to Use Hash Tables
  • Characters in a String
  • Two Sum
  • Challenge
15

Binary Trees

  • When to Use Trees
  • Creating a Binary Tree
  • Breadth-First Tree Traversal
  • More Tree Traversals
  • Invert a Binary Tree
  • Challenges
16

Binary Heaps

  • When to Use Heaps
  • Creating a Heap
  • Connecting Ropes with Minimal Cost
  • Challenge
17

Graphs

  • When to Use Graphs
  • Creating a Graph
  • Dijkstra's Algorithm
  • Challenge
18

Self-Taught Inspiration: Elon Musk

19

Next Steps

  • What’s Next?
  • Climbing the Freelance Ladder
  • How to Get an Interview
  • How to Prepare for a Technical Interview
  • Additional Resources
  • Final Thoughts

1

What Is an Algorithm

  • Iterating Through a List
2

Recursion

  • Printing the Numbers Recursively
  • Calculating the Factorial of a Number Recursively
3

Search Algorithms

  • Performing a Linear Search
  • Performing a Binary Search
4

Sorting Algorithms

  • Using a Bubble Sort Algorithm
  • Using an Insertion Sort Algorithm
5

String Algorithms

  • Determining Anagrams
  • Determining a Palindrome
6

Math

  • Implementing FizzBuzz
  • Finding the Greatest Common Factor of Two Numbers
  • Determining a Prime Number
7

Arrays

  • Locating All the Zeros to the End of a List
  • Combining Two Lists
8

Linked Lists

  • Creating a Linked List
  • Finding a Linked List Cycle
9

Stacks

  • Tracking Stack's Biggest Number
  • Using Stacked Parentheses
10

Queues

  • Creating a Queue Using Two Stacks
11

Hash Tables

  • Removing All Duplicate Words
  • Counting All the Characters in a String
12

Binary Trees

  • Using a Breadth-First Search
  • Inverting a Binary Tree
13

Binary Heaps

  • Creating a Heap
14

Graphs

  • Implementing Dijkstra's Algorithm

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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.

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.

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.

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.

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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