This course introduces the fundamentals of high-performance and parallel computing. It is targeted to scientists, engineers, scholars, really everyone seeking to develop the software skills necessary for work in parallel software environments. These skills include big-data analysis, machine learning, parallel programming, and optimization. We will cover the basics of Linux environments and bash scripting all the way to high throughput computing and parallelizing code. After completing this course, you will familiar with: *The components of a high-performance distributed computing system *Types of parallel programming models and the situations in which they might be used *High-throughput computing *Shared memory parallelism *Distributed memory parallelism *Navigating a typical Linux-based HPC environment *Assessing and analyzing application scalability including weak and strong scaling *Quantifying the processing, data, and cost requirements for a computational project or workflow This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

В настоящее время без сети не может обойтись ни кондитер, ни водитель. И даже дети, которые еще не ходят в школу, а то и в детский сад, уже пользуются сетями. Поэтому сейчас специалистов в этой области требуется всё больше. Наш курс поможет желающим разобраться во всех премудростях этого интереснейшей области. В этом курсе слушатели: - составят целостную картину о работе локальных и глобальных компьютерных сетей; - увидят, как передаётся информация, - поймут логику и принципы работы сетевых протоколов и базовых служб, - научатся диагностировать работоспособность сетевых соединений, выявлять и устранять неполадки, работать с сетевым анализатором, - освоят технологию виртуализации аппаратного обеспечения - и смогут создавать и размещать собственные сетевые серверы и веб-ресурсы на них. Слушатель получит представление и о самых низкоуровневых процессах в сети, и о высокоуровневых. После освоения курса слушатель сможет: - проектировать и разворачивать сети самостоятельно, - настраивать сетевое оборудование, - настраивать серверы и создавать веб-ресурсы, размещая их как удалённо на стороннем, так и локально на своём оборудовании. Курс включает в себя практическую часть, выполняемую при помощи средств виртуализации аппаратного обеспечения непосредственно на компьютере слушателя.

Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information. We start the first week by introducing some major systems for data analysis including Spark and the major frameworks and distributions of analytics applications including Hortonworks, Cloudera, and MapR. By the middle of week one we introduce the HDFS distributed and robust file system that is used in many applications like Hadoop and finish week one by exploring the powerful MapReduce programming model and how distributed operating systems like YARN and Mesos support a flexible and scalable environment for Big Data analytics. In week two, our course introduces large scale data storage and the difficulties and problems of consensus in enormous stores that use quantities of processors, memories and disks. We discuss eventual consistency, ACID, and BASE and the consensus algorithms used in data centers including Paxos and Zookeeper. Our course presents Distributed Key-Value Stores and in memory databases like Redis used in data centers for performance. Next we present NOSQL Databases. We visit HBase, the scalable, low latency database that supports database operations in applications that use Hadoop. Then again we show how Spark SQL can program SQL queries on huge data. We finish up week two with a presentation on Distributed Publish/Subscribe systems using Kafka, a distributed log messaging system that is finding wide use in connecting Big Data and streaming applications together to form complex systems. Week three moves to fast data real-time streaming and introduces Storm technology that is used widely in industries such as Yahoo. We continue with Spark Streaming, Lambda and Kappa architectures, and a presentation of the Streaming Ecosystem. Week four focuses on Graph Processing, Machine Learning, and Deep Learning. We introduce the ideas of graph processing and present Pregel, Giraph, and Spark GraphX. Then we move to machine learning with examples from Mahout and Spark. Kmeans, Naive Bayes, and fpm are given as examples. Spark ML and Mllib continue the theme of programmability and application construction. The last topic we cover in week four introduces Deep Learning technologies including Theano, Tensor Flow, CNTK, MXnet, and Caffe on Spark.

G Suite Mail Management is the fourth course in the G Suite Administration series. In this course you will learn how to protect your organization against spam, spoofing, phishing and malware attacks. You will configure email compliance and learn how to implement data loss prevention (DLP) for your organization. You will gain an understanding of the mail routing options available and learn how to whitelist and block senders. You will also become familiar with other mail options such as inbound and outbound gateways, 3rd party email archiving, and journaling to Vault. Learning Objectives By the end of this course participants will be able to: - Gain a basic understanding of the Domain Name System (DNS) used on the internet and be able to identify the record types used by G Suite. - Be able to implement common email security measures in your DNS records such as SPF, DKIM and DMARC and be able to explain the purpose of each measure. - Learn how to protect your users from inbound phishing and harmful software (malware). - Learn how to control which end user access features are available to your users. - Learn how to configure email whitelists, blacklists and approved sender lists to better manage mail delivery and protect against spam, phishing and malware. - Gain an understanding of the various compliance features provided in G Suite. - Gain a basic understanding of the mail routing options available to you as the G Suite administrator. Prerequisites You should have completed the Introduction to G Suite, Managing G Suite, and G Suite Security courses.

What makes WiFi faster at home than at a coffee shop? How does Google order its search results from the trillions of webpages on the Internet? Why does Verizon charge $15 for every GB of data we use? Is it really true that we are connected in six social steps or less? These are just a few of the many intriguing questions we can ask about the social and technical networks that form integral parts of our daily lives. This course is about exploring the answers, using a language that anyone can understand. We will focus on fundamental principles like “sharing is hard”, “crowds are wise”, and “network of networks” that have guided the design and sustainability of today’s networks, and summarize the theories behind everything from the social connections we make on platforms like Facebook to the technology upon which these websites run. Unlike other networking courses, the mathematics included here are no more complicated than adding and multiplying numbers. While mathematical details are necessary to fully specify the algorithms and systems we investigate, they are not required to understand the main ideas. We use illustrations, analogies, and anecdotes about networks as pedagogical tools in lieu of detailed equations. All the features of this course are available for free. It does not offer a certificate upon completion.

This course is the definitive introduction to blockchain for both the developer and non-developer audience. Beyond the technology, this course will introduce you to some of the philosophy behind decentralization and why there is so much excitement around it. During the first three modules, you'll be introduced to blockchain and the technology behind it. In module four, we'll go beyond bitcoin and delve deeper into a next-generation blockchain called Ethereum to introduce you to what modern blockchains can do. The use cases featured in the final module are drawn from among the businesses in ConsenSys' startup portfolio. We believe we're uniquely positioned to present you with a valuable behind-the-scenes look at the people and companies working in this space to help give you a better understanding of the business side of blockchain. Together, we'll examine businesses use cases, hear from industry leaders, and give you the opportunity to develop and analyze a use case yourself. With this course, not only will you be the one who is able to explain blockchain to your colleagues, you'll be well on your way to making educated business decisions with your new, foundational understanding of the technology.

By nature, cyber conflicts are an international issue that span across nation-state borders. By the end of the course, you will be able to apply the knowledge gained for analysis and management of international cyber incidents and conflicts including for activities such as development of policy related to cybercrime and cyberwarfare. Management of cyber incidents and conflicts requires an interdisciplinary perspective including an understanding of: 1) characteristics of the cyber threats and conflicts themselves, 2) international efforts to reduce and improve cyber security, and 3) psychological and sociopolitical factors. The course is designed to reach an international audience and will encourage discussion on relevant current events among participants to enrich the experience with various personal and cultural perspectives on cutting-edge issues. In addition, assignments and other assessments will supplement video lectures and selected readings to ensure application of the material. After taking this course you will be able to: • Identify different types of actors involved in cyber threats (individuals, organizations & nation-states) • Distinguish between different types of threats and issues in cyber security including, data theft, political espionage, critical infrastructure protection, and propaganda • Detail the basic characteristics of the Internet infrastructure and international efforts to address Internet governance • List several international efforts to address cyber crime and espionage • Evaluate how principals that govern international conflicts might be applied in context of cyber security • Apply different psychological theories of human motivation and cooperation and communication and political theories in analysis of different international issues related to cyber security including censorship, media operations and role of social technologies. Grading: Your grade is assessed based on discussion posts and quizzes. Individual taking this course for credit (i.e. students at the University at Albany y will be required to engage in additional activities communicated to them directly). Recommended Background: No background knowledge or skills are necessary, but an understanding and familiarity of cyber security, Internet infrastructure and international law would be advantageous for anyone who participates in the course. ACKNOWLEDGEMENTS Ersin Dincelli and Nic DePaula were the instructional designers for the course who assisted in the recording of the videos, reviewing material, creating slides, assessments and some of the content. Without their tremendous effort this would not have been possible. We also acknowledge the financial support for the recordings from the University at Albany as well as the support from Media and Marketing. Finally, thanks to Lisa Stephens who is the SUNY liaison to Coursera for being a strong supporter of the MOOC.

Computers are everywhere, they aren't just the desktops and laptops we use for work but the phones in our pockets and even the watches on our wrists are also computers. You probably use a computer every day and in fact you are reading this on a computer! Just because we use computers all the time, doesn't mean that we understand them, or find them easy to use. Computer Science is the science of computers, it is the field of knowledge that experts use to understand computer systems. Knowing a little computer science will help you understand the computers all around you. This isn't a how-to course for a particular piece of software, instead you will learn some fundamental concepts that you can apply to any software or computer system. You'll apply these concepts to the kind of computer systems we use every day, including word processing applications, e-commerce, the internet and web sites. You will learn how to apply computer science concepts to solve problems in daily computer use and generally be a better computer user. Taking this course could be the start of your career in computer science, and the course is an introduction to the Bachelors in Computer Science from University of London, but it is also for you if you just want to learn a little computer science to help you better understand the computers you use in your ordinary life.

This course introduces a series of advanced and current topics in cyber security, many of which are especially relevant in modern enterprise and infrastructure settings. The basics of enterprise compliance frameworks are provided with introduction to NIST and PCI. Hybrid cloud architectures are shown to provide an opportunity to fix many of the security weaknesses in modern perimeter local area networks. Emerging security issues in blockchain, blinding algorithms, Internet of Things (IoT), and critical infrastructure protection are also described for learners in the context of cyber risk. Mobile security and cloud security hyper-resilience approaches are also introduced. The course completes with some practical advice for learners on how to plan careers in cyber security.

What is the X-Factor? In Cybersecurity, the X-Factor related to unknown and unpredictable human behavior within and outside of your organization. “No one really knows why humans do what they do”, (David K. Reynolds), and because of this organizations can be unprepared for malicious, untrained, or even best intentioned behavior that can cause alarm and sometimes irreparable harm. This course will introduce you to the types of training available to reduce the impact of the X-Factor, evaluate its effectiveness, explore the Security Education, Training and Awareness (SETA) program, and learn why it may fail. The course will conclude with information designed to assist you with some critical components for your business security program. Activities focused on hactivism, cyberinsurance, and ransomware will round out your knowledge base. Your team of instructors has prepared a series of readings, discussions, guest lectures, and quizzes to engage you in this exciting topic.