anchor.diff:  The Beauty of Kunqu Opera,kunqu-opera,https://coursera.org/learn/kunqu-opera,Arts and Humanities,The Chinese University of Hong Kong,"This course will focus on the historical and cultural background, literary aesthetics, music, and performance of Kunqu, China’s classical opera. After viewing the lecture videos presented by scholars and renowned maestros in the field of Kunqu, students’ understanding and appreciation of Chinese performing arts, classical literature and traditional culture will be enhanced."
   "The Bible's Prehistory, Purpose, and Political Future",bible-history,https://coursera.org/learn/bible-history,Arts and Humanities,Emory University,"With its walls razed to ground by Babylon’s armies, Jerusalem joined a long line of ancient vanquished cities—from Ur and Nineveh and Persepolis to Babylon itself. While some recovered from the destruction, others did not. But none responded to political catastrophe by fashioning the kind of elaborate and enduring monument to their own downfall that we find in the Bible. Most conquered populations viewed their subjugation as a source of shame. They consigned it to oblivion, opting instead to extol the golden ages of the past."
   The Blues: Understanding and Performing an American Art Form,the-blues,https://coursera.org/learn/the-blues,Arts and Humanities,University of Rochester,"The blues is an American art form and the most important musical form in jazz. Although there are other formal paradigms of the blues, such as 8-bar or 16-bar, this course focuses on different incarnations of the 12-bar blues. There are considerable differences between Early Jazz blues, Swing blues, Bebop blues, Modal blues, and Post Bop blues. Each type has its unique harmonic syntax, melodic vocabulary and, associated with them, improvisational techniques."
  +The Changing Landscape of Ancient Rome. Archaeology and History of the Palatine Hill,palatine-carafa,https://coursera.org/learn/palatine-carafa,Arts and Humanities,Sapienza University of Rome,"Studying ancient - as well as medieval or modern - cities basically means telling local urban stories based on the reconstruction of changing landscapes through the centuries. Given the fragmentary nature of archaeological evidence, it is necessary to create new images that would give back the physical aspect of the urban landscape and that would bring it to life again. We are not just content with analyzing the many elements still visible of the ancient city. The connections between objects and architectures, visible and non visible buildings, which have been broken through time have to be rejoined, to acknowledge the elements that compose the urban landscape. 
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  +Landscape and its content are a very relevant and still vital part of any national cultural heritage. The course will introduce students to the way we have been reflecting on over the last twenty years and still are engaged with the study of the past of our cities, beginning from the most complex case in the ancient Mediterranean World: the core of Italy and of Roman Empire. On the other hand, knowledge means also preservation and defense of material remains and cultural memory.
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  +“The Changing Landscape of Ancient Rome. Archeology and History of the Palatine Hill” presents to a large public the topographical lay-out of the most relevant part of the city (according the Greek and Roman Historians Rome was founded on the Palatine). Research developed on the Palatine since the end of last century by the team of Sapienza Classical Archaeologists opened a new phase in the urban archaeological investigation and in the scientific debate about the relation between archaeological features and literary tradition as well as the “correct use“ of both kind of evidence, key issues of wide archaeological and historical significance."
   The Cycle: Management of Successful Arts and Cultural Organizations,the-cycle,https://coursera.org/learn/the-cycle,Arts and Humanities,"University of Maryland, College Park","What makes a successful arts and cultural organization? Led by DeVos Institute Chairman Michael M. Kaiser and President Brett Egan, this course will introduce you to a management theory called the Cycle which supports thriving arts and cultural organizations. Learning from our work with managers from over 80 countries around the world, the DeVos Institute developed the Cycle as a simple, but powerful tool to assist managers in their effort to respond to an increasingly complex environment and propel their institutions to excellence. The Cycle explains how great art and strong marketing can create a family of supporters, who in turn help the organization produce the revenue required to support even more great art the next year. The Institute has seen the Cycle work in performing and presenting organizations, as well as museums, arts schools, and other nonprofit endeavors like service organizations, historical societies, public libraries, university programs, advocacy organizations, botanical gardens, and zoos."
   The Emergence of the Modern Middle East - Part I,modern-middle-east-1,https://coursera.org/learn/modern-middle-east-1,Arts and Humanities,Tel Aviv University,"This course will discuss the emergence of the modern Middle East from the fall of the Ottoman Empire, at the end of the First World War to the present. It will discuss the Ottoman legacy in the region and the Western imperial impact on the creation of the Arab state system. The course will discuss the rise and retreat of Arab nationalism, the problems of internal cohesion of the Arab states, issues of religion and state, and the evolution of Islamist politics."
