Inhalt: Artificial intelligence (AI) offers businesses the potential for a dramatic increase in functionality and profitability, but it can also spark an array of complex ethical, legal, and social challenges. In this nontechnical, conceptually oriented course, Barton Poulson digs into the hazards of AI, offering potential solutions to key concerns. Barton explores the ethical issues posed by AI, including competing concepts of fairness and moral reasoning. He also goes over social concerns and safety challenges for AI, such as potential life-and-death scenarios in autonomous driving. Barton concludes with recommendations tailored to developers, executives, PR professionals, regulators, and consumers to help them reap the potential of AI in a manner that''s worthy of trust and profitable to all. Umfang: 02:21:49.00
Inhalt: The hype about big data may have peaked several years ago, but big data is far from gone. Instead it forms the foundation for some of today's most exciting technologies. Artificial intelligence (AI), machine learning, and data science rely on big data, or data that-by virtue of its velocity, volume, or variety-can't be easily stored or analyzed with traditional methods. In this nontechnical course, Barton Poulson digs into the topic of big data, explaining how it works and shapes our modern data universe. Barton explains big data's relationship to AI, data science, social media, and the Internet of Things (IoT). He goes over some of the ethical issues behind the use of big data. Plus, he covers techniques involved in analyzing big data, including data mining and predictive analytics. Umfang: 02:07:37.00
Inhalt: Big Data ist in aller Munde. Aber was genau ist darunter zu verstehen? Einfach ausgedrückt sind Daten dann Big Data, wenn Sie wegen Ihrer Menge, der Geschwindigkeit, in der sie entstehen oder ihrer Vielfalt kaum mit herkömmlichen Methoden und Tools gespeichert oder analysiert werden können. In diesem Training erklärt Ihnen Barton Poulsen Methoden, die für Big Data funktionieren und führt Sie in all die Techniken und Konzepte ein, die es erlauben Big Data zu erfassen, zu speichern, zu manipulieren und zu analysieren. Er erklärt ebenso die Beziehung von Big Data zu Fachgebieten wie Statistik, Programmierung und Data Science, wie auch die Verwendung von Big Data z.B. in der Forschung oder Marketing und ethische Problemstellungen, die bei der Nutzung auftreten können. Umfang: 01:57:51.00
Inhalt: Der Big-Data-Hype mag zwar vor einigen Jahren seinen Höhepunkt erreicht haben, aber Big Data ist bei Weitem nicht verschwunden. Im Gegenteil, Big Data bildet die Grundlage einiger der spannendsten heutigen Technologien. Künstliche Intelligenz (KI), Maschinelles Lernen und Data Science hängen von Big Data ab - Daten, die wegen ihrer Menge, ihrer Geschwindigkeit und ihrer Vielfalt mit traditionellen Methoden nicht leicht zu speichern oder zu analysieren sind. In diesem anfängerfreundlichen Kurs führt Sie Barton Poulson in das Thema Big Data ein und erklärt Ihnen, wie Big Data funktioniert und unser modernes Datenuniversum prägt. Sie lernen Techniken zur Analyse von Big Data, wie z. B. Data Mining und Predictive Analytics kennen und erfahren, wie Big Data mit KI, Data Science, Social Media und dem Internet der Dinge (IoT) zusammenhängt. Außerdem behandelt Barton auch einige der ethischen Probleme im Zusammenhang mit der Nutzung von Big Data. (Übersetzung des Kurses aus dem Englischen: Dorothea Heymann-Reder) Umfang: 01:48:30
Inhalt: Creating a well-crafted data visualization is a hands-on process. Challenge yourself with this series of real-world data visualization scenarios in Processing, an open-source drawing and development environment. Barton Poulson, author of the companion Interactive Data Visualization with Processing course, reinforces core concepts with mini-projects that help you practice drawing and interacting with data. A comprehensive challenge at the end of the course shows how to take data from a spreadsheet to a full-fledged online, interactive experience. Umfang: 01:41:29.00
