Datastructures and algorithms in C++

target audience - noobs

This course is for total noobs with no programming experience.

prerequisites

• No prior programming knowledge required
• Basic understanding of computer concepts is helpful but not necessary
• Willingness to learn and experiment with code
• A computer with C++ compiler installed (such as GCC or Microsoft Visual Studio)

learning objectives

• Understand fundamental programming concepts using C++
• Learn basic data structures such as arrays, linked lists, and trees
• Implement algorithms for sorting and searching data efficiently
• Gain hands-on experience writing and debugging C++ code
• Explore the relationship between data structures and algorithms
• Develop problem-solving skills through coding exercises
• Cultivate a hacker mindset focused on experimentation and learning

course outline

chapter 1 - introduction to programming with C++

• objectives
  • Understand what programming is and why it's important
  • Get familiar with C++ as a programming language
• outline
  • Overview of programming concepts
  • Installing a C++ compiler (GCC or Visual Studio)
  • Writing your first C++ program: "Hello, World!"
  • Basic syntax and structure of C++ programs
  • Understanding compilation and execution process

chapter 2 - fundamental programming concepts

• objectives
  • Learn about variables, data types, and scope
  • Grasp control structures like conditionals and loops
• outline
  • Variables, constants, and data types in C++
  • Input and output operations
  • Control flow: if statements, switch statements
  • Loops: for, while, and do-while loops
  • Basic error handling and debugging techniques

chapter 3 - functions and modular programming

• objectives
  • Understand the purpose of functions in programming
  • Learn how to define and call functions in C++
• outline
  • What is a function?
  • Defining and calling functions
  • Function parameters and return types
  • Scope and lifetime of variables
  • Introduction to recursive functions

chapter 4 - data structures: arrays and strings

• objectives
  • Learn how to use arrays and strings to store data
  • Understand the properties and limitations of these data structures
• outline
  • Introduction to arrays: definition, declaration, and initialization
  • Accessing and modifying array elements
  • Multi-dimensional arrays
  • Working with strings in C++: string class and operations
  • Common operations on arrays and strings (sorting, searching)

chapter 5 - linked lists

• objectives
  • Understand the concept of linked lists and their advantages over arrays
  • Learn how to implement a simple linked list in C++
• outline
  • Introduction to linked lists: nodes and pointers
  • Creating a linked list: insertion, deletion, and traversal
  • Types of linked lists: singly and doubly linked lists
  • Comparing linked lists with arrays

chapter 6 - stacks and queues

• objectives
  • Learn about stack and queue data structures
  • Understand their use cases and implementations in C++
• outline
  • Introduction to stacks: definition and operations
  • Implementing a stack using arrays and linked lists
  • Introduction to queues: definition and operations
  • Implementing a queue using arrays and linked lists
  • Real-world applications of stacks and queues

chapter 7 - binary trees and tree traversal

• objectives
  • Understand the structure of binary trees
  • Learn various methods for traversing trees
• outline
  • Introduction to binary trees: nodes and child relationships
  • Creating and manipulating binary trees: insertion and deletion
  • Tree traversal methods: in-order, pre-order, post-order
  • Applications of binary trees in problem-solving

chapter 8 - sorting algorithms

• objectives
  • Learn fundamental sorting algorithms and their efficiency
  • Implement sorting algorithms in C++
• outline
  • Introduction to sorting concepts and the importance of efficiency
  • Bubble sort, selection sort, and insertion sort
  • Quick sort and merge sort
  • Analyzing algorithm complexity: big O notation
  • Implementing sorting algorithms with examples

chapter 9 - searching algorithms

• objectives
  • Understand searching algorithms and when to use them
  • Gain hands-on experience implementing search algorithms
• outline
  • Introduction to searching concepts
  • Linear search and its implementation
  • Binary search: requirements and implementation
  • Search complexity analysis
  • Advanced searching techniques and applications

chapter 10 - introduction to algorithms

• objectives
  • Understand what algorithms are and their significance
  • Explore the relationship between data structures and algorithms
• outline
  • Defining algorithms: what they are and why they matter
  • Characteristics of good algorithms: efficiency and correctness
  • Relationship between data structures and algorithms
  • Common algorithmic problems and strategies

chapter 11 - problem-solving techniques

• objectives
  • Develop algorithmic thinking and problem-solving skills
  • Practice coding exercises to enhance understanding
• outline
  • Introduction to problem-solving approaches
  • Breaking down problems into manageable steps
  • Common coding challenges and practice exercises
  • Reviewing solutions and optimizing code

chapter 12 - final project and course wrap-up

• objectives
  • Apply everything learned in a comprehensive project
  • Reflect on knowledge gained and future learning paths
• outline
  • Overview of a final project: designing and implementing a small application
  • Steps to project planning and execution
  • Presenting project results and receiving feedback
  • Recap of key concepts learned in the course
  • Guidance on next steps and further resources for continued learning