   The Emergence of the Modern Middle East - Part II,modernmiddleeast2,https://coursera.org/learn/modernmiddleeast2,Arts and Humanities,Tel Aviv University,"This course will discuss the developments in the Middle East from the early 20th century to the present. It will discuss the rise and retreat of Arab nationalism, the problems of internal cohesion of the Arab states, issues of religion and state, and the evolution of Islamist politics. It will also focus on the evolution of the Arab-Israeli conflict and its impact on the region and will conclude with an in depth analysis of the “Arab Spring” by placing these contemporary revolutionary events in their historical context."
  
positive.code: Advanced R Programming,advanced-r,https://coursera.org/learn/advanced-r,Data Science,Johns Hopkins University,"This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Because every data science environment encounters unique data challenges, there is always a need to develop custom software specific to your organization’s mission."
  Algorithms for DNA Sequencing,dna-sequencing,https://coursera.org/learn/dna-sequencing,Data Science,Johns Hopkins University,"We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets."
  An Intuitive Introduction to Probability,introductiontoprobability,https://coursera.org/learn/introductiontoprobability,Data Science,University of Zurich,"This course will provide you with an intuitive and practical introduction into Probability Theory. You will be able to learn how to apply Probability Theory in different scenarios and you will earn a ""toolbox"" of methods to deal with uncertainty in your daily life. The course is split in 5 modules. In each module you will first have an easy introduction into the topic, which will serve as a basis to further develop your knowledge about the topic and acquire the ""tools"" to deal with uncertainty. Additionally, you will have the opportunity to complete 5 exercise sessions to reflect about the content learned in each module and start applying your earned knowledge right away."
  "Applied Plotting, Charting & Data Representation in Python",python-plotting,https://coursera.org/learn/python-plotting,Data Science,University of Michigan,"This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework."
  "Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions",descriptive-statistics-statistical-distributions-business-application,https://coursera.org/learn/descriptive-statistics-statistical-distributions-business-application,Data Science,Rice University,"The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers. Different categories of descriptive measures are introduced and discussed along with the Excel functions to calculate them. The notion of probability or uncertainty is introduced along with the concept of a sample and population data using relevant business examples. This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You get to apply these descriptive measures of data and various statistical distributions using easy-to-follow Excel based examples which are demonstrated throughout the course."
  Basic Statistics,basic-statistics,https://coursera.org/learn/basic-statistics,Data Science,University of Amsterdam,"Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics."
  
negative.code: Classification,ml-classification,https://coursera.org/learn/ml-classification,Data Science,University of Washington,"In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank. These tasks are an examples of classification, one of the most widely used areas of machine learning, with a broad array of applications, including ad targeting, spam detection, medical diagnosis and image classification."
  Cluster Analysis in Data Mining,cluster-analysis,https://coursera.org/learn/cluster-analysis,Data Science,University of Illinois at Urbana-Champaign,"Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications."
  Clustering & Retrieval,ml-clustering-and-retrieval,https://coursera.org/learn/ml-clustering-and-retrieval,Data Science,University of Washington,"A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents? Each time you want to a retrieve a new document, do you need to search through all other documents? How do you group similar documents together? How do you discover new, emerging topics that the documents cover? In this third case study, finding similar documents, you will examine similarity-based algorithms for retrieval. In this course, you will also examine structured representations for describing the documents in the corpus, including clustering and mixed membership models, such as latent Dirichlet allocation (LDA)."
  Combining and Analyzing Complex Data,data-collection-analytics-project,https://coursera.org/learn/data-collection-analytics-project,Data Science,"University of Maryland, College Park","In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions.  Software capabilities will be covered with R® receiving particular emphasis.  The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources.  Combining of datasets raises ethical issues which the course reviews.  Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.
  "
  Command Line Tools for Genomic Data Science,genomic-tools,https://coursera.org/learn/genomic-tools,Data Science,Johns Hopkins University,"Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University."
  Communicating Business Analytics Results,communicating-business-analytics-results,https://coursera.org/learn/communicating-business-analytics-results,Data Science,University of Colorado Boulder,"The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions. Presenting findings to decision makers who are not familiar with the language of analytics presents a challenge. In this course you will learn how to communicate analytics results to stakeholders who do not understand the details of analytics but want evidence of analysis and data. You will be able to choose the right vehicles to present quantitative information, including those based on principles of data visualization. You will also learn how to develop and deliver data-analytics stories that provide context, insight, and interpretation."
  "Communicating Results: Visualization, Ethics, Reproducibility",datasci3,https://coursera.org/learn/datasci3,Data Science,University of Washington,"Important note: The second assignment in this course covers the topic of Graph Analysis in the Cloud, in which you will use Elastic MapReduce and the Pig language to perform graph analysis over a moderately large dataset, about 600GB. In order to complete this assignment, you will need to make use of Amazon Web Services (AWS). Amazon has generously offered to provide up to $50 in free AWS credit to each learner in this course to allow you to complete the assignment. Further details regarding the process of receiving this credit are available in the welcome message for the course, as well as in the assignment itself."
  