In 2024, it was projected that people in the United States with a Master’s degree in Computer Science would have the highest average starting salary, at 85,403 U.S. dollars. People who held a Master’s degree in Engineering were projected to have the second-highest starting salary, at 83,628 U.S. dollars. An abundance of Masters As higher education in the United States has become more common, and even expected, the number of Master’s degrees awarded has increased. During the 1949-50 academic year, about 58,180 Master’s degrees were awarded to students, with the vast majority being earned by male students. In the 2018-19 academic year, this figure increased to about 833,710 Master’s degrees awarded, with the majority being earned by female students. The right career While Engineering might have the highest starting pay for Master’s degree holders, those with a Master’s degree as a Physician Assistant had the highest mid-career median pay in 2021. Engineering continues to be one of the most popular fields for those seeking their Master’s degree, and STEM fields continue to dominate the field in number of Master’s degrees awarded.

Studyportals dataset provides a comprehensive set of data that can help students find Master's programs in Computer Science and IT worldwide. 🌍

This Dataset features a database of universities and colleges from around the world that offer Master's programs in these fields. Students can search for programs based on various criteria such as location, specialization, duration, and tuition fees.

• Once students find a program of interest, Studyportals provides detailed information about the program, including the curriculum, admission requirements, application deadlines, and tuition fees. Students can also read reviews and ratings from other students who have completed the program, which can help them make informed decisions about their education.

• Studyportals also offers a range of resources to help students prepare for their Master's program in Computer Science and IT. These resources include language courses, standardized test preparation courses, and career advice.

• Overall, Studyportals is a useful resource for students who are interested in pursuing a Master's program in Computer Science and IT, as it provides a comprehensive database of programs and offers a range of resources to help students prepare for their studies.

1. Times Higher Education Ranking (2018): The Times Higher Education (THE) ranking is one of the most prestigious university rankings in the world. It ranks universities based on various factors such as research, teaching quality, knowledge transfer, and international outlook. Some universities that may be included in this ranking are the University of Oxford (UK), the University of Cambridge (UK), and Stanford University (USA).

2. Shanghai Jiao Tong University Ranking (2017): The Shanghai Jiao Tong University (SJTU) ranking is another well-known university ranking system. It focuses mainly on research performance and ranks universities based on factors such as Nobel Prize winners, highly cited researchers, and publications in top journals. Some universities that may be included in this ranking are Harvard University (USA), the University of Tokyo (Japan), and the University of Toronto (Canada).

   1. TopUniversities Ranking (2018): The TopUniversities ranking is based on several factors such as academic reputation, employer reputation, and research impact. It is widely used by students and universities to compare different institutions. Some universities that may be included in this ranking are the Massachusetts Institute of Technology (USA), the University of Cambridge (UK), and the University of Melbourne (Australia).

3. U.S. News & World Report Ranking (2018): The U.S. News & World Report ranking focuses primarily on American universities and colleges, but it also includes some international institutions. It ranks universities based on factors such as research performance, student outcomes, and academic reputation. Some universities that may be included in this ranking are Princeton University (USA), the California Institute of Technology (USA), and the University of Oxford (UK).

"""When using Studyportals, students can search for universities based on their rankings in these systems and also filter by location, program, tuition fees, and other criteria. This can help students find universities that meet their specific needs and preferences."""

Objective: To describe the history, origin, objectives, characteristics, implications, the questions of the evaluation form and some examples of the Professional Masters (MP), to differentiate the Academic Master, and identify the challenges for the next quadrennial assessment. Methods: The CAPES site on Professional Masters and documents and meeting area of reports from 2004 to 2013 of Medicine III were read as well as the reports and the sub-page of the area in Capes site. The data relating to the evaluation process and the Scoreboard of the other areas were computed and analyzed. From these data it was detected the challenges of Medicine III for the next four years (2013-2016). Results: The creation of the Professional Master is very recent in Medicine III and no Professional Master of Medicine III course was evaluated yet. Were described the objectives, assumptions, characteristics, motivations, the possibilities, the feasibility, the profile of the students, the faculty, the curriculum, funding, intellectual production, social inclusion, the general requirements of Ordinance No. 193/2011 CAPES and some examples of proposals, technological lines of scientific activities, partnerships and counterparties. The evaluation form of the MP was discussed, the need for social, economic and political intellectual production and the differences with the MA. It was also reported the global importance of the MP and its evolution in Brazil. From the understanding of the MP, Medicine III outlined some challenges and goals to be developed in the 2013-2016 quadrennium. Conclusion: Medicine III understood the MP as a new technological scientific horizon within the strict sensu post-graduate and full consistency with the area.

Morocco MA: Prevalence of Undernourishment: % of Population data was reported at 3.500 % in 2015. This records a decrease from the previous number of 4.100 % for 2014. Morocco MA: Prevalence of Undernourishment: % of Population data is updated yearly, averaging 5.550 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 6.800 % in 2000 and a record low of 3.500 % in 2015. Morocco MA: Prevalence of Undernourishment: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Health Statistics. Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.; ; Food and Agriculture Organization (http://www.fao.org/publications/en/).; Weighted average;

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus version numbers of files within a dataset may not match.

Context

This dataset is originally from Dhaka Stock Exchange Ltd. The objective of the dataset is to assign analytical report writing tasks to Summer 2020 students enrolled in ASDS18: Data Mining course in proceedings of the partial fulfillment of the requirements for the Professional Masters in Applied Statistics and Data Science (PMASDS) degree. This data set was collected using the Dhaka Stock Exchange API.

Content

The datasets consist of several stock company predictor (independent) variables and one target (dependent) variable, Outcome. Independent variables include the last price, net asset value (NAV) of the stock, Earnings Per Share (EPS), price-to-earnings (P/E) ratio of the stock, paid-up capital per share, and so on.

It contains information on 374 listed companies from Dhaka Stock Exchange - DSE, Bangladesh. The outcome tested was Category, 258 tested positive and 500 tested negative. Therefore, there is one target (dependent) variable and 8 attributes.

Acknowledgements

Dr. Md. Rezaul Karim, Associate Professor, Department of Statistics, Jahangirnagar University, Dhaka, Bangladesh (2021) provided us with this dataset. Using the Dhaka Stock Exchange API this data set was collected to assign analytical report writing tasks to Summer 2020 students in proceedings of the partial fulfillment of the requirements for the Professional Masters in Applied Statistics and Data Science (PMASDS) degree.

DSE Listed Companies Database

Inspiration

Abstract

The General Household Survey (GHS) has been used as an instrument to track the progress of development since 2002 when it was first introduced . It is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

National

Analysis unit

Households

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus, version numbers of files within a dataset may not match.

In the academic year 2023/24, there were 331,602 international students from India studying in the United States. International students The majority of international students studying in the United States are originally from India and China, totaling 331,602 students and 277,398 students respectively in the 2023/24 school year. In 2022/23, there were 467,027 international graduate students , which accounted for over one third of the international students in the country. Typically, engineering and math & computer science programs were among the most common fields of study for these students. The United States is home to many world-renowned schools, most notably, the Ivy League Colleges which provide education that is sought after by both foreign and local students. International students and college Foreign students in the United States pay some of the highest fees in the United States, with an average of 24,914 U.S. dollars. American students attending a college in New England paid an average of 14,900 U.S. dollars for tuition alone and there were about 79,751 international students in Massachusetts . Among high-income families, U.S. students paid an average of 34,700 U.S. dollars for college, whereas the average for all U.S. families reached only 28,026 U.S. dollars. Typically, 40 percent of families paid for college tuition through parent income and savings, while 29 percent relied on grants and scholarships.

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Telephone Interview

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

Employment income (in 2019 and 2020) by detailed major field of study and highest certificate, diploma or degree, including work activity (full time full year, part time full year, or part year).

The Temporary Graduate visas lodged and granted reports are based on lodgement and grant data recorded for visa subclass 485 in the current financial year and previous financial years. \r \r The dimensions include the financial year and quarter of visa grant, gender, age and citizenship country. \r \r These de-identified statistics are periodically checked for privacy and other compliance requirements. The statistics were temporarily removed in March 2024 in response to a question about privacy within the emerging technological environment. Following a thorough review and risk assessment, the Department of Home Affairs has republished the dataset.\r \r

NUIG Post-graduate training survey in Galway Bay. Training Objectives * To deliver an accredited, offshore, blended learning, post-graduate module that will contribute towards student learning and research in order to fulfill academic requirements. * Provide students with the knowledge necessary to design, plan and execute an offshore scientific research survey. * Develop student understanding of how physical, chemical and biological marine processes shape the marine environment and influence the abundance and distribution of marine organisms. * Familiarize students with the applications of scientific sampling equipment and instrumentation on board a modern survey vessel. * Collect multidisciplinary data sets for analysis, quality control, interpretation, and integration. * Enable students to produce scientific survey reports integrating multiple data sets and analyses of collected samples. * Provide students with the basic knowledge necessary to carry out a cost-benefit analysis of a newly planned marine development scenario .hidden { display: none }

In 2025, the Masters of Business Administration domain had the highest employability rating among degree types in India at about ** percent, an increase from the previous year. The polytechnic domain had the lowest employability rate of around ** percent. What is employability? Employability refers to attributes that make an individual gain and maintain employment. This may include job-specific or soft skills. Higher employability is considered a precondition for achieving a higher employment rate. Although employability in India has increased to over ** percent from ** percent over a decade ago, there has remained a critical skill mismatch between education and skills. In other words, Indian graduates have been facing a disconnect between what is taught at colleges and what the industry demands. Enhancing employability through skill development Government initiatives like the National Skill Development Corporation and Pradhan Mantri Kaushal Vikas Yojana aim to promote skill development in India. Public-private partnerships (PPP) have also been instrumental in making skill development initiatives effective in India. For example, TCS has partnered with educational institutions to provide vocational training in digital literacy and soft skills. Other industry giants like Samsung and IBM are planning to launch special training programs in artificial intelligence (AI) and machine learning (ML) in collaboration with the National Skill Development Corporation (NSDC).

Morocco MA: SPI: Pillar 5 Data Infrastructure Score: Scale 0-100 data was reported at 50.000 NA in 2019. This records an increase from the previous number of 45.000 NA for 2018. Morocco MA: SPI: Pillar 5 Data Infrastructure Score: Scale 0-100 data is updated yearly, averaging 47.500 NA from Dec 2016 (Median) to 2019, with 4 observations. The data reached an all-time high of 50.000 NA in 2019 and a record low of 30.000 NA in 2016. Morocco MA: SPI: Pillar 5 Data Infrastructure Score: Scale 0-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank.WDI: Governance: Policy and Institutions. The data infrastructure pillar overall score measures the hard and soft infrastructure segments, itemizing essential cross cutting requirements for an effective statistical system. The segments are: (i) legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system; (ii) standards and methods addressing compliance with recognized frameworks and concepts; (iii) skills including level of skills within the statistical system and among users (statistical literacy); (iv) partnerships reflecting the need for the statistical system to be inclusive and coherent; and (v) finance mobilized both domestically and from donors.;Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators);Weighted average;

