Data Analysis Fundamentals Certificate

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Data Analysis Fundamentals Certificate

Author : AICPA
Publisher : Wiley
ISBN 13 : 9781119696636
Total Pages : 0 pages
Book Rating : 4.6/5 (966 download)

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Book Synopsis Data Analysis Fundamentals Certificate by : AICPA

Download or read book Data Analysis Fundamentals Certificate written by AICPA and published by Wiley. This book was released on 2020-03-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Data Analysis Fundamentals Certificate (10.0 CPE Credits) provides you with the knowledge on the different job roles involved in the analytics practice and the most commonly encountered technologies in today's data ecosystem. This certificate is Part 1 of the Data Analyst Certificates Bundle - a comprehensive five-part program that provides training and practical guidance on the topic of data analytics. The Data Analysis Fundamentals Certificate begins with a foundational understanding of the need of transformational assets within an organization and explains the importance of intelligent data management and corresponding analytics practice. This certificate program aims to provide you with the knowledge on the different job roles involved in the analytics practice and the most commonly encountered technologies in today's data ecosystem. It will cover concepts behind the most common types of data you will need to be prepared to analyze, as well as help you explore the factors impacting data practice. This certificate program will also explain why intelligent data management and a corresponding analytics practice is critical for the success of both the organization and the professional. WHO WILL BENEFIT Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations' make informed, data-driven business decisions. KEY TOPICS The business impacts and disruptive potential of organizational data Basic concepts behind different types of data and how they're used The job roles and duties associated with data analytics The life cycle of organizational data and how to manage it A vocabulary for evaluating and communicating in data practice Exposure to and demonstrations of tools used for managing and analyzing data Common obstacles and hurdles to effectively leveraging data in an organization How to tie data to business requirements and build business cases LEARNING OBJECTIVES Determine how the digital transformation and disruption landscape create a competitive advantage across the enterprise. Identify the organizational ecosystem needed for becoming a data-driven organization. Analyze the life cycle of data and its implications for data-driven decision making. Compare common problems and risks associated with becoming a data-driven business. Differentiate between data analysis tools. Identify requirements for data-driven projects. Digital Badge: Your Professional Distinction Set yourself apart as a future-ready financial professional. Upon completion, you will be awarded with a certificate in the form of a digital badge. Digital badges allow you to distinguish yourself in the marketplace and show your commitment to quality. The badge can be posted to your social media profiles and linked to your resume or email signature, providing maximum visibility to your achievement. Credit Info CPE CREDITS: Online: 10.0 (CPE credit info) NASBA FIELD OF STUDY: Specialized Knowledge LEVEL: Basic PREREQUISITES: None ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: DALP-S1 Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product for one full year. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact [email protected].

Microsoft Excel 2019 Data Analysis and Business Modeling

Author : Wayne Winston
Publisher : Microsoft Press
ISBN 13 : 1509306080
Total Pages : 1488 pages
Book Rating : 4.5/5 (93 download)

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Book Synopsis Microsoft Excel 2019 Data Analysis and Business Modeling by : Wayne Winston

Download or read book Microsoft Excel 2019 Data Analysis and Business Modeling written by Wayne Winston and published by Microsoft Press. This book was released on 2019-03-28 with total page 1488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master business modeling and analysis techniques with Microsoft Excel 2019 and Office 365 and transform data into bottom-line results. Written by award-winning educator Wayne Winston, this hands-on, scenario-focused guide helps you use Excel to ask the right questions and get accurate, actionable answers. New coverage ranges from Power Query/Get & Transform to Office 365 Geography and Stock data types. Practice with more than 800 problems, many based on actual challenges faced by working analysts. Solve real business problems with Excel—and build your competitive advantage: Quickly transition from Excel basics to sophisticated analytics Use PowerQuery or Get & Transform to connect, combine, and refine data sources Leverage Office 365’s new Geography and Stock data types and six new functions Illuminate insights from geographic and temporal data with 3D Maps Summarize data with pivot tables, descriptive statistics, histograms, and Pareto charts Use Excel trend curves, multiple regression, and exponential smoothing Delve into key financial, statistical, and time functions Master all of Excel’s great charts Quickly create forecasts from historical time-based data Use Solver to optimize product mix, logistics, work schedules, and investments—and even rate sports teams Run Monte Carlo simulations on stock prices and bidding models Learn about basic probability and Bayes’ Theorem Use the Data Model and Power Pivot to effectively build and use relational data sources inside an Excel workbook Automate repetitive analytics tasks by using macros

