45 Essential Concepts In Data Science In 7 Minutes Each
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45 Essential Concepts in Data Science in 7 Minutes Each
### Book Description: '45 Essential Concepts in Data Science in 7 Minutes Each' Unlock the world of data science with *45 Essential Concepts in Data Science in 7 Minutes Each*, an engaging and insightful guide designed for professionals and enthusiasts alike. This book offers succinct overviews of key topics that shape the data science landscape, allowing readers to grasp fundamental concepts quickly and effectively. #### Why This Book? In today's fast-paced environment, understanding data science is essential, but time is often limited. Each chapter is crafted to be read in just seven minutes, making it the perfect resource for busy individuals seeking to enhance their knowledge without the overwhelm of lengthy texts. From foundational theories to cutting-edge techniques, this book covers a comprehensive range of topics that are pivotal for success in the data-driven world. #### What You'll Learn: - **Introduction to Data Science**: Discover the basics and the significance of data science in various industries. - **Data Types and Data Structures**: Understand how data is categorized and organized. - **Data Collection Methods**: Explore the different ways to gather data effectively. - **Data Cleaning and Preprocessing**: Learn the essential steps to prepare data for analysis. - **Exploratory Data Analysis (EDA)**: Uncover patterns and insights through initial investigations. - **Descriptive Statistics**: Get to know the tools for summarizing and describing data sets. - **Data Visualization Techniques**: Master the art of making data accessible and interpretable through visuals. - **Probability Basics & Statistical Inference**: Dive into the concepts that form the backbone of data analysis. - **Hypothesis Testing & Confidence Intervals**: Develop your skills in making data-driven decisions. - **Regression Analysis, Classification Techniques, and Clustering Methods**: Familiarize yourself with essential modeling techniques. - **Machine Learning Algorithms**: Gain insight into Decision Trees, Support Vector Machines, Neural Networks, and more. - **Natural Language Processing (NLP)**: Explore the intersection of language and data. - **Feature Engineering & Dimensionality Reduction**: Learn to enhance and streamline your datasets. - **Model Evaluation Metrics, Overfitting and Underfitting**: Understand how to measure the success of your models. - **Big Data Technologies & Distributed Computing**: Navigate the complexities of modern data environments. - **Data Ethics and Privacy**: Reflect on the moral responsibilities of data scientists in today's world. - **Deployment of Data Science Models & Data Pipelines**: Understand how to implement models in real-world settings. - **Cloud Computing in Data Science & Working with APIs**: Learn how the cloud empowers data science infrastructure. - **Data Governance & Interpretation**: Explore frameworks for maintaining data integrity and conveying results effectively. - **Industry Applications and Future Trends**: Gain insights into how data science is transforming various sectors. Each chapter concisely introduces you to the topic, breaking down complex concepts into digestible insights. Whether you are a student, a working professional, or just someone curious about the data science field, this book equips you with the essential knowledge to thrive in a data-centric world. ### Get ready to embark on your data journey and transform your understanding of data science in just seven minutes at a time!
Seven Essentials for Business Success
Successful leaders are great teachers, and successful teachers serve as models of leadership. This book enables both leaders and teachers to understand and use the best practices developed by award-winning professors, each of whom teaches one of the seven areas that are essential for business success. These professors candidly discuss their successes and failures in the classroom, the mentors who inspired them, how they developed their teaching methods, and their rigorous preparation for class. Through descriptions of the professors in action, readers will gain an insider’s perspective on their teaching skills, and witness how they teach the seven essentials for success in a variety of settings—MBA, Executive MBA, and executive education courses. The chapters also describe the daily lives (professional and personal) of the professors, and the impact they have beyond the classroom in improving organizations and society. If you are a leader or teacher—or if you are interested in the content of a business school education—this book provides an insider’s perspective on the best practices used by legendary professors when teaching the seven essentials that represent the core body of knowledge for business success.
Leveraging Data Science for Global Health
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.