Inhalt: Data analysis isn't just for specialists who need to make sense of massive datasets. Decision-makers in every industry can benefit from a basic understanding of the goals and concepts of applied data analysis. In this course, join Barton Poulson as he focuses on the fundamentals of data fluency, or the ability to work with data to extract insights and determine your next steps. Barton shows how exploring data with graphs and describing data with statistics can help you reach your goals and make better decisions. Instead of focusing on particular tools, he concentrates on general procedures that can help you solve specific problems. Find out how to prepare data, explore it visually, and use statistical methods to describe it. Umfang: 04:19:09.00
Inhalt: Data Science treibt eine weltweite Revolution an, die alles beeinflusst, von der Automatisierung in Unternehmen bis zur sozialen Interaktion. Data Science ist auch eines der am schnellsten wachsenden und einträglichsten Berufsfelder, in dem auf aller Welt Analyst:innen und Techniker:innen beschäftigt werden. Dieser LinkedIn Learning-Kurs gibt einen verständlichen, nicht allzu technischen Überblick über dieses Gebiet. Er behandelt die Terminologie, Fähigkeiten, Berufe, Tools und Techniken rund um Data Science. Barton Poulson definiert die Beziehungen zu anderen datenlastigen Feldern, wie zum Beispiel Machine Learning und Künstliche Intelligenz. Er erklärt die Hauptaufgaben: Wie Sie Daten sammeln und analysieren, wie Sie Regeln für Klassifizierung und Entscheidungsfindung formulieren und wie Sie aus alledem Erkenntnisse gewinnen, die zu informiertem Handeln führen. Er geht auch auf die Themenbereiche Ethik und Verantwortung ein und gibt Tipps, wo Sie weiterlernen können. Am Ende des Kurses verstehen Sie, wie Ihnen Data Science helfen kann, bessere Entscheidungen zu treffen, tiefere Einblicke zu gewinnen und Ihre Arbeit wirkungsvoller und schneller zu tun. (Übersetzung des Kurses aus dem Englischen: Dorothea Heymann-Reder) Umfang: 03:26:38
Inhalt: All data science begins with good data. Data mining is a framework for collecting, searching, and filtering raw data in a systematic matter, ensuring you have clean data from the start. It also helps you parse large data sets, and get at the most meaningful, useful information. This course, Data Science Foundations: Data Mining, is designed to provide a solid point of entry to all the tools, techniques, and tactical thinking behind data mining. Barton Poulson covers data sources and types, the languages and software used in data mining (including R and Python), and specific task-based lessons that help you practice the most common data-mining techniques: text mining, data clustering, association analysis, and more. This course is an absolute necessity for those interested in joining the data science workforce, and for those who need to obtain more experience in data mining. Umfang: 04:40:50.00
Inhalt: Data mining is the area of data science that focuses on finding actionable patterns in large and diverse datasets: clusters of similar customers, trends over time that can only be spotted after disentangling seasonal and random effects, and new methods for predicting important outcomes. In this course, instructor Barton Poulson introduces you to data mining that uses the programming language Python. Barton goes over some preliminaries, such as the tools you may use for data mining. He discusses aspects of dimensionality reduction, then explains clustering, including hierarchical clustering, k-Means, DBSCAN, and more. Barton covers classification, including kNN and decision trees. He goes into association analysis and introduces you to Apriori, Eclat, and FP-Growth. Barton steps you through a time-series decomposition, then concludes with sentiment scoring and other text mining tools. Umfang: 03:03:26
Inhalt: Data science continues to grow in sophistication and demand at an exponential rate. Data mining is the area of data science that focuses on finding actionable patterns in large and diverse datasets: clusters of similar customers, trends over time that can only be spotted after disentangling seasonal and random effects, and new methods for predicting important outcomes. Instructor Barton Poulson focuses on data mining in R, presents a broad range of algorithms including machine learning methods, and offers important information on laws and policies that affect data mining. Barton gives an overview of dimensionality reduction. He introduces clustering, including hierarchical clustering, then goes into association analysis. He explains time-series mining and decomposition, then concludes with text mining, sentiment analysis, and sentiment scoring. Umfang: 03:51:30
