Feel confident navigating the fundamentals of data science
Data Science Essentials For Dummies is a quick reference on the core concepts of the exploding and in-demand data science field, which involves data collection and working on dataset cleaning, processing, and visualization. This direct and accessible resource helps you brush up on key topics and is right to the point―eliminating review material, wordy explanations, and fluff―so you get what you need, fast. "Data Science Essentials For Dummies" is part of the popular For Dummies series, which aims to make complex topics accessible and understandable for a broad audience. This book serves as an excellent introduction to data science, designed for beginners and those who want to grasp the foundational concepts without being overwhelmed by technical jargon.
Strengthen your understanding of data science basics
Review what you've already learned or pick up key skills
Effectively work with data and provide accessible materials to others
Jog your memory on the essentials as you work and get clear answers to your questions
Perfect for supplementing classroom learning, reviewing for a certification, or staying knowledgeable on the job, Data Science Essentials For Dummies is a reliable reference that's great to keep on hand as an everyday desk reference.
"Data Science Essentials For Dummies" is part of the popular For Dummies series, which aims to make complex topics accessible and understandable for a broad audience. This book serves as an excellent introduction to data science, designed for beginners and those who want to grasp the foundational concepts without being overwhelmed by technical jargon.
Key Features
Beginner-Friendly Approach:
Explains data science concepts in a clear and straightforward manner.
Breaks down complex ideas into digestible parts, making it ideal for readers with little to no prior experience.
Comprehensive Coverage:
Covers the entire data science lifecycle, including data collection, analysis, and visualization.
Introduces machine learning and predictive modeling in an accessible way.
Practical Examples:
Includes real-world examples to demonstrate how data science is applied in various fields.
Offers hands-on exercises to reinforce learning.
Focus on Tools and Techniques:
Explains the use of common data science tools such as Python, R, and Excel.
Discusses data visualization techniques using platforms like Tableau and Power BI.
Who Should Read This Book?
Beginners: Those new to data science who want a gentle introduction to the field.
Business Professionals: Individuals looking to use data science to inform business decisions.
Students: Learners seeking to explore data science as a potential career path.
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