Data Structures and Algorithms-Deep Dive into Core Concepts from Udemy

What's inside

Learning objectives

Understand the foundational data structures such as arrays, linked lists, stacks, queues, hash tables, graphs and trees,
Gain a thorough understanding of various sorting and searching algorithms, including quicksort, mergesort, and binary search

Delve into graph theory and learn essential graph algorithms, including depth-first search (dfs), breadth-first search (bfs), dijkstra’s algorithm and mst
Develop strong problem-solving skills by applying data structures and algorithms to real-world scenarios and coding challenges.

Understand the foundational data structures such as arrays, linked lists, stacks, queues, hash tables, graphs and trees,
Gain a thorough understanding of various sorting and searching algorithms, including quicksort, mergesort, and binary search
Delve into graph theory and learn essential graph algorithms, including depth-first search (dfs), breadth-first search (bfs), dijkstra’s algorithm and mst
Develop strong problem-solving skills by applying data structures and algorithms to real-world scenarios and coding challenges.

Syllabus

Understand the fundamental data structures like arrays, linked lists, stacks, queues, trees and Graphs

Demo Video -Array Advantages and Disadvantages

Demo Video - Linked Link Introduction

Introduction

Understanding the concept of arrays and their usage in accessing data elements. Implementing array operations such as insertion, deletion, traversal and searching

Introduction to arrays

Inserting an element in an array

Deleting an element from an Array

Traversal and Searching in an Array

Advantages and Disadvantages of arrays

Students will be able to implement, manipulate, and understand the advantages of linked lists over arrays.

Introduction of Linked Lists

Singly Linked Lists - Traversal and Searching

Singly Linked Lists - Insertion at the Beginning and the End

Singly Linked Lists - Insertion at the Middle

Singly Linked Lists - Deletion at the Beginning and the End

Singly Linked Lists - Deletion at the Middle

Circular Singly Linked Lists - Insertion

Circular Singly Linked Lists - Deletion

Doubly Linked Lists - Introduction

Doubly Linked Lists - Insertion at the beginning and the end

Doubly Linked Lists - Insertion at the Middle

Doubly Linked Lists - Deletion at the Beginning and the End

Doubly Linked Lists - Deletion at the Middle

Circular Doubly Linked Lists - Introduction

Circular Doubly Linked Lists - Insertion

Circular Doubly Linked Lists - Deletion

Linked Lists - Advantages, Disadvantages and Applications

Students will be able to implement, manipulate, and utilize stacks to solve a variety of algorithmic problems efficiently.

Stacks Introduction

Stack Implementation Using Array

Stack Implementation Using Array - Advantages, Disadvantages and Applications

Stack Implementation Using Linked Lists

Stack Implementation Using L L - Advantages, Disadvantages and Applications

Stack Applications

Stack Applications - Reversing a List and Balancing Symbols

Stack Applications - Infix to Postfix Conversion 1

Stack Applications - Infix to Postfix Conversion 2

Stack Applications - Infix to Postfix Conversion 3

Stack Applications - Evaluating Postfix Expression

Stack Applications - Recursion

Students will be able to implement queue operations and use them to solve practical problems.

Queue Introduction

Queue Implementation Using Array

Queue Implementation Using Linked List

Types of Queues

Circular Queue - Introduction

Circular Queue - Enqueue Operation

Circular Queue - Dequeue Operation

DEQUE (Double-Ended Queue) - Insertion Operation

DEQUE (Double-Ended Queue) - Deletion Operation

DEQUE (Double-Ended Queue) - Advantages, Disadvantages and Applications

Inserting an Element into the Priority Queue

Deleting an Element from the Priority Queue

Students will have mastered the understanding, implementation, and application of tree data structures and algorithms.

Trees - Introduction

Different Types of Trees

Binary Trees

Operations on Binary Trees - Insertion and Deletion

Tree Traversals

Tree Traversals - In-Order Traversal

Tree Traversals - Pre-Order Traversal

Tree Traversals - Post-Order Traversal

Expression Tree

Binary Search Trees - Searching Operation

Binary Search Trees - Insertion Operation

Binary Search Trees - Deletion Operation

AVL Tree - Rotations (LL, RR, LR, RL)

AVL Tree - Insertion

Students will proficiently understand, implement, and apply graph traversal and path-finding algorithms to solve diverse real-world problems efficiently.