Application of Data Analysis Essentials Certificate

Author : AICPA
Publisher : Wiley
ISBN 13 : 9781119696612
Total Pages : 0 pages
Book Rating : 4.6/5 (966 download)

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Book Synopsis Application of Data Analysis Essentials Certificate by : AICPA

Download or read book Application of Data Analysis Essentials Certificate written by AICPA and published by Wiley. This book was released on 2020-03-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Data Analysis Essentials Certificate (14.0 CPE Credits) offers hands-on experience regarding how to analyze data and calculate fundamental aspects of your data sets. This certificate program provides the core concepts and definitions of data analytics, which explain the anatomy of data as a medium, and provides fundamental statistical analysis techniques for beginning to glean useful information from data. This certificate is Part 2 of the Data Analyst Certificates Bundle - a comprehensive five-part program that provides training and practical guidance on the topic of data analytics. First, you will learn the different types of variables that make up a data set and perform meaningful calculations on data to discover and explore relationships that yield insights: central tendency, variability, probability, and distribution. Then we will delve into recognizing these qualities in their different forms and how to utilize them in practical business situations. This program offers straightforward exercises to help you practice and immediately apply what you've learned. You will also get exposure to and practice with useful concepts such as quartiles, variance, and standard deviation. Finally, you will be introduced to one of the most powerful tools available for analyzing data: the open-source "R" platform. You will be guided through an actual use case for analyzing data using R and complete your learning by seeing how the statistical concepts you've just learned can be applied in a real-world example. By completing this certificate, you will have a solid grasp of core statistical techniques underpinning an analytics practice and hands-on-practice using them. Note: It is recommended that you complete the Data Analysis Fundamentals Certificate, or ensure you have equivalent knowledge and skills, before starting this certificate course. Learning Labs* This is an interactive learning program that includes bonus hands-on learning labs that will expose you to the tools needed to implement an analytics practice in a practical way and equip you to deploy those tools as needed within your organization. You will practice using various technologies for preparing, analyzing and managing datasets in the real world. *Time spent on learning labs does not award CPE and completing learning labs is not a requirement for earning the certificate. WHO WILL BENEFIT Accounting and finance professionals, especially those interested in learning and applying data analysis techniques to help their organizations make informed, data-driven business decisions. KEY TOPICS The nature and types of different variables in data sets and how to use them Fundamental statistical concepts for working with data Characteristics of data that can be used for conducting analysis Basic calculations for analyzing and discovering useful insights from data sets How to understand and calculate probability from a data set Different types of distribution and how they can be used Guided exposure to the open-source R platform and its analytics capabilities A practical case study exploring how statistical analysis can be used in a common fraud-detection scenario Examples and practice exercises throughout the program to reinforce what you learn LEARNING OBJECTIVES Determine and classify variables. Calculate meaningful statistics, including central tendency, measurement and variability, basic probability, conditional probability, advanced probabilities, discrete distributions, and continuous distributions. Analyze statistics and distributions in R case study. Analyze fraud-detection case study. Digital Badge: Your Professional Distinction Set yourself apart as a future-ready financial professional. Upon completion, you will be awarded with a certificate in the form of a digital badge. Digital badges allow you to distinguish yourself in the marketplace and show your commitment to quality. The badge can be posted to your social media profiles and linked to your resume or email signature, providing maximum visibility to your achievement. Credit Info CPE CREDITS: Online: 14.0 (CPE credit info) NASBA FIELD OF STUDY: Statistics LEVEL: Intermediate PREREQUISITES: Recommended: Complete the Data Analysis Fundamentals Certificate or ensure you have equivalent knowledge and skills. ADVANCE PREPARATION: None DELIVERY METHOD: QAS Self-Study COURSE ACRONYM: DALP-S2 Online Access Instructions A personal pin code is enclosed in the physical packaging that may be activated online upon receipt. Once activated, you will gain immediate online access to the product for one full year. System Requirements AICPA’s online CPE courses will operate in a variety of configurations, but only the configuration described below is supported by AICPA technicians. A stable and continuous internet connection is required. In order to record your completion of the online learning courses, please ensure you are connected to the internet at all times while taking the course. It is your responsibility to validate that CPE certificate(s) are available within your account after successfully completing the course and/or exam. Supported Operating Systems: Macintosh OS X 10.10 to present Windows 7 to present Supported Browsers: Apple Safari Google Chrome Microsoft Internet Explorer Mozilla Firefox Required Browser Plug-ins: Adobe Flash Adobe Acrobat Reader Technical Support: Please contact [email protected].