Inhalt: Data science is driving a world-wide revolution that touches everything from business automation to social interaction. It's also one of the fastest growing, most rewarding careers, employing analysts and engineers around the globe. This course provides an accessible, nontechnical overview of the field, covering the vocabulary, skills, jobs, tools, and techniques of data science. Instructor Barton Poulson defines the relationships to other data-saturated fields such as machine learning and artificial intelligence. He reviews the primary practices: gathering and analyzing data, formulating rules for classification and decision-making, and drawing actionable insights. He also discusses ethics and accountability and provides direction to learn more. By the end, you'll see how data science can help you make better decisions, gain deeper insights, and make your work more effective and efficient. Umfang: 03:41:57.00
Inhalt: Dieses Training führt Sie in das Thema Data Science ein, also die Beschaffung, Durchdringung, Modellierung und Interpretation von Daten. Barton Poulson erläutert für Data Science wichtige Disziplinen wie Programmierung, Statistik, Mathematik, Machine Learning, Datenanalyse, Virtualisierung und Big Data. Er erklärt, warum die Nachfrage nach Data Science-Spezialisten so hoch ist und welche Fähigkeiten in diesem Bereich am wichtigsten sind. Er zeigt Ihnen, wie Daten erhoben werden können und führt Sie in häufig für Data Science verwendete Sprachen wie R, Python und SQL ein. Am Ende des Trainings werden Sie den Stellenwert und die Möglichkeiten von Data Science bei der Erzeugung von Wissen aus den komplexen und großen Datenmengen, die uns heutzutage umgeben, verstehen. Umfang: 03:03:30.00
Inhalt: Cada dia mais empresas se apoiam em dados para tomar decisões e melhorar os seus produtos. R é uma linguagem de programação gratuita, de código aberto, voltada para ciência de dados e está entre as ferramentas mais utilizadas para análise e manipulação de dados por profissionais da área. Aprenda o básico de R e inicie a sua jornada no mundo dos dados, com a instrutora e especialista em ciência de dados Jessica Temporal. As aulas vão te ensinar os primeiros passos com R, incluindo como instalar a linguagem e a ferramenta RStudio, assim como utilizar diversos pacotes da vasta biblioteca de pacotes disponível. Você vai ver em primeira mão como fazer modelagem de dados, visualizações e análises estatísticas. Após terminar o curso, você vai ter um conhecimento básico, mas completo do poder e da flexibilidade de R, e entender como aproveitar essa ferramenta para explorar e analisar uma variedade de dados. Umfang: 01:28:48
Inhalt: Este curso de introdução proporciona uma visão abrangente da ciência de dados moderna: a prática da coleta, exploração, modelagem e interpretação de dados. Embora a maioria das pessoas só pense no "grande assunto", o Big Data, há muitas outras áreas e conceitos a investigar. Barton Poulson aborda disciplinas como programação, estatística, matemática, aprendizado de máquina, análise e visualização de dados e, é claro, Big Data. Ele explica por que existe tanta demanda por cientistas de dados atualmente e as competências necessárias para ter sucesso em diferentes tarefas. Barton mostra como obter dados de repositórios legítimos de código aberto por meio de Web APIs e scraping de páginas, além de apresentar tecnologias (R, Python e SQL) e técnicas (máquinas de vetores de suporte e florestas aleatórias) específicas para análise. Ao final do curso, você deve entender melhor o papel da ciência de dados na obtenção de conhecimentos expressivos a partir dos grandes e complexos conjuntos de dados ao nosso redor. Umfang: 03:01:15.00