Graphs - Introduction

Graph Traversals - Breadth-First Search (BFS)

Graph Traversals - Depth-First Search (DFS)

Breadth-First Search (BFS) Vs Depth-First Search (BFS)

Minimum Spanning Tree (MST) - Prim's Algorithm

Minimum Spanning Tree (MST) - Kruskal's Algorithm

Topological Sorting

Dijkstra's algorithm

Understand the principles of hashing, implement hash functions and resolve collisions using various hashing techniques.

Hashing - Introduction

Different Hashing Techniques

Collision Resolution Techniques - Linear Probing Method

Collision Resolution Techniques - Quadratic Probing Method

Collision Resolution Techniques - Double Hashing Method

Collision Resolution Techniques - Separate Chaining Method

Students will proficiently understand, implement, and analyze various searching algorithms, enabling them to efficiently locate elements within datasets.

Linear Search

Binary Search - Example

Binary Search - Pseudocode and Time Complexity Analysis

Difference Between Linear Search and Binary Search

Students will proficiently understand, implement, and analyze a variety of sorting algorithms, enhancing their ability to efficiently organize and manipulate data in programming tasks.

Bubble Sort - Example, Pseudocode and Time Complexity Analysis

Insertion Sort - Example

Insertion Sort - Pseudocode and Time Complexity Analysis

Quick Sort - Example

Quick Sort - Pseudocode and Time Complexity Analysis

Merge Sort - Example

Merge Sort - Pseudocode and Time Complexity Analysis

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a robust foundation in data structures and algorithms, enabling learners to write scalable code and navigate complex programming tasks, which is essential for career advancement

Covers a broad spectrum of essential sorting and searching algorithms, empowering learners with the ability to tackle diverse computational challenges, which is highly relevant to industry

Explores graph algorithms like depth-first search (DFS), breadth-first search (BFS), and Dijkstra’s algorithm in depth, with a focus on understanding their practical applications in software engineering

Teaches a variety of data structures, including arrays, linked lists, stacks, queues, hash tables, trees, graphs, heaps, and balanced trees, which are core concepts for efficient programming

Includes demo videos that explain array advantages and disadvantages, which may help learners understand the nuances of data structures and their applications

Requires learners to understand the concept of arrays and their usage in accessing data elements, which may require some learners to review basic programming concepts first

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Structures and Algorithms-Deep Dive into Core Concepts with these activities:

Review Basic Data Structures

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Reinforce your understanding of fundamental data structures before diving into more complex concepts.

Browse courses on Arrays

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Review definitions and properties of arrays, linked lists, stacks, and queues.
Work through simple implementation exercises for each data structure.
Solve basic problems using these data structures.

Review Introduction to Algorithms

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Supplement your learning with a comprehensive algorithms textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Read relevant chapters on data structures and algorithms.
Work through examples and exercises in the book.
Compare the book's explanations with the course material.

Implement Array Operations

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Practice implementing common array operations to solidify your understanding of array manipulation.

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Implement insertion, deletion, and searching in arrays.
Practice array traversal using loops and recursion.
Solve problems involving array manipulation, such as reversing an array or finding the maximum element.

Four other activities

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LeetCode Practice

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Sharpen your problem-solving skills by practicing data structure and algorithm problems on LeetCode.

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Select problems related to the topics covered in the course.
Attempt to solve the problems independently.
Analyze the solutions and learn from your mistakes.

Create a Data Structure Comparison Chart

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Solidify your understanding of different data structures by creating a comparison chart highlighting their strengths and weaknesses.

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Choose several data structures covered in the course.
Research and document the characteristics of each data structure.
Create a chart comparing the data structures based on various criteria.

Build a Simple Search Engine

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Apply your knowledge of data structures and algorithms to build a practical search engine.

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Design data structures to store and index documents.
Implement searching algorithms to retrieve relevant documents.
Optimize search performance using appropriate data structures and algorithms.

Review Cracking the Coding Interview

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Prepare for technical interviews by practicing common data structure and algorithm questions.

