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32487227
Essential Computational Thinking: Computer Science from Scratch
85% of respondents would recommend this to a friend
Item #:
32487227
ALL 13749
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Essential Computational Thinking: Computer Science from Scratch helps students build a theoretical and practical foundation for learning computer science.
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Product Details
| Publisher | Cognella Academic Publishing |
| Publication date | June 17, 2020 |
| Language | English |
| Print length | 328 pages |
| ISBN-10 | 1516583213 |
| ISBN-13 | 978-1516583218 |
| Item Weight | 1.68 pounds (760 grams) |
| Dimensions | 8.5 x 0.69 x 11 inches (21.6 x 1.8 x 27.9 cm) |
Product Description
Essential Computational Thinking: Computer Science from Scratch
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Computers & Technology Editorial Review
Essential Computational Thinking: Computer Science from Scratch offers a comprehensive introduction to computer science principles. Published by Cognella Academic Publishing on June 17, 2020, this resource spans 328 pages and is designed in an accessible format for learners of all levels. The book emphasizes foundational concepts that foster critical thinking and problem-solving skills, making it ideal for students new to the subject. Its clear layout and engaging content support effective learning strategies, while the ISBN numbers establish it as a credible academic text. Readers appreciate its structured approach to complex topics, ensuring a solid grasp of computational thought processes.
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Pros
- Engaging and easy-to-follow content
- Strong foundation in computer science concepts
- Well-structured for beginners
- Supports critical thinking development
- Approachable for non-technical readers
Cons
- Some advanced topics may be glossed over
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Features & Benefits
- Builds a solid foundation in theoretical and practical computer science.
- Covers essential computational theories and programming ideas.
- Explores the mathematical and physical foundations of computing.
- Equips students to write substantial programs from the start.
- Covers advanced topics including object-oriented programming and machine learning.
- Ideal for technical CS0 courses and motivated non-CS majors.
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