Inhalt: Toda ciência de dados começa com bons dados. A mineração de dados é uma abordagem para coleta, pesquisa e filtragem de dados brutos em situações sistemáticas, garantindo a obtenção de dados limpos desde o começo. Também auxilia na análise de grandes conjuntos de dados e na obtenção das informações mais úteis e relevantes. Este curso, Fundamentos da Ciência de Dados: Mineração de Dados, visa oferecer uma introdução sólida a todas as ferramentas, técnicas e raciocínio tático por trás da mineração de dados. Barton Poulson aborda fontes e tipos de dados, as linguagens e os programas usados na mineração de dados (incluindo R e Python) e lições específicas baseadas em tarefas que ajudam a praticar as técnicas mais comuns de mineração de dados: mineração de textos, agrupamento de dados, análise de associação e muito mais. Este curso é fundamental para os interessados em ingressar na força de trabalho de ciência de dados e para quem precisa adquirir mais experiência em mineração de dados. Umfang: 04:29:50
Inhalt: Descubre la ciencia del big data. Conoce cómo se relaciona con campos como la ciencia de datos, la estadística y la programación; y cómo está revolucionando una amplia variedad de sectores, como el consumo, la investigación e, incluso, el ámbito empresarial. Aprende lo que son los macrodatos o los datos masivos, las tres V del big data: volumen, velocidad y variedad, los datos no estructurados o semiestructurados y la importancia de la privacidad de dichos datos en cada uno de estos puntos. Umfang: 02:21:27.00
Inhalt: El curso Fundamentos de data science nos da una visión general de la ciencia de datos moderna: la práctica de obtener, explorar, dar forma e interpretar los datos. Aunque muchos creen que la ciencia de datos solo se relaciona con big data, existen muchos más campos y conceptos que explorar. Barto Poulson nos explica disciplinas como la programación, la estadística, las matemáticas, el aprendizaje automático, el análisis de datos, la visualización y (sí), big data. Además, nos revela por qué los científicos de datos tienen tanta demanda, y qué habilidades se requieren para tener éxito en varias tareas relacionadas con este campo. También nos muestra cómo obtener datos a partir de bases de datos de libre acceso, mediante API y la técnica de extracción de datos, y nos introduce a tecnologías (R, Python y SQL) y técnicas (máquinas de vectores de soporte y bosques aleatorios) específicas para el análisis. Al acabar el curso, entenderás mejor la función de la ciencia de datos a la hora de aportar información significativa sobre los conjuntos de datos complejos y amplios que tenemos a nuestro alrededor. Umfang: 03:19:58.00
Inhalt: O Big Data é uma grande novidade. Mas o que é Big Data e como podemos usá-lo? Simplificando, Big Data são dados que, em virtude de sua velocidade, volume ou variedade (os três vês), não podem ser facilmente armazenados ou analisados usando métodos tradicionais. As planilhas e bancos de dados relacionais não bastam para trabalhar com Big Data. Neste curso, Barton Poulson fala dos métodos que realmente funcionam, apresentando todas as técnicas e conceitos envolvidos na captura, armazenamento, manipulação e análise de Big Data, inclusive mineração de dados e análise preditiva. Ele explica a relação entre Big Data e ciência de dados, estatística e programação; seus usos em marketing, pesquisa científica e ferramentas como o mecanismo de recomendações da Amazon; e as questões éticas subjacentes à sua utilização. Umfang: 02:04:24.00
Inhalt: jamovi is a free, open-source data analysis application that bridges the gap between the freedom and power of R and the accessibility of SPSS. In this course, learn how to do data analysis that's both fast and friendly with jamovi. Instructor Barton Poulson demonstrates how to install jamovi and third-party modules, import and wrangle data, create visualizations based on ggplot2, and analyze data using advanced methods. Plus, see how to share your work with unified files and collaborate with the Open Science Framework (OSF). Umfang: 04:41:08.00
Inhalt: Get a first look at Julia, the powerful and fast programming language for data science and analytics. Julia is growing quickly in popularity and many data science practitioners are interested in learning more. This fast-paced course provides a general introduction to the language's functionality, power, and limitations. Discover how Julia compares to C, R, and Python and how to call those languages in, how to format data with the different data types, how to perform math and vectorized operations, how to create expressions and run macros, and more. You can decide whether to incorporate Julia into your data science workflow or follow the next steps to learn more. Umfang: 00:33:37.00