View Cracking the Coding Interview: 189 Programming... on Amazon

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Select relevant chapters on data structures and algorithms.
Work through the interview questions and solutions.
Analyze your performance and identify areas for improvement.

Career center

Learners who complete Data Structures and Algorithms-Deep Dive into Core Concepts will develop knowledge and skills that may be useful to these careers:

Software Engineer

A software engineer designs, develops, tests, and maintains software applications. This Data Structures and Algorithms course helps build a foundation in efficient coding practices. The course's comprehensive coverage of data structures, from arrays and linked lists to trees and graphs, provides the knowledge needed to select the right data structure for optimal performance. The emphasis on algorithmic design principles and sorting/searching algorithms enables the software engineer to tackle complex problems effectively. This course also covers DFS, BFS, and Dijkstra’s algorithm, all of which are crucial for any aspiring software engineer.

See salaries and explore the career path for Software Engineer

Full-Stack Developer

A full stack developer works on both the frontend and backend of web applications. This Data Structures and Algorithms course helps build the skills necessary to design and implement efficient and scalable web applications. The course's coverage of fundamental data structures, such as arrays, linked lists, trees, and graphs, is crucial for managing data both on the client-side and server-side. The emphasis on algorithmic design principles and sorting/searching algorithms enables full stack developers to optimize database queries, API endpoints, and user interface rendering. This course truly prepares one to become a full stack developer.

See salaries and explore the career path for Full-Stack Developer

Backend Developer

Backend developers build and maintain the server-side logic and databases that power web applications. The role requires an understanding of data structures and algorithms for efficient data processing and storage. This Data Structures and Algorithms course helps backend developers write scalable and performant code. The course covers fundamental data structures, such as arrays, linked lists, and hash tables, which are essential for managing application data. The focus on algorithmic design principles and sorting/searching algorithms enables backend developers to optimize database queries and API endpoints. This course's coverage of graph algorithms also helps in understanding relationships between data in complex systems.

See salaries and explore the career path for Backend Developer

Mobile Application Developer

Mobile application developers design and build applications for smartphones and tablets. This Data Structures and Algorithms course helps build the skills needed to optimize application performance and create smooth user experiences on mobile devices. The course's coverage of fundamental data structures, such as arrays, linked lists, and hash tables, is crucial for managing data efficiently on resource-constrained mobile devices. The emphasis on algorithmic design principles and sorting/searching algorithms enables mobile application developers to optimize data processing tasks and ensure responsiveness. This course truly prepares one to become a mobile application developer.

See salaries and explore the career path for Mobile Application Developer

Quantitative Analyst

Quantitative analysts, often requiring advanced degrees, develop and implement mathematical models for financial analysis and risk management. This Data Structures and Algorithms course helps them optimize their models and improve their efficiency. The course's coverage of fundamental data structures, such as arrays, linked lists, and trees, helps quantitative analysts manage and manipulate financial data efficiently. The emphasis on algorithmic design principles and sorting/searching algorithms enables them to optimize model performance. This course's coverage of hashing is relevant to financial data analysis.

See salaries and explore the career path for Quantitative Analyst

Machine Learning Engineer

A machine learning engineer develops and implements machine learning models. The models must scale efficiently. This Data Structures and Algorithms course helps build the skills necessary to optimize the performance of these models. The course's exploration of data structures like trees, graphs, and hash tables enables efficient storage and retrieval of data. Additionally, the coverage of graph algorithms like Dijkstra's and MST, along with algorithmic design, provides insight into how to optimize machine learning algorithms. This course provides the essential toolkit for anyone looking to excel as a machine learning engineer.

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Systems Architect

A systems architect designs and oversees the implementation of complex software systems. They should have a deep understanding of data structures and algorithms to make informed decisions about system design and optimization. This Data Structures and Algorithms course helps build the foundations for efficient and scalable system architectures. The course's coverage of various data structures, including trees, graphs, and hash tables, enables systems architects to choose the right structures for different components of the system. The emphasis on algorithmic design principles empowers them to optimize data flow and processing within the system. An aspiring systems architect should take this course.

