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| cisco introduction to data science: Data Analytics for IT Networks John Garrett, 2018-10-24 Use data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance. Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use cases Explore and access network data sources, and choose the right data for your problem Innovate more successfully by understanding mental models and cognitive biases Walk through common analytics use cases from many industries, and adapt them to your environment Uncover new data science use cases for optimizing large networks Master proven algorithms, models, and methodologies for solving network problems Adapt use cases built with traditional statistical methods Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication Fully leverage your existing Cisco tools to collect, analyze, and visualize data |
| cisco introduction to data science: Introduction To Data Science Gaoyan Ou, Zhanxing Zhu, Bin Dong, Weinan E, 2023-11-24 The book systematically introduces the basic contents of data science, including data preprocessing and basic methods of data analysis, handling special problems (e.g. text analysis), deep learning, and distributed systems.In addition to systematically introducing the basic content of data science from a theoretical point of view, the book also provides a large number of data analysis practice cases. |
| cisco introduction to data science: A General Introduction to Data Analytics João Moreira, Andre Carvalho, Tomás Horvath, 2018-06-25 A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms. |
| cisco introduction to data science: A Hands-On Introduction to Data Science Chirag Shah, 2020-04-02 An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines. |
| cisco introduction to data science: The Data Science Design Manual Steven S. Skiena, 2017-07-01 This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) |
| cisco introduction to data science: Data Science for Business Foster Provost, Tom Fawcett, 2013-07-27 Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the data-analytic thinking necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates |
| cisco introduction to data science: Competing on Analytics: Updated, with a New Introduction Thomas Davenport, Jeanne Harris, 2017-08-29 The New Edition of a Business Classic This landmark work, the first to introduce business leaders to analytics, reveals how analytics are rewriting the rules of competition. Updated with fresh content, Competing on Analytics provides the road map for becoming an analytical competitor, showing readers how to create new strategies for their organizations based on sophisticated analytics. Introducing a five-stage model of analytical competition, Davenport and Harris describe the typical behaviors, capabilities, and challenges of each stage. They explain how to assess your company’s capabilities and guide it toward the highest level of competition. With equal emphasis on two key resources, human and technological, this book reveals how even the most highly analytical companies can up their game. With an emphasis on predictive, prescriptive, and autonomous analytics for marketing, supply chain, finance, M&A, operations, R&D, and HR, the book contains numerous new examples from different industries and business functions, such as Disney’s vacation experience, Google’s HR, UPS’s logistics, the Chicago Cubs’ training methods, and Firewire Surfboards’ customization. Additional new topics and research include: Data scientists and what they do Big data and the changes it has wrought Hadoop and other open-source software for managing and analyzing data Data products—new products and services based on data and analytics Machine learning and other AI technologies The Internet of Things and its implications New computing architectures, including cloud computing Embedding analytics within operational systems Visual analytics The business classic that turned a generation of leaders into analytical competitors, Competing on Analytics is the definitive guide for transforming your company’s fortunes in the age of analytics and big data. |
| cisco introduction to data science: Advanced Wireless LAN Song Guo, 2012-06-05 The past two decades have witnessed starling advances in wireless LAN technologies that were stimulated by its increasing popularity in the home due to ease of installation, and in commercial complexes offering wireless access to their customers. This book presents some of the latest development status of wireless LAN, covering the topics on physical layer, MAC layer, QoS and systems. It provides an opportunity for both practitioners and researchers to explore the problems that arise in the rapidly developed technologies in wireless LAN. |
| cisco introduction to data science: Data Science from Scratch Joel Grus, 2015-04-14 Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases |
| cisco introduction to data science: Enterprise Networking, Security, and Automation Companion Guide (CCNAv7) Cisco Networking Academy, 2020-07-08 Enterprise Networking, Security, and Automation Companion Guide is the official supplemental textbook for the Enterprise Networking, Security, and Automation v7 course in the Cisco Networking Academy CCNA curriculum. This course describes the architectures and considerations related to designing, securing, operating, and troubleshooting enterprise networks. You will implement the OSPF dynamic routing protocol, identify and protect against cybersecurity threats, configure access control lists (ACLs), implement Network Address Translation (NAT), and learn about WANs and IPsec VPNs. You will also learn about QoS mechanisms, network management tools, network virtualization, and network automation. The Companion Guide is designed as a portable desk reference to use anytime, anywhere to reinforce the material from the course and organize your time. The book's features help you focus on important concepts to succeed in this course: * Chapter objectives: Review core concepts by answering the focus questions listed at the beginning of each chapter. * Key terms: Refer to the lists of networking vocabulary introduced and highlighted in context in each chapter. * Glossary: Consult the comprehensive Glossary with more than 500 terms. * Summary of Activities and Labs: Maximize your study time with this complete list of all associated practice exercises at the end of each chapter. * Check Your Understanding: Evaluate your readiness with the end-of-chapter questions that match the style of questions you see in the online course quizzes. The answer key explains each answer. How To: Look for this icon to study the steps you need to learn to perform certain tasks. Interactive Activities: Reinforce your understanding of topics with dozens of exercises from the online course identified throughout the book with this icon. Videos: Watch the videos embedded within the online course. Packet Tracer Activities: Explore and visualize networking concepts using Packet Tracer exercises interspersed throughout the chapters and provided in the accompanying Labs & Study Guide book. Hands-on Labs: Work through all the course labs and additional Class Activities that are included in the course and published in the separate Labs & Study Guide. This book is offered exclusively for students enrolled in Cisco Networking Academy courses. It is not designed for independent study or professional certification preparation. Visit netacad.com to learn more about program options and requirements. Related titles: CCNA 200-301 Portable Command Guide Book: 9780135937822 eBook: 9780135937709 31 Days Before Your CCNA Exam Book: 9780135964088 eBook: 9780135964231 CCNA 200-301 Official Cert Guide, Volume 1 Book: 9780135792735 Premium Edition: 9780135792728 CCNA 200-301 Official Cert Guide, Volume 2 Book: 9781587147135 Premium Edition: 9780135262719 |
| cisco introduction to data science: Network Programmability and Automation Fundamentals Khaled Abuelenain, Jeff Doyle, Anton Karneliuk, Vinit Jain, 2021-05-06 Modernize and optimize network management with APIs and automation Legacy network management approaches don't scale adequately and can't be automated well. This guide will help meet tomorrow's challenges by adopting network programmability based on Application Programming Interfaces (APIs). Using these techniques, you can improve efficiency, reliability, and flexibility; simplify implementation of high-value technologies; automate routine administrative and security tasks; and deploy services far more rapidly. Four expert authors help you transition from a legacy mindset to one based on solving problems with software. They explore today's emerging network programmability and automation ecosystem; introduce each leading programmable interface; and review the protocols, tools, techniques, and technologies that underlie network programmability. You'll master key concepts through hands-on examples you can run using Linux, Python, Cisco DevNet sandboxes, and other easily accessible tools. This guide is for all network architects, engineers, operations, and software professionals who want to integrate programmability into their networks. It offers valuable background for Cisco DevNet certification—and skills you can use with any platform, whether you have software development experience or not. Master core concepts and explore the network programmability stack Manage network software and run automation scripts in Linux environments Solve real problems with Python and its Napalm and Nornir automation frameworks Make the most of the HTTP protocol, REST architectural framework, and SSH Encode your data with XML, JSON, or YAML Understand and build data models using YANG that offer a foundation for model-based network programming Leverage modern network management protocols, from gRPC and gNMI to NETCONF and RESTCONF Meet stringent service provider KPIs in large-scale, fast-changing networks Program Cisco devices running IOS XE, IOS XR, and NX-OS as well as Meraki, DNA Center, and Webex platforms Program non-Cisco platforms such as Cumulus Linux and Arista EOS Go from “zero to hero” with Ansible network automation Plan your next steps with more advanced tools and technologies |
| cisco introduction to data science: Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud, Global Edition Paul Deitel, 2021-05-31 |
| cisco introduction to data science: Data Science on AWS Chris Fregly, Antje Barth, 2021-04-07 With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more |
| cisco introduction to data science: Analytics, Data Science, and Artificial Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2020-03-06 For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT. |