Data Analysis for Social Science

Author : Elena Llaudet
Publisher : Princeton University Press
ISBN 13 : 0691199434
Total Pages : 256 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Data Analysis for Social Science by : Elena Llaudet

Download or read book Data Analysis for Social Science written by Elena Llaudet and published by Princeton University Press. This book was released on 2022-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Data Analytics Basics

Author : Simplilearn
Publisher : IndraStra Whitepapers
ISBN 13 :
Total Pages : 25 pages
Book Rating : 4.5/5 (778 download)

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Book Synopsis Data Analytics Basics by : Simplilearn

Download or read book Data Analytics Basics written by Simplilearn and published by IndraStra Whitepapers. This book was released on 2020-12-14 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics is increasingly becoming a key element in shaping a company’s business strategy. Today, data influences every decision made by an organization, and this is driving the wide-scale adoption of data analytics, including machine learning technologies and artificial intelligence solutions. The heightened focus is propelling a surge in data analytics spending, reflected in various studies conducted by leading market research firms. The field of data analytics offers some amazing salaries and is not only the hottest IT job, but it is also one of the best-paying jobs in the world. This guide aims at providing the readers with everything they need to know about the data analytics field, basic terminologies, key concepts, real-life use cases, skills you must master in order to scale up your career, and training and certifications you might need to reach your dream job.

Databases, Data Science, and Data Analytics Fundamentals

Author : Johnathan Mun
Publisher :
ISBN 13 : 9781734497380
Total Pages : 268 pages
Book Rating : 4.4/5 (973 download)

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Book Synopsis Databases, Data Science, and Data Analytics Fundamentals by : Johnathan Mun

Download or read book Databases, Data Science, and Data Analytics Fundamentals written by Johnathan Mun and published by . This book was released on 2020-04-27 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Slides for the course covering the fundamentals of databases. The material covered includes Basic SQL, IBM Cloud DB2, Microsoft Access, Microsoft Excel, Python, QDM SQL, Risk Simulator, ROV BizStats.

R for Data Science

Author : Hadley Wickham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Handbook of Data Analysis

Author : Melissa A Hardy
Publisher : SAGE
ISBN 13 : 1446203441
Total Pages : 728 pages
Book Rating : 4.4/5 (462 download)

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Book Synopsis Handbook of Data Analysis by : Melissa A Hardy

Download or read book Handbook of Data Analysis written by Melissa A Hardy and published by SAGE. This book was released on 2009-06-17 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electronic Inspection Copy available for instructors here 'This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond' - Environment and Planning 'The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher' - Clive Seale, Brunel University 'With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ' - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa 'This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments' - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.