Inhalt: If you want to participate in the data revolution, you need the right tools and skills. R is a free, open-source language for data science that is among the most popular platforms for professional analysts. Learn the basics of R and get started finding insights from your own data, in this course with professor and data scientist Barton Poulson. The lessons explain how to get started with R, including installing R, RStudio, and code packages that extend R's power. You also see first-hand how to use R and RStudio for beginner-level data modeling, visualization, and statistical analysis. By the end of the course, you'll have a thorough introduction to the power and flexibility of R, and understand how to leverage this tool to explore and analyze a wide variety of data. Umfang: 02:51:42.00
Inhalt: Ce cours donne une vue d'ensemble de la data science moderne, également appelée science des données en français, et qui est la pratique consistant à collecter, explorer, modéliser et interpréter des données. Si le big data monopolise toutes les attentions, il existe bien d'autres domaines et concepts intéressants. Barton Poulson évoque ici des branches telles que la programmation, les statistiques, les mathématiques, le machine learning, les analyses de données, la visualisation et (oui) le big data. Il explique pourquoi les data scientists sont si demandés et décrit les compétences requises pour réussir dans les différents métiers. Il montre aussi comment collecter des données à partir de référentiels open source via des API web ou via le scraping, et présente certaines technologies (R, Python et SQL) ainsi que certaines techniques (machines à vecteurs supports et forêts aléatoires) d'analyse. À l'issue de cette formation, vous devriez mieux comprendre l'utilité de la data science pour obtenir des informations exploitables à partir des jeux de données complexes qui vous entourent. Umfang: 02:41:40.00
Inhalt: Start communicating ideas and diagramming data in a more interactive way. In this course, author Barton Poulson shows how to read, map, and illustrate data with Processing, an open-source drawing and development environment. On top of a solid introduction to Processing itself, this course investigates methods for obtaining and preparing data, designing for data visualization, and building an interactive experience out of a design. When your visualization is complete, explore the options for sharing your work, whether uploading it to specialized websites, embedding the visualizations in your own web pages, or even creating a desktop or Android app for your work. Umfang: 07:43:24.00
Inhalt: Trying to locate meaning and direction in big data is difficult. R can help you find your way. R is a statistical programming language to analyze and visualize the relationships between large amounts of data. It's one of the most important tools available for data analysis, machine learning, and data science. This training series provides a thorough introduction to R, with detailed instruction for working with R and RStudio and hands-on examples, from exploratory graphics to neural networks. In part two, Modeling Data, instructor Barton Poulson shows how to compute statistics, analyze data, predict outcomes, and group and classify cases. These are the fundamental techniques you need to generate meaningful insights for your organization. Umfang: 03:59:34.00
Inhalt: Trying to locate meaning and direction in big data is difficult. R can help you find your way. R is a statistical programming language to analyze and visualize the relationships between large amounts of data. This training series provides a thorough introduction to R, with detailed instruction for installing and navigating R and RStudio and hands-on examples, from exploratory graphics to neural networks. In part one, instructor Barton Poulson shows how to get R and popular R packages up and running and start importing, cleaning, and converting data for analysis. He also shows how to create visualizations such as bar charts, histograms, and scatterplots and transform categorical, qualitative, and outlier data to best meet your research questions and the requirements of your algorithms. Umfang: 04:18:36.00
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