| cisco introduction to data science: Data Science For Cyber-security Nicholas A Heard, Niall M Adams, Patrick Rubin-delanchy, Mellisa Turcotte, 2018-09-26 Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies. |
| cisco introduction to data science: Machine Learning and Security Clarence Chio, David Freeman, 2018-01-26 Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions |
| cisco introduction to data science: CCNA Data Center - Introducing Cisco Data Center Networking Study Guide Todd Lammle, John Swartz, 2013-06-05 Cisco has announced big changes to its certification program. As of February 24, 2020, all current certifications will be retired, and Cisco will begin offering new certification programs. The good news is if you’re working toward any current CCNA certification, keep going. You have until February 24, 2020 to complete your current CCNA. If you already have CCENT/ICND1 certification and would like to earn CCNA, you have until February 23, 2020 to complete your CCNA certification in the current program. Likewise, if you’re thinking of completing the current CCENT/ICND1, ICND2, or CCNA Routing and Switching certification, you can still complete them between now and February 23, 2020. A must-have study guide for exam 640-911 on Cisco's Unified Data Center The Cisco Certified Network Associate Data Center certification is Cisco's newest certification, covering the Cisco Unified Data Center technologies. Written by unparalleled author and Cisco authority Todd Lammle, and CCIE John Swartz, this comprehensive study guide is essential reading for anyone preparing to take the 640-911 exam (Introducing Cisco Data Center Networking), providing in-depth coverage of all the exam's objectives. In addition, it offers expanded coverage on key topics reflected on the exam. Addresses understanding basic networking and ethernet technologies Reviews the OSI and DoD model and TCP/IP Transport Layer Covers basic IP routing technologies, layer 2 switching technologies, and routing principles Provides an introduction to Nexus switch as well as how to configure it CCNA Data Center Study Guide offers you access to additional study tools, including bonus practice exams, electronic flashcards, a searchable PDF of a glossary of terms. Plus, you will be able to use the free nexus simulator to perform all the hands-on labs in the book. |
| cisco introduction to data science: Introduction to Cisco Router Configuration , 1998 |
| cisco introduction to data science: Data Science Xiaohui Cheng, Weipeng Jing, Xianhua Song, Zeguang Lu, 2019-09-13 This two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application. |
| cisco introduction to data science: Data Center Fundamentals Mauricio Arregoces, Maurizio Portolani, 2003-12-04 Master the basics of data centers to build server farms that enhance your Web site performance Learn design guidelines that show how to deploy server farms in highly available and scalable environments Plan site performance capacity with discussions of server farm architectures and their real-life applications to determine your system needs Today's market demands that businesses have an Internet presence through which they can perform e-commerce and customer support, and establish a presence that can attract and increase their customer base. Underestimated hit ratios, compromised credit card records, perceived slow Web site access, or the infamous Object Not Found alerts make the difference between a successful online presence and one that is bound to fail. These challenges can be solved in part with the use of data center technology. Data centers switch traffic based on information at the Network, Transport, or Application layers. Content switches perform the best server selection process to direct users' requests for a specific service to a server in a server farm. The best server selection process takes into account both server load and availability, and the existence and consistency of the requested content. Data Center Fundamentals helps you understand the basic concepts behind the design and scaling of server farms using data center and content switching technologies. It addresses the principles and concepts needed to take on the most common challenges encountered during planning, implementing, and managing Internet and intranet IP-based server farms. An in-depth analysis of the data center technology with real-life scenarios make Data Center Fundamentals an ideal reference for understanding, planning, and designing Web hosting and e-commerce environments. |
| cisco introduction to data science: Cisco Packetized Voice and Data Integration Robert Caputo, 2000 Cisco Packetized Voice and Data Integration gives you the knowledge and insight to quickly get up to speed on planning, designing, and implementing Cisco-based voice and data networks. Through the use of real-world examples, case studies, and detailed configuration analyses, you will obtain the skills necessary to successfully deploy voice and data networks. Book jacket. |
