CompTIA DataX Study Guide: Exam DY0-001 (Sybex Study Guide)
Author: Fred Nwanganga (Author)
Publisher finelybook 出版社: Sybex
Edition 版次: 1st
Publication Date 出版日期: 2024-08-13
Language 语言: English
Print Length 页数: 416 pages
ISBN-10: 1394238983
ISBN-13: 9781394238989
Book Description
Demonstrate your Data Science skills by earning the brand-new CompTIA DataX credential
In CompTIA DataX Study Guide: Exam DY0-001, data scientist and analytics professor, Fred Nwanganga, delivers a practical, hands-on guide to establishing your credentials as a data science practitioner and succeeding on the CompTIA DataX certification exam. In this book, you’ll explore all the domains covered by the new credential, which include key concepts in mathematics and statistics; techniques for modeling, analysis and evaluating outcomes; foundations of machine learning; data science operations and processes; and specialized applications of data science.
This up-to-date Study Guide walks you through the new, advanced-level data science certification offered by CompTIA and includes hundreds of practice questions and electronic flashcards that help you to retain and remember the knowledge you need to succeed on the exam and at your next (or current) professional data science role. You’ll find:
- Chapter review questions that validate and measure your readiness for the challenging certification exam
- Complimentary access to the intuitive Sybex online learning environment, complete with practice questions and a glossary of frequently used industry terminology
- Material you need to learn and shore up job-critical skills, like data processing and cleaning, machine learning model-selection, and foundational math and modeling concepts
Perfect for aspiring and current data science professionals, CompTIA DataX Study Guide is a must-have resource for anyone preparing for the DataX certification exam (DY0-001) and seeking a better, more reliable, and faster way to succeed on the test.
From the Back Cover
Prove your skills as a Data Scientist with the CompTIA® DataX Study Guide
The CompTIA®DataX Study Guide is your one-stop resource for complete coverage of the DY0-001 exam. This Sybex Study Guide covers all the DY0-001 objectives. Prepare for the exam smarter and faster with Sybex thanks to efficient and accurate content, including assessment test that validate and measure exam readiness, real-world examples and scenarios, practical exercises, and challenging chapter review questions. Reinforce and remember what you’ve learned with the intuitive Sybex online learning environment and test bank, accessible across multiple devices. Prepare like a pro for the CompTIA DataX exam with Sybex.
Coverage of 100% of all exam objectives in this Study Guide means you’ll be ready:
- To understand data science operations and processes
- To implement key data science best practices
- To apply mathematical and statistical models appropriately
- To decide how to clean and process data effectively and efficiently
- To apply concepts from statistical modeling, linear algebra, and calculus
- To apply machine-learning models and understand deep learning concepts
- To make justified model recommendations
ABOUT THE COMPTIA DATAX CERTIFICATION
CompTIA DataX certification validates your understanding of data and your ability to leverage data and artificial intelligence to make predictions and communicate those predictions to stakeholders.
Interactive learning environment
Take your exam prep to the next level with Sybex’s superior interactive online study tools. To access our learning environment, simply visit http://www.wiley.com/ go/sybextestprep, register your book to receive your unique PIN, and instantly gain one year of FREE access after activation to:
• Interactive test bank with 2 practice exams to help you identify areas where further review is needed. Get more than 90% of the answers correct, and you’re ready to take the certification exam.
• Over 100 electronic flashcards to reinforce learning and last-minute prep before the exam
About the Author
ABOUT THE AUTHOR
FRED NWANGANGA is a technology professional and professor in the IT, Analytics, and Operations Department within the University of Notre Dame – Mendoza College of Business. He teaches undergraduate and graduate courses in Python for Data Analytics, Machine Learning, and Unstructured Data Analytics. He has over 20 years of experience in technology management and analytics. He is the author of several LinkedIn Learning machine learning courses and the founder of the Early Bridges to Data Science Program in the Notre Dame Lucy Family Institute for Data & Society.
