Data Science and Programming Support Services Research Guide

In this book, four leading experts convey the excitement and promise of data science and examine the major challenges in gaining its benefits and mitigating its harms. The authors' far-ranging exploration of these complex issues will stimulate data science practitioners and students, as well as humanists, social scientists, scientists, and policy makers, to study and debate how data science can be used more effectively and more ethically to better our world.

Current or future user-support professionals discover the critical people skills and exceptional technical knowledge to provide outstanding support with Beisse's A GUIDE TO COMPUTER USER SUPPORT FOR HELP DESK AND SUPPORT SPECIALISTS, 6E. This useful guide focuses on the informational resources and technical tools needed most to function effectively in a support position.

Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media--including who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter.

Gain a fundamental understanding of Python's syntax and features with this up-to-date introduction and practical reference. Covering a wide array of Python-related programming topics, including addressing language internals, database integration, network programming, and web services, you'll be guided by sound development principles. Ten accompanying projects will ensure you can get your hands dirty in no time. Updated to reflect the latest in Python programming paradigms and several of the most crucial features found in Python 3, Beginning Python also covers advanced topics such as extending Python and packaging/distributing Python applications. What You'll Learn Become a proficient Python programmer by following along with a friendly, practical guide to the language's key features

This text provides a comprehensive, but concise introduction to software engineering. It adopts a methodical approach to solving software engineering problems proven over several years of teaching, with outstanding results. The book covers concepts, principles, design, construction, implementation, and management issues of software systems.

JavaScript is the native language of the Internet. Originally created to make web pages more dynamic, it is now used for software projects of all kinds, including scientific visualization and data services. However, most data scientists have little or no experience with JavaScript, and most introductions to the language are written for people who want to build shopping carts rather than share maps of coral reefs.

Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

Data science and machine learning can transform any organization and unlock new opportunities. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions.

Practical Data Science for Information Professionals provides an accessible introduction to a potentially complex field, providing readers with an overview of data science and a framework for its application. It provides detailed examples and analysis on real data sets to explore the basics of the subject in three principle areas: clustering and social network analysis; predictions and forecasts; and text analysis and mining.