Exploring Data Science
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Exploring Data Science: Concepts, Techniques and Tools
Author: Dr. A.P. Siva Kumar
language: en
Publisher: IIP Iterative International Publishers
Release Date: 2025-06-24
Welcome to "Data Science with Python"! Whether you're a student, a professional looking to switch careers, or an enthusiast eager to explore the world of data science, this book is designed to take you on an exciting journey through one of the most rapidly growing fields in the world. Data science is the key to unlocking the potential of vast amounts of data in today's digital age. With Python emerging as the leading language for data analysis, machine learning, and visualization, this book leverages Python's rich ecosystem of libraries to provide a hands-on and practical approach to learning data science concepts. Throughout the chapters, you will gain a solid foundation in the essential techniques used in data science, including data manipulation, exploration, statistical analysis, machine learning, and data visualization. You’ll also find real-world examples, case studies, and step-by-step tutorials that will guide you in solving complex problems using Python. The book assumes no prior knowledge of data science or Python, making it suitable for beginners. As you progress, you will gradually move into more advanced topics, empowering you to build your own data-driven solutions with confidence. By the end of this book, you will not only have a deep understanding of the core principles of data science but also be equipped with practical skills to tackle real-world challenges using Python’s powerful data science tools. Whether you're analyzing business data, building machine learning models, or visualizing complex datasets, you'll find the skills you need to succeed. Data science is an ever-evolving field, and as you embark on this journey, remembers that learning is continuous. This book serves as a foundation for that journey, and the possibilities are endless as you dive deeper into data science with Python.
Exploring Data Science with R and the Tidyverse
This book introduces the reader to data science using R and the tidyverse. No prerequisite knowledge is needed in college-level programming or mathematics (e.g., calculus or statistics). The book is self-contained so readers can immediately begin building data science workflows without needing to reference extensive amounts of external resources for onboarding. The contents are targeted for undergraduate students but are equally applicable to students at the graduate level and beyond. The book develops concepts using many real-world examples to motivate the reader. Upon completion of the text, the reader will be able to: Gain proficiency in R programming Load and manipulate data frames, and "tidy" them using tidyverse tools Conduct statistical analyses and draw meaningful inferences from them Perform modeling from numerical and textual data Generate data visualizations (numerical and spatial) using ggplot2 and understand what is being represented An accompanying R package "edsdata" contains synthetic and real datasets used by the textbook and is meant to be used for further practice. An exercise set is made available and designed for compatibility with automated grading tools for instructor use.
Advanced Data Analytics with AWS: Explore Data Analysis Concepts in the Cloud to Gain Meaningful Insights and Build Robust Data Engineering Workflows Across Diverse Data Sources
Author: Joseph Conley
language: en
Publisher: Orange Education Pvt Limited
Release Date: 2024-04-17
Master the Fundamentals of Data Analytics at Scale Key Features ● Comprehensive guide to constructing data engineering workflows spanning diverse data sources ● Expert techniques for transforming and visualizing data to extract actionable insights ● Advanced methodologies for analyzing data and employing machine learning to uncover intricate patterns Book Description Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook. Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets. The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons. The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence. What you will learn ● Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats. ● Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis. ● Perform ad-hoc queries for preliminary data exploration, uncovering initial insights. ● Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights. ● Develop advanced machine learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights. Table of Contents 1. Introduction to Data Analytics and AWS 2. Getting Started with AWS 3. Collecting Data with AWS 4. Processing Data on AWS 5. Descriptive Analytics on AWS 6. Advanced Data Analysis on AWS 7. Additional Use Cases for Data Analysis 8. Data Visualization and Interaction on AWS 9. The Future of Data Analytics 10. Conclusion and Next Steps Index