Data Structure And Algorithm Training in Virtual

Data Structure and Algorithm Training Course Outline

Module 1: Why Data Structures Matter

• Data Structures in Real Software
• Algorithms and Data Structures: The Relationship
• Choosing the Right Structure for the Problem
• Lab: Explore a Python/JS Programme and Identify Structures

Module 2: Big-O Complexity Analysis

• Time Complexity: Growth Rates and Big-O Notation
• Common Complexity Classes: O(1) to O(n²)
• Space Complexity and Memory Trade-offs
• Best, Worst, and Average Case Analysis
• Exercise: Classify Code Snippets by Big-O

Module 3: Arrays and Linked Lists

• Array Structure, Indexing, and Memory Layout
• Array Operations and Complexity Analysis
• Linked List Structure: Nodes and Pointers
• Singly vs Doubly Linked Lists
• Core Linked List Operations: Insert, Delete, Traverse
• Arrays vs Linked Lists: Trade-offs
• Lab: Implement a Linked List with Insert and Delete

Module 4: Stacks and Queues

• Stack Structure, LIFO Behaviour, and Use Cases
• Queue Structure, FIFO Behaviour, and Variants
• Complexity Analysis for Stacks and Queues
• Lab: Build a Stack and Queue from Scratch

Module 5: Searching and Sorting Algorithms

• Linear Search vs Binary Search: When to Use Each
• Binary Search Prerequisites and Implementation
• Bubble Sort and Insertion Sort: Mechanics and Complexity
• Merge Sort: Divide-and-Conquer Strategy
• Quick Sort: Partitioning and Pivot Selection
• Comparing Sorting Algorithms: Stability and Performance
• Lab: Implement Binary Search and Compare Sorting Runs

Module 6: Recursion and Divide-and-Conquer

• What Is Recursion: Base Case and Recursive Case
• The Call Stack and Recursion Depth
• Recursion vs Iteration: Trade-offs
• Divide-and-Conquer Strategy Explained
• Exercise: Trace Merge Sort and Quick Sort Recursively

Module 7: Hashing and Trees

• Hash Functions and Hash Table Structure
• Collision Handling: Chaining and Open Addressing
• Hash Table Complexity and Real-World Applications
• Tree Terminology: Nodes, Edges, Height, and Depth
• Binary Search Tree: Structure and Operations
• BST Complexity and When to Use Trees
• Lab: Use a Hash Map to Solve a Lookup Problem

Module 8: Capstone and Consolidation

• Mini Case: Multi-Concept Algorithm Challenge
• Choosing Data Structures and Algorithms Reviewed
• Complexity Cheat Sheet and Problem-Solving Best Practices

Who Should Attend the Data Structure and Algorithm Training?

The Data Structures and Algorithms Course is designed to equip individuals with comprehensive learning on the fundamental concepts of Data Structures and Algorithms. This course will benefit the following professionals:

• Software Developers
• Programmers
• Application Developers
• Systems Analysts
• IT Professionals
• Database Administrators
• Algorithm Specialists
• Solutions Architects

Prerequisites for the Data Structure and Algorithm Training

There are no formal prerequisites to attend the Data Structures and Algorithm Course. However, some familiarity with programming concepts would be beneficial.

Data Structure and Algorithm Training Course Overview

Data Structures and Algorithms are central to computer science and software development. They enable efficient organisation, storage, and retrieval of data, which is essential for solving complex computational problems.

This course helps improve coding efficiency, problem-solving skills, and interview readiness. It offers practical knowledge that supports career growth in software development and technical roles.

The Knowledge Academy’s 1-day Data Structures and Algorithms Course in Virtual provide hands-on learning. Delegates gain a solid understanding of key concepts through expert guidance and real-world exercises.

Data Structure and Algorithm Course Objectives

• To understand the fundamental concepts of Data Structures and Algorithms
• To learn how to implement various Data Structures such as arrays, linked lists, and trees
• To gain knowledge of sorting and searching algorithms
• To develop problem-solving skills using algorithms
• To explore advanced topics like graph algorithms and dynamic programming
• To apply data structures and algorithms to optimise code performance

Upon completion of this Data Structures and Algorithms Course, delegates will possess a solid foundation in Data Structures and Algorithms, enabling them to write more efficient and effective code. This training will empower them to solve complex problems and enhance their career prospects in the technology sector.

What’s Included in the Data Structure and Algorithm Training?

• World-Class Training Sessions from Experienced Instructors
• Data Structure and Algorithm Certificate
• Digital Delegate Pack