See salaries and explore the career path for Systems Architect

Research Scientist

Research scientists conduct research to advance knowledge in a particular field, often requiring advanced degrees. A strong understanding of data structures and algorithms is essential for conducting research involving data analysis, modeling, and simulation. Taking this Data Structures and Algorithms course may be useful because it helps research scientists develop efficient algorithms for processing large datasets and solving complex problems. The course's coverage of data structures, such as trees, graphs, and hash tables, enables researchers to choose the right structures for their specific research needs. The emphasis on algorithmic design principles empowers them to optimize their research methods and develop novel solutions.

See salaries and explore the career path for Research Scientist

Game Developer

Game developers create video games for various platforms. This Data Structures and Algorithms course may be useful, as it provides the knowledge needed to optimize game performance and create engaging gameplay experiences. The course's coverage of data structures, such as trees and graphs, is useful for managing game worlds and character relationships. Also, the exploration of algorithmic design principles helps game developers implement efficient game mechanics and artificial intelligence. The course's discussion of graph algorithms, like Dijkstra's algorithm, is particularly relevant for pathfinding in game environments.

See salaries and explore the career path for Game Developer

Data Scientist

Data scientists analyze large datasets to extract meaningful insights and inform business decisions. This requires a strong understanding of data structures and algorithms for efficient data manipulation and analysis. This Data Structures and Algorithms course may be useful because it helps data scientists choose the most appropriate data structures and algorithms for their specific tasks. The course's exploration of searching and sorting algorithms, as well as graph algorithms like DFS and BFS, provides the skills necessary to analyze complex relationships within data. Moreover, exposure to algorithmic design ensures efficient data processing and modeling.

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DevOps Engineer

DevOps engineers are responsible for automating and streamlining the software development and deployment process. This Data Structures and Algorithms course may be useful as it provides a grounding for understanding the performance implications of different data structures and algorithms when automating infrastructure and managing deployments. The course's coverage of fundamental data structures helps DevOps engineers understand how data is stored and manipulated within various systems. Also, the exploration of algorithmic design principles enables them to optimize automation scripts and deployment processes. The course's discussion of graph algorithms could be relevant for understanding network topologies and dependencies.

See salaries and explore the career path for DevOps Engineer

Data Engineer

Data engineers are responsible for building and maintaining the infrastructure for data storage and processing. This Data Structures and Algorithms course may be useful, as it provides a strong foundation for designing efficient data pipelines. The course's coverage of various data structures, including arrays, linked lists, stacks, queues, hash tables, trees, and graphs, helps data engineers choose the right structure for specific data storage needs. Furthermore, the exploration of algorithmic design principles empowers them to optimize data processing workflows. The course's discussion of sorting and searching algorithms equips data engineers to efficiently manage and retrieve data from diverse sources.

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Frontend Developer

Frontend developers create the user interface and user experience of web applications. While often associated with visual design, a solid understanding of data structures and algorithms can significantly enhance a frontend developer's ability to optimize application performance and handle complex data interactions. This Data Structures and Algorithms course may be useful because it helps frontend developers implement efficient data handling techniques. The course's exploration of data structures, like arrays and linked lists, provides them with the tools to manage and manipulate data displayed on the user interface. The understanding of different sorting algorithms helps in rendering sorted lists efficiently.

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Database Administrator

Database administrators are responsible for managing and maintaining databases. This Data Structures and Algorithms course may be useful, because it provides a foundation for understanding the underlying principles of database design and optimization. The course's coverage of data structures, such as trees and hash tables, helps database administrators grasp how data is organized and indexed within a database. Also, the exploration of sorting and searching algorithms enables them to optimize query performance. The course's coverage of hashing is also relevant to managing database indexes and ensuring data integrity.

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Security Engineer

Security engineers protect computer systems and networks from cyber threats. This Data Structures and Algorithms course may be useful because it provides a foundation for understanding common security vulnerabilities and developing effective mitigation strategies. The course's coverage of data structures, such as hash tables and trees, helps security engineers analyze data storage and retrieval mechanisms for potential vulnerabilities. The emphasis on algorithmic design principles may lead to a better understanding of encryption algorithms and security protocols. Furthermore, the course's discussion of graph algorithms could be relevant for analyzing network traffic patterns and detecting malicious activity.

See salaries and explore the career path for Security Engineer

Data Structures and Algorithms-Deep Dive into Core Concepts

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