| cisco introduction to data science: Automate Your Network: Introducing the Modern Approach to Enterprise Network Management John W. Capobianco, 2019-03-09 Network automation is one of the hottest topics in Information Technology today. This revolutionary book aims to illustrate the transformative journey towards full enterprise network automation. This book outlines the tools, technologies and processes required to fully automate an enterprise network. Automated network configuration management is more than converting your network configurations to code. The benefits of source control, version control, automated builds, automated testing and automated releases are realized in the world of networking using well established software development practices. The next-generation network administrative toolkit is introduced including Microsoft Team Foundation Server, Microsoft Visual Studio Code, Git, Linux, and the Ansible framework. Not only will these new technologies be covered at length, a new and continuously integrated / continuously delivered pipeline is also introduced. Starting with safe, simple, non-intrusive, non-disruptive information gathering organizations can ease into network automation while building a dynamic library of documentation and on-demand utilities for network operations. Once comfortable with the new ecosystem, administrators can begin making fully automated, orchestrated, and tactical changes to the network. The next evolutionary leap occurs when fully automated network configuration management is implemented. Important information from the network running-configurations is abstracted into data models in a human readable format. Device configurations are dynamically templated creating a scalable, intent-based, source of truth. Much like in the world of software development, full automation of the network using a CI/CD pipeline can be realized. Automated builds, automated testing and automated scheduled releases are orchestrated and executed when changes are approved and checked into the central repository. This book is unlike any on the market today as it includes multiple Ansible playbooks, sample YAML data models and Jinja2 templates for network devices, and a whole new methodology and approach to enterprise network administration and management. The CLI no longer cuts it. Readers should take away from this book a new approach to enterprise network management and administration as well as the full knowledge and understanding of how to use TFS, VS Code, Git, and Ansible to create an automation ecosystem. Readers should have some basic understanding of modern network design, operation, and configuration. No prior programming or software development experience is required. John Capobianco has over 20 years of IT experience and is currently a Technical Advisor for the Canadian House of Commons. A graduate of St. Lawrence College's Computer Programmer Analyst program, John is also a former Professor at St. Lawrence College in the Computer Networking and Technical Support (CNTS) program. John has achieved CCNP, CCDP, CCNA: Data Center, MCITP: EA/SA, CompTIA A+ / Network+, and ITIL Foundation certifications. Having discovered a new way to interface with the network John felt compelled to share this new methodology in hopes of revolutionizing the industry and bringing network automation to the world. |
| cisco introduction to data science: Cisco CCNA/CCENT Exam 640-802, 640-822, 640-816 Preparation Kit Dale Liu, 2009-06-30 Three exams, two certifications, one complete Cisco training solution for networking professionals! The CCNA exam is an entry-level IT certification from Cisco Systems for professionals installing and maintaining route and switched networks. The current exam material covers networking concepts along with new and updated content on network security fundamentals and the basics of wireless networking. This book can be used as a study guide for either track you choose to receive your CCNA – the single exam, 640-802 or the combined 640-822 and 640-816, and for the CCENT certification which a student will receive upon completion of the 640-822 exam. The author team has arranged the content so that you can easily identify the objectives for each half of the combined exam. - Layout of the guide parallels the CCNA/CCENT exam objectives for ease of study - Details all aspects of the exams including security and wireless networking essentials - Covers everything from introductory to advanced topics—keeping the beginner and intermediate IT professional in mind - Chapter ending questions and answers allow for graduated learning - Two practice exams on the accompanying DVD help eliminate test-day jitters |
| cisco introduction to data science: Introducing Routing and Switching in the Enterprise, CCNA Discovery Learning Guide Allan Reid, Jim Lorenz, Cheryl A. Schmidt, 2008-04-25 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introducing Routing and Switching in the Enterprise, CCNA Discovery Learning Guide is the official supplemental textbook for the Introducing Routing and Switching in the Enterprise course in the Cisco® Networking Academy® CCNA® Discovery curriculum version 4. The course, the third of four in the new curriculum, familiarizes you with the equipment applications and protocols installed in enterprise networks, with a focus on switched networks, IP Telephony requirements, and security. It also introduces advanced routing protocols such as Enhanced Interior Gateway Routing Protocol (EIGRP) and Open Shortest Path First (OSPF) Protocol. Hands-on exercises include configuration, installation, and troubleshooting. The Learning Guide’s features help you focus on important concepts to succeed in this course: Chapter Objectives—Review core concepts by answering the focus questions listed at the beginning of