Data Structures and Algorithms with Python: With an Introduction to Multiprocessing (Undergraduate Topics in Computer Science)
This clear and concise textbook is invaluable for undergraduate courses on data structures and algorithms, catering to both beginners and advanced learners.
Data Structures and Algorithms with Python: With an Introduction to Multiprocessing (Undergraduate Topics in Computer Science)
Stavka #: 88644480

Data Structures and Algorithms with Python: With an Introduction to Multiprocessing (Undergraduate Topics in Computer Science)

Stavka #: 88644480

€ 72

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This clear and concise textbook is invaluable for undergraduate courses on data structures and algorithms, catering to both beginners and advanced learners.
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What Stands Out

Comprehensive Coverage
This second edition offers a thorough exploration of data structures and algorithms, providing students with essential concepts and practical applications tailored for undergraduate computer science curricula.
Multiprocessing Insights
Incorporating multiprocessing topics prepares students for modern programming challenges, enhancing their understanding of concurrency and parallelism in Python, setting them apart in the job market.
Practical Examples
Real-world examples and exercises reinforce learning, helping students effectively apply theoretical concepts in practice, ensuring deeper understanding and retention of critical computer science principles.

Detalji o proizvodu

Shop Data Structures and Algorithms with Python: With an Introduction to Multiprocessing (Undergraduate Topics in Computer Science) online at a best price in Croatia. 3031422082
  • This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms―supported by motivating examples―that bring meaning to the problems faced by computer programmers. The idea of computational complexity is introduced, demonstrating what can and cannot be computed efficiently at scale, helping programmers make informed judgements about the algorithms they use. The easy-to-read text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python.Topics and features:Includes introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective coursesProvides learning goals, review questions, and programming exercises in each chapter, as well as numerous examplesPresents a primer on Python for those coming from a different language backgroundAdds a new chapter on multiprocessing with Python using the DragonHPC multinode implementation of multiprocessing (includes a tutorial)Reviews the use of hashing in sets and maps, and examines binary search trees, tree traversals, and select graph algorithmsOffers downloadable programs and supplementary files at an associated website to help studentsStudents of computer science will find this clear and concise textbook invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer books, Python Programming Fundamentals, and Foundations of Programming Languages.Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.
Publisher Springer
Publication date January 25, 2024
Edition Second Edition 2024
Language English
Print length 414 pages
ISBN-10 3031422082
ISBN-13 978-3031422089
Item Weight 1.72 pounds (780 grams)
Dimensions 5.75 x 1 x 9 inches (14.6 x 2.5 x 22.9 cm)
Part of series Undergraduate Topics in Computer Science

Who Should Buy?

Suitable For
  • Undergraduate Students

    Ideal for those studying computer science, offering foundational knowledge in data structures and algorithms using Python.

  • Aspiring Programmers

    Great for beginner programmers who want to enhance their coding skills and understand algorithms deeply.

  • Educators and Instructors

    Useful for teaching materials, providing structured content to facilitate learning data structures and algorithms.

Not Suitable For
  • Advanced Professionals

    May not satisfy experienced developers seeking complex algorithms or advanced data structures beyond undergraduate level.

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Pros

  • Clear and concise explanations
  • Comprehensive coverage of topics
  • Hands-on coding examples
  • Accessible for beginners
  • Integrates multiprocessing concepts

Protiv

  • Some may prefer more advanced examples.

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