Pierson L. Data Science for Dummies

2nd Edition. — John Wiley & Sons, Inc., Hoboken, New Jersey, Canada, 2017. — 329 p. — ISBN: 978-1-119-32763-9Your ticket to breaking into the field of data science!
Jobs in data science are projected to outpace the number of people with data science skills — making those with the knowledge to fill a data science position a hot commodity in the coming years. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of an organization's massive data sets and applying their findings to real-world business scenarios.
From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization.
Provides a background in data science fundamentals and preparing your data for analysis
Details different data visualization techniques that can be used to showcase and summarize your data
Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques
Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark
It's a big, big data world out there — let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.Getting Started with Data Science
Wrapping Your Head around Data Science
Exploring Data Engineering Pipelines and Infrastructure
Applying Data-Driven Insights to Business and Industry
Using Data Science to Extract Meaning from Your Data
Machine Learning: Learning from Data with Your
Math, Probability, and Statistical Modeling
Using Clustering to Subdivide Data
Modeling with Instances
Building Models That Operate Internet-of-Things Devices
Creating Data Visualizations That Clearly Communicate Meaning
Following the Principles of Data Visualization Design
Using D3.js for Data Visualization
Web-Based Applications for Visualization Design
Exploring Best Practices in Dashboard Design
Making Maps from Spatial Data
Computing for Data Science
Using Python for Data Science
Using Open-source R for Data Science
Using SQL in Data Science
Doing Data Science with Excel and Knime
Applying Domain Expertise to Solve Real-World Problems Using Data Science
Data Science in Journalism: Nailing Down the Five Ws (and an H)
Delving into Environmental Data Science
Data Science for Driving Growth in E-Commerce
Using Data Science to Describe and Predict Criminal Activity
The Part of Tens
Ten Phenomenal Resources for Open Data
Ten Free Data Science Tools and Applications