Foundations of Data Science

Author : Avrim Blum
Publisher : Cambridge University Press
ISBN 13 : 1108617360
Total Pages : 433 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Foundations of Data Science by : Avrim Blum

Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Become a Python Data Analyst

Author : Alvaro Fuentes
Publisher : Packt Publishing Ltd
ISBN 13 : 1789534402
Total Pages : 170 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Become a Python Data Analyst by : Alvaro Fuentes

Download or read book Become a Python Data Analyst written by Alvaro Fuentes and published by Packt Publishing Ltd. This book was released on 2018-08-31 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enhance your data analysis and predictive modeling skills using popular Python tools Key Features Cover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data analysis techniques and detailed code with scikit-learn and SciPy Book Description Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations. Become a Python Data Analyst introduces Python’s most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations. In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques. By the end of this book, you will have hands-on experience performing data analysis with Python. What you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build predictive models and understand the principles of predictive analytics Who this book is for Become a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this book

Data Science for Undergraduates

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
ISBN 13 : 0309475597
Total Pages : 139 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis Data Science for Undergraduates by : National Academies of Sciences, Engineering, and Medicine

Download or read book Data Science for Undergraduates written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-11-11 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

Practical Packet Analysis

Author : Chris Sanders
Publisher : No Starch Press
ISBN 13 : 1593271492
Total Pages : 194 pages
Book Rating : 4.5/5 (932 download)

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Book Synopsis Practical Packet Analysis by : Chris Sanders

Download or read book Practical Packet Analysis written by Chris Sanders and published by No Starch Press. This book was released on 2007 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides information on ways to use Wireshark to capture and analyze packets, covering such topics as building customized capture and display filters, graphing traffic patterns, and building statistics and reports.

Doing Data Science

Author : Cathy O'Neil
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 144936389X
Total Pages : 408 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Doing Data Science by : Cathy O'Neil

Download or read book Doing Data Science written by Cathy O'Neil and published by "O'Reilly Media, Inc.". This book was released on 2013-10-09 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Storytelling with Data

Author : Cole Nussbaumer Knaflic
Publisher : John Wiley & Sons
ISBN 13 : 1119002265
Total Pages : 288 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Storytelling with Data by : Cole Nussbaumer Knaflic

Download or read book Storytelling with Data written by Cole Nussbaumer Knaflic and published by John Wiley & Sons. This book was released on 2015-10-09 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

Process Mining

Author : Wil M. P. van der Aalst
Publisher : Springer
ISBN 13 : 3662498510
Total Pages : 477 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Process Mining by : Wil M. P. van der Aalst

Download or read book Process Mining written by Wil M. P. van der Aalst and published by Springer. This book was released on 2016-04-15 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.

Guide to Business Data Analytics

Author : Iiba
Publisher :
ISBN 13 : 9781927584200
Total Pages : 172 pages
Book Rating : 4.5/5 (842 download)

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Book Synopsis Guide to Business Data Analytics by : Iiba

Download or read book Guide to Business Data Analytics written by Iiba and published by . This book was released on 2020-08-07 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Guide to Business Data Analytics provides a foundational understanding of business data analytics concepts and includes how to develop a framework; key techniques and application; how to identify, communicate and integrate results; and more. This guide acts as a reference for the practice of business data analytics and is a companion resource for the Certification in Business Data Analytics (IIBA(R)- CBDA). Explore more information about the Certification in Business Data Analytics at IIBA.org/CBDA. About International Institute of Business Analysis International Institute of Business Analysis(TM) (IIBA(R)) is a professional association dedicated to supporting business analysis professionals deliver better business outcomes. IIBA connects almost 30,000 Members, over 100 Chapters, and more than 500 training, academic, and corporate partners around the world. As the global voice of the business analysis community, IIBA supports recognition of the profession, networking and community engagement, standards and resource development, and comprehensive certification programs. IIBA Publications IIBA publications offer a wide variety of knowledge and insights into the profession and practice of business analysis for the entire business community. Standards such as A Guide to the Business Analysis Body of Knowledge(R) (BABOK(R) Guide), the Agile Extension to the BABOK(R) Guide, and the Global Business Analysis Core Standard represent the most commonly accepted practices of business analysis around the globe. IIBA's reports, research, whitepapers, and studies provide guidance and best practices information to address the practice of business analysis beyond the global standards and explore new and evolving areas of practice to deliver better business outcomes. Learn more at iiba.org.

Deep Learning for Coders with fastai and PyTorch

Author : Jeremy Howard
Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala