This dataset provides comprehensive information about various Data Science and Analytics master's programs offered in the United States. It includes details such as the program name, university name, annual tuition fees, program duration, location of the university, and additional information about the programs.

Column Descriptions:

• Subject Name: The name or field of study of the master's program, such as Data Science, Data Analytics, or Applied Biostatistics.

• University Name: The name of the university offering the master's program.

• Per Year Fees: The tuition fees for the program, usually given in euros per year. For some programs, the fees may be listed as "full" or "full-time," indicating a lump sum for the entire program or for full-time enrollment, respectively.

• About Program: A brief description or overview of the master's program, providing insights into its curriculum, focus areas, and any unique features.

• Program Duration: The duration of the master's program, typically expressed in years or months.

• University Location: The location of the university where the program is offered, including the city and state.

• Program Name: The official name of the master's program, often indicating its degree type (e.g., M.Sc. for Master of Science) and format (e.g., full-time, part-time, online).

In 2023, ** percent of prospective graduate business students in the United States were interested in hybrid programs, an increase from ** percent in 2019. However, the overall preference in 2023 was for in-person business school programs, at ** percent.

A file that holds the master records for all online training courses nominated for reimbursement.

Key indicators of broadband adoption, service and infrastructure in New York City. Data Limitations: Data accuracy is limited as of the date of publication and by the methodology and accuracy of the original sources. The City shall not be liable for any costs related to, or in reliance of, the data contained in these datasets.

Between 2015 and 2024, the number of bachelor's students who graduated from online universities in Italy steadily increased. In 2015, less than ***** people obtained their bachelor's from an online university. After nine years, the number of students more than doubled, reaching ****** graduates. In Italy, bachelor's students represented the largest group of e-learning university students, ******* people.

China Number of Graduate: Postgraduate: Master Degree data was reported at 927.629 Person th in 2023. This records an increase from the previous number of 779.845 Person th for 2022. China Number of Graduate: Postgraduate: Master Degree data is updated yearly, averaging 334.613 Person th from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 927.629 Person th in 2023 and a record low of 38.051 Person th in 1998. China Number of Graduate: Postgraduate: Master Degree data remains active status in CEIC and is reported by Ministry of Education. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GD: No of Graduate: Higher Education: By Region.

Key indicators of the availability of internet service choice and speed based on publicly available data from the Federal Communications Commission Data Limitations: Data accuracy is limited as of the date of publication and by the methodology and accuracy of the original sources. The City shall not be liable for any costs related to, or in reliance of, the data contained in these datasets.

According to a 2023 survey, ** percent of undergraduate students who were studying online in the United States were White, while ** percent were Black or African-American. In comparison, ** percent of graduate students studying online in the United States in that year were White, while ** percent were Black or African American.

The data relates to the paper that analyses the determinants or factors that best explain student research skills and success in the honours research report module during the COVID-19 pandemic in 2021. The data used have been gathered through an online survey created on the Qualtrics software package. The research questions were developed from demographic factors and subject knowledge including assignments to supervisor influence and other factors in terms of experience or belonging that played a role (see anonymous link at https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY. An SMS was sent to all students of the 2021 module group to make them aware of the survey. They were under no obligation to complete it and all information was regarded as anonymous. We received 39 responses. The raw data from the survey was processed through the SPSS statistical, software package. The data file contains the demographics, frequencies, descriptives, and open questions processed.The study reported in this paper employed the mixed methods approach comprising a quantitative and qualitative analysis. The quantitative and econometric analysis of the dependent variable, namely, the final marks for the research report and the independent variables that explain it. The results show significance in terms of the assignments and existing knowledge marks in terms of their bachelor's average mark. We extended the analysis to a qualitative and quantitative survey, which indicated that the mean statistical feedback was above average and therefore strongly agreed/agreed except for library use by the student. Students, therefore, need more guidance in terms of library use and the open questions showed a need for a research methods course in the future. Furthermore, supervision tends to be a significant determinant in all cases. It is also here where supervisors can use social media instruments such as WhatsApp and Facebook to inform students further. This study contributes as the first to investigate the preparation and research skills of students for master's and doctoral studies during the COVID-19 pandemic in an online environment.