each chapter. Key Terms—Refer to the lists of networking vocabulary introduced and highlighted in context in each chapter. The Glossary defines each key term. Summary of Activities and Labs—Maximize your study time with this complete list of all associated exercises at the end of each chapter. Check Your Understanding—Evaluate your readiness with the end-of-chapter questions that match the style of questions you see in the online course quizzes. The answer key explains each answer. Challenge Questions and Activities—Apply a deeper understanding of the concepts with these challenging end-of-chapter questions and activities. The answer key explains each answer. Hands-on Labs— Master the practical, hands-on skills of the course by performing all the tasks in the course labs and additional challenge labs included in Part II of the Learning Guide. This book is part of the Cisco Networking Academy Series from Cisco Press®. Books in this series support and complement the Cisco Networking Academy curriculum. |
| cisco introduction to data science: CCNP Enterprise Cisco Networking Academy, 2020-08-18 This hands-on routing Lab Manual is the perfect companion for all Cisco Networking Academy students who are taking the new course CCNP Cisco Networking Academy CCNP Enterprise: Core Networking (ENCOR) as part of their CCNP preparation. It offers a portable, bound copy of all CCNP ENCOR network routing labs in a convenient, lightweight format that allows students to walk through key procedures and easily take notes without a large textbook or a live Internet connection. Working with these conveniently-formatted labs, students will gain practical experience and skills for using advanced IP addressing and routing in implementing scalable and secure Cisco ISR routers connected to LANs and WANs; and for configuring secure routing solutions to support branch offices and mobile workers. |
| cisco introduction to data science: Web and Network Data Science Thomas W. Miller, 2015 Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University's prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems. |
| cisco introduction to data science: Handbook of Data Analysis Melissa A Hardy, Alan Bryman, 2009-06-17 ′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. |
| cisco introduction to data science: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Chkoniya, Valentina, 2021-06-25 The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students. |
| cisco introduction to data science: Internet of Things and Big Data Analytics for a Green Environment Yousef Farhaoui, Bharat Bhushan, Nidhi Sindhwani, Rohit Anand, Agbotiname Lucky Imoize, Anshul Verma, 2024-11-27 This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field. Key Features: • Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics. • Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment. • Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment. • Provides a systematic overview of the state-of-the-art research efforts. • Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment. This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment. |
| cisco introduction to data science: Advanced Deep Learning Applications in Big Data Analytics Bouarara, Hadj Ahmed, 2020-10-16 Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students. |
| cisco introduction to data science: A Beginning to Data Science with Python Dr. S. Britto Ramesh Kumar, K.Vani, 2023-02-22 This text is a fundamental reference for Data Science using Python required for Computer Science Professional. Authors cover basic concepts of python and Data Science with a step-by-step, “hands on” pedagogical approach with suitable examples together with Python’s clear and simple syntax, which help the reader to teach and learn from. By the time the user completes the book, they will able to do simple data analysis. |
| cisco introduction to data science: Big Data, Cloud Computing, Data Science & Engineering Roger Lee, 2018-08-13 This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science. |
| cisco introduction to data science: Cisco CCNA Routing and Switching ICND 200-101 Wendell Odom, 2013 CCNA ICND2 200-101 Official Cert Guide, Academic Edition, is a comprehensive textbook and study package for an intermediate-level networking course. This book has been completely revised to align to Cisco''s new CCNA 200-101 ICND2 exam. Material is presented in a concise manner, focusing on increasing student''s retention and recall of exam topics. The book is printed in four color, allowing students to benefit from carefully crafted figures that utilize color to convey concepts. Students will organize their study through the use of the consistent features in these chapters, including: Foundation Topics -- These sections make up the majority of the page count, explaining concepts, configurations, with emphasis on the theory and concepts, and with linking the theory to the meaning of the configuration commands. Key Topics -- Inside the Foundation Topics sections, every figure, table, or list that should absolutely be understood and remembered for the exam is noted with the words Key Topic in the margin. This tool allows the reader to quickly review the most important details in each chapter. Chapter-ending Summaries -- These bulleted lists provide a quick and concise review of the key topics covered in each chapter. Chapter-ending