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Item #:
37905986
Programming for Data Science: 4 Books in 1. The Complete Beginners Guide you Cant Miss to Master the Era of the Data Economy, using Python, Java, SQL
83% of respondents would recommend this to a friend
Item #:
37905986
HKD 402
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What Stands Out
Comprehensive Content
Offers an extensive overview of four essential programming languages—Python, Java, SQL—specifically tailored for data science, ensuring readers gain a broad understanding and skill set.
Beginners Friendly
Designed for absolute beginners, this guide simplifies complex concepts, making data science accessible and engaging for anyone looking to start a career in the evolving data economy.
Practical Applications
Includes practical examples and exercises that encourage hands-on learning, allowing readers to apply their knowledge immediately and build confidence in real-world coding scenarios.
Product Details
| Publisher | Independently published |
| Publication date | October 28, 2020 |
| Language | English |
| Print length | 610 pages |
| ISBN-13 | 979-8554981258 |
| Item Weight | 1.78 pounds (810 grams) |
| Dimensions | 6 x 1.38 x 9 inches (15.2 x 3.5 x 22.9 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners aiming to start a career in data science and learn essential programming languages.
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Self-Learners
Great for individuals who prefer self-paced learning through comprehensive guides bundled into one resource.
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Career Switchers
Helpful for professionals transitioning into data-driven fields seeking foundational knowledge in programming and data analysis.
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Advanced Programmers
Not suitable for those with existing programming expertise, as it targets complete beginners in data science.
Product Description
Programming for Data Science: 4 Books in 1. The Complete Beginners Guide you Cant Miss to Master the Era of the Data Economy, using Python, Java, SQL Coding
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Beginner's Guides Editorial Review
"Programming for Data Science: 4 Books in 1" is a comprehensive guidebook for anyone interested in pursuing a career in data programming. The author provides a thorough overview of the subject, starting with an introduction to data programming as a career and its future. Then the author goes on to cover the different programming languages such as Python, Java, and SQL, with each language having its own chapter. The chapters are set up similarly, introducing the basics of the language, what they are best suited for, and providing sample exercises to work with the language. Though the book does contain a lot of information, it may feel overwhelming to some. However, if one takes time to go through it, the information is comprehensive and easy to follow. It is a great companion book for self-teaching and efficient in building skills in programming for data science.
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Pros
- Thorough overview of data programming as a career
- Comprehensive guide covering multiple programming languages
- Sample exercises for each language to practice
- Great companion book for self-teaching
- Information is comprehensive and easy to follow
Cons
- Writing can feel disjointed
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