
Algorithmic Thinking, 2nd Edition
Learn Algorithms to Level Up Your Coding Skills
Daniel Zingaro(Author)
No Starch Press
Published on 23. January 2024
480 pages
978-1-7185-0323-6 (ISBN)
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Description
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Get in the game and learn essential computer algorithms by solving competitive programming problems, in the fully revised second edition of the bestselling original. (Still no math required!)
Are you hitting a wall with data structures and algorithms? Whether you're a student prepping for coding interviews or an independent learner, this book is your essential guide to efficient problem-solving in programming.
UNLOCK THE POWER OF DATA STRUCTURES & ALGORITHMS:
Learn the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge.
REAL-WORLD, COMPETITION-PROVEN CODE EXAMPLES:
The programs and challenges in this book aren't just theoretical-they're drawn from real programming competitions. Train with problems that have tested and honed the skills of coders around the world.
GET INTERVIEW-READY:
Prepare yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently.
WRITTEN IN C, USEFUL ACROSS LANGUAGES:
The code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem: We've got recommended reading, too.
Algorithmic Thinking is the complete package, providing the solid foundation you need to elevate your coding skills to the next level.
Are you hitting a wall with data structures and algorithms? Whether you're a student prepping for coding interviews or an independent learner, this book is your essential guide to efficient problem-solving in programming.
UNLOCK THE POWER OF DATA STRUCTURES & ALGORITHMS:
Learn the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge.
REAL-WORLD, COMPETITION-PROVEN CODE EXAMPLES:
The programs and challenges in this book aren't just theoretical-they're drawn from real programming competitions. Train with problems that have tested and honed the skills of coders around the world.
GET INTERVIEW-READY:
Prepare yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently.
WRITTEN IN C, USEFUL ACROSS LANGUAGES:
The code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem: We've got recommended reading, too.
Algorithmic Thinking is the complete package, providing the solid foundation you need to elevate your coding skills to the next level.
More details
Language
English
Place of publication
New York
United States
Product notice
Reflowable
File size
20,17 MB
ISBN-13
978-1-7185-0323-6 (9781718503236)
Schweitzer Classification
Other editions
Additional editions

Book
01/2024
2nd Edition
No Starch Press
€47.00
Available immediately
Person
Dr. Daniel Zingaro is an award-winning Assistant Professor of Mathematical and Computational Sciences at the University of Toronto Mississauga, where he is well known for his uniquely interactive approach to teaching and internationally recognized for his expertise in Active Learning. He is also the author of Learn to Code by Solving Problems (No Starch Press, 2021).
Content
Introduction
Part I: Sources and Datasets
Chapter 1: Protecting Sources and Yourself
Chapter 2: Acquiring Datasets
Part II: Tools of the Trade
Chapter 3: The Command Line Interface
Chapter 4: Exploring Datasets in the Terminal
Chapter 5: Docker, Aleph, and Making Datasets Searchable
Chapter 6: Reading Other People's Email
Part III: Python Programming
Chapter 7: An Introduction to Python
Chapter 8: Working with Data in Python
Part IV: Structured Data
Chapter 9: BlueLeaks, Black Lives Matter, and the CSV File Format
Chapter 10: BlueLeaks Explorer
Chapter 11: Parler, the January 6 Insurrection, and the JSON File Format
Chapter 12: Epik Fail, Extremism Research, and SQL Databases
Part V: Case Studies
Chapter 13: Pandemic Profiteers and COVID-19 Disinformation
Chapter 14: Neo-Nazis and Their Chat Rooms
Afterword
Appendix A: Solutions to Common WSL Problems
Appendix B: Scraping the Web
Index
Part I: Sources and Datasets
Chapter 1: Protecting Sources and Yourself
Chapter 2: Acquiring Datasets
Part II: Tools of the Trade
Chapter 3: The Command Line Interface
Chapter 4: Exploring Datasets in the Terminal
Chapter 5: Docker, Aleph, and Making Datasets Searchable
Chapter 6: Reading Other People's Email
Part III: Python Programming
Chapter 7: An Introduction to Python
Chapter 8: Working with Data in Python
Part IV: Structured Data
Chapter 9: BlueLeaks, Black Lives Matter, and the CSV File Format
Chapter 10: BlueLeaks Explorer
Chapter 11: Parler, the January 6 Insurrection, and the JSON File Format
Chapter 12: Epik Fail, Extremism Research, and SQL Databases
Part V: Case Studies
Chapter 13: Pandemic Profiteers and COVID-19 Disinformation
Chapter 14: Neo-Nazis and Their Chat Rooms
Afterword
Appendix A: Solutions to Common WSL Problems
Appendix B: Scraping the Web
Index
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