Review Questions -- Each chapter provides a set of multiple choice questions that help student''s test their knowledge of the chapter concepts, including answers and full explanations. Chapter-ending Exercises -- Each chapter concludes with a series of exercises designed to help students increase their retention of the chapter content including key term reviews, key topic tables, command review exercises, and memory table exercises. Part Reviews -- This new edition includes a new part review feature that helps students consolidate their knowledge of concepts presented across multiple chapters. A new mind mapping exercise helps students build strong mental maps of concepts. A new exam bank of part review questions helps students test themselves with scenario-based questions that span multiple topics. In addition to these powerful chapter learning, review, and practice features, this book also contains several other features that make it a truly effective and comprehensive study package, including: A Getting Started chapter at the beginning of the book offer terrific advice for how to use the book features and build an effective study plan. The DVD contains over 60 minutes of video mentoring from the author on challenging topics such as OSPF, EIGRP, EIGRP Metrics, PPP, and CHAP. The book comes complete with the CCNA ICND2 Network Simulator Lite software, providing students with the opportunity to practice their hands-on command line interface skills with Cisco routers and switches. The 13 labs included for free with this product cover a range of EIGRP configuration and troubleshooting exercises. The Pearson IT Certification Practice Test software that comes with the book includes 4 full ICND2 exams and 4 full CCNA exams, providing tons of opportunities to assess and practice. Including the book review questions and part review questions, the exam bank includes more than 500 unique practice questions. A Final Preparation Chapter helps students review for final exams and prepare to take the official Cisco CCNA exams, if they want to achieve that certification. A Study Plan Template is included on the DVD to help students organize their study time. |
| cisco introduction to data science: Big Data Analytics for Smart and Connected Cities Dey, Nilanjan, Tamane, Sharvari, 2018-09-07 To continue providing people with safe, comfortable, and affordable places to live, cities must incorporate techniques and technologies to bring them into the future. The integration of big data and interconnected technology, along with the increasing population, will lead to the necessary creation of smart cities. Big Data Analytics for Smart and Connected Cities is a pivotal reference source that provides vital research on the application of the integration of interconnected technologies and big data analytics into the creation of smart cities. While highlighting topics such as energy conservation, public transit planning, and performance measurement, this publication explores technology integration in urban environments as well as the methods of planning cities to implement these new technologies. This book is ideally designed for engineers, professionals, researchers, and technology developers seeking current research on technology implementation in urban settings. |
| cisco introduction to data science: Data Science and Intelligent Applications Ketan Kotecha, Vincenzo Piuri, Hetalkumar N. Shah, Rajan Patel, 2020-06-17 This book includes selected papers from the International Conference on Data Science and Intelligent Applications (ICDSIA 2020), hosted by Gandhinagar Institute of Technology (GIT), Gujarat, India, on January 24–25, 2020. The proceedings present original and high-quality contributions on theory and practice concerning emerging technologies in the areas of data science and intelligent applications. The conference provides a forum for researchers from academia and industry to present and share their ideas, views and results, while also helping them approach the challenges of technological advancements from different viewpoints. The contributions cover a broad range of topics, including: collective intelligence, intelligent systems, IoT, fuzzy systems, Bayesian networks, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, speech processing, machine learning and deep learning, and intelligent applications and systems. Helping strengthen the links between academia and industry, the book offers a valuable resource for instructors, students, industry practitioners, engineers, managers, researchers, and scientists alike. |
| cisco introduction to data science: Cognitive Social Mining Applications in Data Analytics and Forensics Haldorai, Anandakumar, Ramu, Arulmurugan, 2018-12-14 Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals. |
