What is the best material for understanding algorithmic analysis by a newbie?

For a newbie looking to understand algorithmic analysis, here are some highly recommended resources that cater to different learning styles and preferences:

Books

"Introduction to Algorithms" by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein

This book is a comprehensive resource that covers algorithms extensively, including theory and practice. It assumes a reasonable familiarity with math and data structures but is highly detailed and practical1.

"Algorithms Unlocked" by Thomas H. Cormen

This book explains how algorithms work in everyday technology and covers basic tasks like searching, sorting, and graphing. It's more accessible and less dense than "Introduction to Algorithms," making it a good starting point1.

"Grokking Algorithms: An illustrated guide for programmers and other curious people" by Aditya Bhargava

This book is designed for visual learners and covers common algorithms like sorting and searching. It includes step-by-step walkthroughs and code samples in Python, making it easier for beginners to follow1.

Online Courses and Resources

Khan Academy - Algorithms Course

Developed in partnership with Dartmouth College professors, this course provides a comprehensive introduction to algorithms, covering topics like searching, sorting, recursion, and graph theory. It uses articles, visualizations, quizzes, and coding challenges to make learning interactive25.

GeeksforGeeks - Learn Data Structures and Algorithms Course

This course breaks down the learning process into key steps, including understanding time and space complexities, basics of data structures, and fundamentals of algorithms. It offers a modular and sequential learning experience2.

freeCodeCamp - Algorithms and Data Structures Course

This 6-hour course on YouTube covers the concept and applications of algorithms, data structures like arrays and linked lists, and sorting algorithms like Merge Sort. It provides a solid introduction to algorithms and data structures2.

Articles and Guides

"The Ultimate Beginners Guide To Analysis of Algorithm" on Codeburst

This article is targeted at programmers without a theoretical computer science background. It explains key concepts like algorithm complexity analysis, Big Θ, asymptotic behavior, and worst-case analysis without requiring mathematical prerequisites4.

"A Beginner’s Guide to Algorithmic Thinking" on Learn to Code With Me

This guide focuses on developing an understanding of algorithmic thinking, including breaking down problems, building solutions, and introducing optimization and Big O notation. It emphasizes fostering a mindset for understanding and applying algorithmic logic2.

These resources collectively provide a well-rounded approach to learning algorithmic analysis, from foundational concepts to practical applications, and cater to various learning styles.