Web archive derivatives of the National Statistical Offices and Central Banks Web Archive collection from the Ivy Plus Libraries Confederation. The derivatives were created with the Archives Unleashed Toolkit and Archives Unleashed Cloud.

The ivy-10637-parquet.tar.gz derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples.

Domains

.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)

Produces a DataFrame with the following columns:

• domain
• count

Web Pages

.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))

Produces a DataFrame with the following columns:

• crawl_date
• url
• mime_type_web_server
• mime_type_tika
• content

Web Graph

.webgraph()

Produces a DataFrame with the following columns:

• crawl_date
• src
• dest
• anchor

Image Links

.imageLinks()

Produces a DataFrame with the following columns:

• src
• image_url

Binary Analysis

• Audio
• Images
• PDFs
• Presentation program files
• Spreadsheets
• Text files
• Word processor files
  

The ivy-10637-auk.tar.gz derivatives are the standard set of web archive derivatives produced by the Archives Unleashed Cloud.

• Gephi file, which can be loaded into Gephi. It will have basic characteristics already computed and a basic layout.
• Raw Network file, which can also be loaded into Gephi. You will have to use that network program to lay it out yourself.
• Full text file. In it, each website within the web archive collection will have its full text presented on one line, along with information around when it was crawled, the name of the domain, and the full URL of the content.
• Domains count file. A text file containing the frequency count of domains captured within your web archive.

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

This file set is the basis of a project in which Stephanie Pywell from The Open University Law School created and evaluated some online teaching materials – Fundamentals of Law (FoLs) – to fill a gap in the knowledge of graduate entrants to the Bachelor of Laws (LLB) programme. These students are granted exemption from the Level 1 law modules, from which they would normally acquire the basic knowledge of legal principles and methods that is essential to success in higher-level study. The materials consisted of 12 sessions of learning, each covering one key topic from a Level 1 law module.The dataset includes a Word document that consists of the text of a five-question, multiple-choice Moodle poll, together with the coding for each response option.The rest of the dataset consists of spreadsheets and outputs from SPSS and Excel showing the analyses that were conducted on the cleaned and anonymised data to ascertain students' use of, and views on, the teaching materials, and to explore any statistical association between students' studying of the materials and their academic success on Level 2 law modules, W202 and W203.Students were asked to complete the Moodle poll at the end of every session of study, of which there were 1,013. Only one answer from each of the 240 respondents was retained for Questions 3, 4 and 5, to avoid skewing the data. Some data are presented as percentages of the number of sessions studied; some are presented as percentages of the number of respondents, and some are presented as percentage of the number of respondents who meet specific criteria.Student identifiers, which have been removed to ensure anonymity, are as follows: Open University Computer User code (OUCU) and Personal Identifier (PI). These were used to collate the output from the Moodle poll with students' Level 2 module results.

The global massive open online course (MOOC) market size is calculated to advance at a CAGR of 32% through 2034, which is set to increase its market value from US$ 13.2 billion in 2024 to US$ 212.7 billion by the end of 2034.

Report Attribute	Detail
MOOC Market Size (2024E)	US$ 13.2 Billion
Projected Market Value (2034F)	US$ 212.7 Billion
Global Market Growth Rate (2024 to 2034)	32% CAGR
China Market Value (2034F)	US$ 23.3 Billion
Japan Market Growth Rate (2024 to 2034)	32.6% CAGR
North America Market Share (2024E)	23.9%
East Asia Market Value (2034F)	US$ 49.1 Billion
Key Companies Profiled	Alison; Coursera Inc; edX Inc; Federica.EU; FutureLearn; Instructure; Intellipaat; iverity; Jigsaw Academy; Kadenze.