| cisco introduction to data science: Data Science for Genomics Amit Kumar Tyagi, Ajith Abraham, 2022-11-27 Data Science for Genomics presents the foundational concepts of data science as they pertain to genomics, encompassing the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions and supporting decision-making. Sections cover Data Science, Machine Learning, Deep Learning, data analysis, and visualization techniques. The authors then present the fundamentals of Genomics, Genetics, Transcriptomes and Proteomes as basic concepts of molecular biology, along with DNA and key features of the human genome, as well as the genomes of eukaryotes and prokaryotes. Techniques that are more specifically used for studying genomes are then described in the order in which they are used in a genome project, including methods for constructing genetic and physical maps. DNA sequencing methodology and the strategies used to assemble a contiguous genome sequence and methods for identifying genes in a genome sequence and determining the functions of those genes in the cell. Readers will learn how the information contained in the genome is released and made available to the cell, as well as methods centered on cloning and PCR. - Provides a detailed explanation of data science concepts, methods and algorithms, all reinforced by practical examples that are applied to genomics - Presents a roadmap of future trends suitable for innovative Data Science research and practice - Includes topics such as Blockchain technology for securing data at end user/server side - Presents real world case studies, open issues and challenges faced in Genomics, including future research directions and a separate chapter for Ethical Concerns |
| cisco introduction to data science: Machine Intelligence and Data Science Applications Amar Ramdane-Cherif, T. P. Singh, Ravi Tomar, Tanupriya Choudhury, Jung-Sup Um, 2023-10-03 This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications (MIDAS 2022), held on October 28 and 29, 2022, at the University of Versailles—Paris-Saclay, France. The book covers applications in various fields like data science, machine intelligence, image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis. It also includes interdisciplinary applications like legal, healthcare, smart society, cyber-physical system, and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in the machine intelligence discipline, and engineering graduates. |
| cisco introduction to data science: Practical Data Science for Information Professionals David Stuart, 2020-07-24 Practical Data Science for Information Professionals provides an accessible introduction to a potentially complex field, providing readers with an overview of data science and a framework for its application. It provides detailed examples and analysis on real data sets to explore the basics of the subject in three principle areas: clustering and social network analysis; predictions and forecasts; and text analysis and mining. As well as highlighting a wealth of user-friendly data science tools, the book also includes some example code in two of the most popular programming languages (R and Python) to demonstrate the ease with which the information professional can move beyond the graphical user interface and achieve significant analysis with just a few lines of code. After reading, readers will understand: · the growing importance of data science · the role of the information professional in data science · some of the most important tools and methods that information professionals can use. Bringing together the growing importance of data science and the increasing role of information professionals in the management and use of data, Practical Data Science for Information Professionals will provide a practical introduction to the topic specifically designed for the information community. It will appeal to librarians and information professionals all around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, it aims to reduce barriers for readers to use the lessons learned within. |
| cisco introduction to data science: Computational Science and Its Applications – ICCSA 2020 Osvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blečić, David Taniar, Bernady O. Apduhan, Ana Maria A.C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca, 2020-09-30 The seven volumes LNCS 12249-12255 constitute the refereed proceedings of the 20th International Conference on Computational Science and Its Applications, ICCSA 2020, held in Cagliari, Italy, in July 2020. Due to COVID-19 pandemic the conference was organized in an online event. Computational Science is the main pillar of most of the present research, industrial and commercial applications, and plays a unique role in exploiting ICT innovative technologies. The 466 full papers and 32 short papers presented were carefully reviewed and selected from 1450 submissions. Apart from the general track, ICCSA 2020 also include 52 workshops, in various areas of computational sciences, ranging from computational science technologies, to specific areas of computational sciences, such as software engineering, security, machine learning and artificial intelligence, blockchain technologies, and of applications in many fields. |
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INTRODUCTION TO DATA SCIENCE
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Protect Your Sensitive Data From Generative AI Usage
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Source: Cisco IBSG, 2012 • Data: With IoT, devices typically gather data and stream it over the Internet to a central source, where it is analyzed and processed. As the capabilities of things …
The Profound Effects of Data Science on Business and Society
INTRODUCTION Data Science is revolutionizing how we solve complex challenges, unlocking unprecedented opportunities for both businesses and communities. It is using recent data …
Introduction - Cisco
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