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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

物品 #: 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

物品 #: 37905986

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Do you want to master the era of data economy? Do you want to learn the top programming languages for data science? If yes, then keep reading!One of the core elements of economic growth in the twenty-first century is the data economy.We are all required to educate ourselves about a paradigm that represents only the very beginning of a genuine industrial revolution, this time driven by data. Data we generate, store, share, analyze, data that describes us, pinpoints where we are, reveals our tastes and preferences, our opinions and also those of our network of family and friends.Data has become a crucial input for any economic process.There is more data being produced daily these days than there was ever produced in even the past centuries! In such a scenario, Data Science is obviously a very popular field as it is important to analyze and process this data to obtain useful insights. According to an IBM report published on Forbes, data science has been ranked the best job in tech for the last 3 years.But in order to be able to assess and analyze the data gathered, you need the best data science tools and skills.In this beginners and practical guide, you are going to learn the best programming language for data science in 2020, the mostly used by other data scientists and that employers are constantly looking.This is a complete guide, with 4 Books in 1:Python crash coursePython for data analysisJava programming for beginnersSQL for beginnersPython is one of the best programming languages for data science because of its capacity for statistical analysis, data modeling, and easy readability. Another reason for this huge success of Python in Data Science is its extensive library support for data science and analytics. There are many Python libraries that contain a host of functions, tools, and methods to manage and analyze data. Each of these libraries has a particular focus with some libraries managing image and textual data, data mining, neural networks, data visualization, and so on. Java is one of the oldest languages used for enterprise development. Most of the popular Big Data frameworks/tools on the likes of Spark, Flink, Hive, Spark and Hadoop are written in Java. It has a great number of libraries and tools for Machine Learning and Data Science. Some of them being to solve most of your ML or data science problems. SQL is a language specifically created for managing and retrieving the data stored in a relational database management system. This language is extremely important for data science as it deals primarily with data. The main role of data scientists is to convert the data into actionable insights and so they need SQL to retrieve the data to and from the database when required. There are many popular SQL databases that data scientists can use such as SQLite, MySQL, Oracle and Microsoft SQL Server. BigQuery, in particular, is a data warehouse that can manage data analysis over petabytes of data and enable super fats SQL queries.Each of these languages come with their benefits, often offering better and faster results when compared with others. The domain of Data Science is exceedingly vast and can often demand a different set of tools for various tasks.Equipping yourself with more than one programming language can guarantee to help you overcome unique challenges while dealing with the data. If you are a budding Data Scientist, you should start with the programming languages mentioned above as they are the most in-demand languages right now.Ready to get started? Click the BUY NOW button!

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)

產品敘述

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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題: 如何從 Ubuy 在線購物 Programming for Data Science: 4 Books in 1. The？

回答: 從 Ubuy 在線購物 Programming for Data Science: 4 Books in 1. The 非常簡單。. 您只需搜索產品，在結賬時選擇運輸方式，然後將其運送到您所在的位置。
題: Programming for Data Science: 4 Books in 1. The 可以在 Hong Kong 在線購物嗎？

回答: 是的，您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. Programming for Data Science: 4 Books in 1. The 在本地不可用，但您可以信任我們的快遞服務。
題: 下訂單後需要多長時間才能收到產品？

回答: 您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間，所以購物時請放心。

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.

Customer Reviews & Ratings

3.9

26 客戶評分

5 星

50%
4 星

24%
3 星

5%
2 星

8%
1 星

13%

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優點

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

缺點

Writing can feel disjointed

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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