Country Wise Insights

Attribute	United States
Market Value (2024E)	US$ 1.4 Billion
Growth Rate (2024 to 2034)	32.5% CAGR
Projected Value (2034F)	US$ 23.6 Billion

Attribute	China
Market Value (2024E)	US$ 1.5 Billion
Growth Rate (2024 to 2034)	32% CAGR
Projected Value (2034F)	US$ 23.3 Billion

Category-wise Insights

Attribute	xMOOC
Segment Value (2024E)	US$ 9.3 Billion
Growth Rate (2024 to 2034)	30.8% CAGR
Projected Value (2034F)	US$ 136.1 Billion

Attribute	Degree & Master Programs
Segment Value (2024E)	US$ 6.4 Billion
Growth Rate (2024 to 2034)	30.2% CAGR
Projected Value (2034F)	US$ 89.3 Billion

Morocco Number of Internet Subscribers data was reported at 42,127,000.000 Unit in Sep 2024. This records an increase from the previous number of 39,145,000.000 Unit for Jun 2024. Morocco Number of Internet Subscribers data is updated quarterly, averaging 7,094,075.000 Unit from Dec 2003 (Median) to Sep 2024, with 84 observations. The data reached an all-time high of 42,127,000.000 Unit in Sep 2024 and a record low of 60,812.000 Unit in Dec 2003. Morocco Number of Internet Subscribers data remains active status in CEIC and is reported by National Telecommunication Regulatory Agency. The data is categorized under Global Database’s Morocco – Table MA.TB001: Internet Statistics.

Snapshot img

Distance Learning Market Size 2024-2028

The distance learning market size is forecast to increase by USD 149.23 billion at a CAGR of 9.65% between 2023 and 2028.

The growing demand for distance learning, fueled by the continuous development of technology, is a key driver of the distance learning market. As technology improves, online education becomes more accessible, engaging, and effective, allowing students to learn remotely with ease. The integration of advanced tools such as video conferencing, AI-driven assessments, and interactive content is further enhancing the appeal of distance learning.
In North America, the market is experiencing significant growth due to the integration of advanced technologies and shifting educational preferences. With a growing emphasis on flexible, personalized learning experiences, including self-paced e-learning, institutions are increasingly offering distance learning programs that cater to diverse student needs. This trend is expected to continue, contributing to the market's expansion in the region.

What will be the Size of the Distance Learning Market During the Forecast Period?

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The market is experiencing significant growth due to the increasing adoption of remote learning solutions among K-12 students and higher education students. Online assessments, video conferencing sessions, and virtual schools are becoming popular flexible education options for students who require flexibility in their learning schedules. Website-based mediums and application-based mediums, such as e-learning platforms, are increasingly being used to deliver educational programs. Internet access is essential for distance learning, making online learning platforms an indispensable tool for universities and colleges.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD Billion' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

Type

  Traditional
  Online


Method

  Synchronous distance learning
  Asynchronous distance learning


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  Middle East and Africa



  South America

By Type Insights

The traditional segment is estimated to witness significant growth during the forecast period. The market encompasses various methods and technologies, including gamification, personalized learning pathways, educational environments, and remote learning techniques. Traditional distance learning, characterized by asynchronous online courses, pre-recorded lecture books, and minimal instructor interaction, remains a significant revenue contributor. This approach caters to a broad audience, particularly those with limited access to digital devices or high-internet connectivity. Academic institutions and the government sector continue to offer traditional distance learning programs, such as those provided by the Open University in the UK via mail. However, corporate blended learning, online education solutions, and personalized learning solutions are gaining popularity due to their interactive and technologically advanced nature.

These methods include learning management systems, virtual classrooms, mobile e-learning platforms, and cloud-based e-Learning platforms. Moreover, the use of intranet connection, computers, tutorials, podcasts, recorded lectures, e-books, and machine learning technology enhances the learning experience. The market also serves academic users and corporate users through service providers and content providers. The increasing literacy rate, internet penetration, and the need for continuous skill upgrading further fuel the market's growth.

