Data Structures And Algorithms

This 100-hour (Lectures + hands-on Lab) Data Structures and Algorithms training is crafted to arm you with the knowledge, skills, and expertise necessary to conceptualize, construct, and implement highly efficient, robust, and scalable algorithms.

Candidates will learn to craft intricate algorithmic solutions using popular programming languages like JavaScript, Python, Java and C++, diving deep into both fundamental and complex data structures and algorithms.

Throughout the course, candidates will navigate through essential topics ranging from basic structures like arrays and lists to advanced concepts involving trees and graphs.

They will also tackle real-world challenges and algorithmic puzzles to reinforce their understanding and gain practical experience.

Additionally, candidates will become adept at analyzing algorithmic complexity and performance, essential skills in optimized problem-solving and software development. This is a lab-intensive, project-based course, and objectives are achieved through hands-on learning.

This 100-hour (Lectures + hands-on Lab) Data Structures and Algorithms course is designed to equip you with the knowledge, skills, and expertise required to, developing, and implementing highly efficient, stable, and scalable algorithms.

Candidates will be educated on formulating sophisticated algorithmic solutions and will traverse through an extensive spectrum of data structures and algorithmic concepts, from rudimentary to advanced levels.

Throughout the program, learners will immerse themselves in vital subjects, transitioning from elementary structures like arrays and queues to more complex themes such as trees and graphs. They will also confront real-world algorithmic problems and data structure challenges to fortify their comprehension and acquire hands-on expertise.

Additionally, candidates will master the art of algorithmic complexity and performance analysis, crucial competencies in the realm of efficient problem-solving and computational programming.

Candidates will undertake myriad coding tasks and projects intended to refine their analytical thinking and solidify the theories expounded in the lectures. This is a lab-intensive, project-based course and objectives are accomplished through hands on learning.

The key to a high success rate is based on the program’s objectives as follows:

• Course contents are based on industry best practices.
• Dedicated Monitoring to evaluate and report candidate’s progress.
• Extensive hands-on lab exercises.
• Industry acclaimed, experienced and certified instructors.

Objectives:

• Grasp the fundamental concepts and structures of efficient algorithm and data structure design.
• Gain a foundational understanding of Data Structures and Algorithms, preparing candidates for real-world challenges in computational problem solving.
• Construct and analyze algorithms for their efficiency and performance.
• Implement various data structures to solve complex computational problems.
• Design and understand the usage of advanced data structures for data handling.
• Develop practical skills through real-world algorithmic and data structuring challenges.
• Learn to implement security and efficiency best practices in algorithm design.
• Understand and apply advanced concepts such as graph theory and dynamic programming.
• Learn to manage and structure data securely and efficiently
• Implement and understand the importance of time and space complexity in algorithms.
• Understand and implement asynchronous processing and multithreading in algorithms.
• Develop problem-solving and debugging skills essential for complex computational tasks.
• Understand the principles of creating and managing scalable and efficient code.
• Explore advanced concepts in data manipulation and resource management for comprehensive algorithm development.
• Leverage modern development tools and practices for efficient project management.
• Develop a solid understanding of different computational architectures and their applications.

Course Topics:

• The Data Structures and Algorithms Course is designed to prepare participants with the crucial skills and knowledge required to excel in crafting efficient solutions within the contemporary computational environment.
• This comprehensive course is segmented into several key modules, each focused on a critical aspect of Data Structures and Algorithms. The following topics are general guidelines to better reflect the contents of the course and for clarity purposes, the guidelines below may change at any time without notice.
• Introduction
• What are Data Structures?
• What are Algorithms?
• Understanding Algorithms and Basic Programming Solutions:
• Get Sum
• Calculator
• Count Occurences
• Find Max Number
• Title Case
• Reverse String
• Palindrome
• Count Vowels
• Remove Duplicates
• FizzBuzz Array
• Array Intersection
• Display Likes
• Find Missing Number
• Find Missing Letter
• Character Uniqueness
• First Non-Repeating Character
• Dice Game Simulation
• Formating Phone Numbers
• Email Validation
• High Order Array Methods:
• Using map, filter, find, reduce, every, some
• Sum of Even Numbers
• Calculate Total Sales
• Highest Scoring Word
• Valid Anagrams
• Hashtag Generator
• Valid IPv4
• Analyze Car Mileage
• Password Validator
• Find Missing Letter
• Time & Space Complexity:
• What is Time Complexity
• Big O Notation
• Constant Time Complexity - O(1)
• Linear Time Complexity - O(n)
• Quadratic Time Complexity O(n^2)
• Logarithmic Time Complexity O(log n)
• Space Complexity
• Max Subarray - Quadratic
• Sliding Window Technique
• Max Subarray - Linear
• Array.reduce Method
• More Array Methods
• Hash Tables, Maps & Sets:
• Introduction to Hash Tables
• Maps
• Word Frequency Counter
• Phone Number Directory
• Anagram Groupings
• Sets
• Symmetric Difference
• Two Sum
• Longest Consecutive
• Custom Hash Table
• Word Instance Counter with Custom Hash Table
• Add getValues() Method
• Anagram Grouping With Custom Hash Table