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The traditional segment accounted for USD 152.29 billion in 2018 and showed a gradual increase during the forecast period.

Regional Insights

North America is estimated to contribute 34% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The market in North America is experiencing significant growth due to the integration of advanced technologies and shifting educational preferences. With the rise of gamification, personalized learning pathways, and educational environments, online education solutions have become increasingly popular. Academic institutions and the government sector are expanding their digital services, offering distance learning programs through Learning Management Systems and cloud-based e-Learning platforms. Remote learning methods, such as pre-recorded lectures, tutorials

The International STEM Graduate Student Survey assesses why international students are coming to the United States for their graduate studies, the challenges they have faced while studying in the US, their future career plans, and whether they wish to stay or leave the US upon graduation. According to the Survey of Earned Doctorates by the National Science Foundation and the National Center for Science and Engineering Statistics, international students accounted for over 40% of all US doctoral graduates in STEM in 2013. The factors that influence international students' decisions to study in the US and whether they will stay or leave are important to US economic competitiveness. We contacted graduate students (both domestic and international) in STEM disciplines from the top 10 universities ranked by the total number of enrolled international students. We estimate that we contacted approximately 15,990 students. Individuals were asked to taken an online survey regarding their background, reasons for studying in the US, and whether they plan to stay or leave the US upon graduation. We received a total of 2,322 completed surveys, giving us a response rate of 14.5%. 1,535 of the completed were from domestic students and 787 of which were from international students. Raw survey data are presented here.Survey participants were contacted via Qualtrics to participate in this survey. The Universe of this survey data set pertains to all graduate students (Master's and PhD) in STEM disciplines from the following universities: Columbia University, University of Illinois-Urbana Champaign, Michigan State University, Northeastern University, Purdue University, University of Southern California, Arizona State University, University of California at Los Angeles, New York University, University of Washington at Seattle. Data are broken into 2 subsets: one for international STEM graduate students and one for domestic STEM graduate students, please see respective files.

Raw data for the manuscript entitled: European Agrifood and Forestry Education for a Sustainable Future - Gap Analysis from an Informatics Approach

Abstract

Purpose: To evaluate how well European agrifood and forestry Masters program websites use vocabulary associated with the NextFood Project ‘categories of skills’.

Methodology: Web-scraping Python scripts were used to collect texts from European Masters programs websites, which were then analysed using statistical tools including Partial Least Squares Regression and contextual relation analysis. A total of fourteen countries, twenty-seven universities, 1303 European Masters programs, 3305 web-pages and almost two million words were studied using this approach.

Findings: While agrifood and forestry Masters programs used vocabulary from the NextFood Project ‘categories of skills’ in most cases equal to or more often than non-agrifood and forestry Masters programs, we found evidence for the relative underuse of words associated with networking skills, with least use among agriculture-related Masters programs.

Practical Implications: The informatic approach provides evidence that European agrifood and forestry Masters programs are for the most part following the educational paths for meeting future challenges as outlined by the NextFood Project, with the possible exception of networking skills.

Theoretical Implications: This text-based, informatic approach complements the more targeted approaches taken by the NextFood Project in studying the skilling-pathways, which involved focus-group interviews, surveys of stakeholders, interviews of individuals with expert-knowledge and literature reviews.

Originality: A text-based, web-scraping informatic approach has thus far been limited in the study of agrifood and forestry higher education, especially relative to recent advances made in the social sciences.

This dataset contains counts of live births for California as a whole based on information entered on birth certificates. Final counts are derived from static data and include out of state births to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all births that occurred during the time period.

The final data tables include both births that occurred in California regardless of the place of residence (by occurrence) and births to California residents (by residence), whereas the provisional data table only includes births that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by parent giving birth's age, parent giving birth's race-ethnicity, and birth place type. See temporal coverage for more information on which strata are available for which years.

Libraries Statistics: MA. Table 14. Libraries with web page by type of library. National.