Introduction: In an age of increasingly face-to-face, blended, and online Health Professions Education, students have more selections of where they will receive a degree. For an applicant, oftentimes, the first step is to learn more about a program through its website. Websites allow programs to convey their unique voice and to share their mission and values with others, such as applicants, researchers, and academics. Additionally, as the number of Health Professions Education programs rapidly grows, websites can share the priorities of these programs. Methods: In this study, we conducted a website review of 158 Health Professions Education websites to explore their geographical distributions, missions, educational concentrations, and various programmatic components. Results: We compiled this information and synthesized pertinent aspects, such as program similarities and differences, or highlighted the omission of critical data. Conclusion: Given that websites are often the first point of contact for prospective applicants, curious collaborators, and potential faculty, the digital image of HPE programs matters. We believe our findings demonstrate opportunities for growth within institutions and assist the field in identifying the priorities of HPE programs. As programs begin to shape their websites with more intentionality, they can reflect their relative divergence/convergence compared to other programs as they see fit and, therefore, attract individuals to best match this identity. Periodic reviews of the breadth of programs, such as those undergone here, are necessary to capture diversifying goals, and serve to help advance the field of Health Professions Education as a whole. Methods Our team deduced that most HPE programs would have a website, and that this would serve as a representation of how individuals within the program choose to view themselves and hope to be viewed by others. Further, our team determined that these websites would be an efficient means of collecting programmatic information for the purposes of learning more about program growth, diversity, and values. We conducted the website review from August 2021 to April 2022 using a list of worldwide Health Professions Education programs, which was acquired from the Foundation of Advancement of International Medical Education and Research’s (FAIMER’s) website. FAIMER was chosen as the origin source of programs studied due to its use in another published study evaluating HPE programs. Each master's degree in HPE offered by a university was counted separately, allowing us to note the differences in course and time requirements across all programs. Only HPE master's programs were selected for this study. Certificate and Ph.D. programs were excluded. Next, we developed a data extraction tool. Categories were jointly identified for data collection by three of our authors (JS, SW, and HM). JS, SW, and HW worked independently through a set of three HPE programs, obtaining the data for our selected categories. Afterward, we cross-checked each other's work for verification purposes. For example, if JS obtained the information, SW or HM, who were blinded to JS’s findings, would independently find the answers to the same questions/ topics. This was performed until an agreement between pre and post-review information was above 95%. There was no discovered information that was not agreed upon after discussion. Once 100% agreement was reached with this method, the total number of HPE programs analyzed was split between JS and SW, and the raw data was obtained for the same categories. This data then underwent a review by the other two researchers to ensure high accuracy. This review consisted of information verification on individual program websites where it was originally obtained. For example, if JS found the information about a program, SW and HM (now not blinded) would both have to independently find the same information. Any identified discrepancies were rectified through discussion, and three-way agreement was mandatory for the team to move on to the next program.

Morocco MA: Imports: Lead Time: Documentary Compliance data was reported at 26.000 Hour in 2017. This stayed constant from the previous number of 26.000 Hour for 2016. Morocco MA: Imports: Lead Time: Documentary Compliance data is updated yearly, averaging 26.000 Hour from Dec 2014 (Median) to 2017, with 4 observations. The data reached an all-time high of 29.000 Hour in 2014 and a record low of 26.000 Hour in 2017. Morocco MA: Imports: Lead Time: Documentary Compliance data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Trade Statistics. Documentary compliance captures the time and cost associated with compliance with the documentary requirements of all government agencies of the origin economy, the destination economy and any transit economies. The aim is to measure the total burden of preparing the bundle of documents that will enable completion of the international trade for the product and partner pair assumed in the case study.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Time is measured in hours, and 1 day is 24 hours (for example, 22 days are recorded as 22 × 24 = 528 hours). If customs clearance takes 7.5 hours, the data are recorded as is. Alternatively, suppose that documents are submitted to a customs agency at 8:00 a.m., are processed overnight and can be picked up at 8:00 a.m. the next day. In this case the time for customs clearance would be recorded as 24 hours because the actual procedure took 24 hours. Data are presented for the survey year instead of publication year.

Morocco MA: Export: Cost: Documentary Compliance data was reported at 107.000 USD in 2017. This stayed constant from the previous number of 107.000 USD for 2016. Morocco MA: Export: Cost: Documentary Compliance data is updated yearly, averaging 107.000 USD from Dec 2014 (Median) to 2017, with 4 observations. The data reached an all-time high of 107.000 USD in 2017 and a record low of 107.000 USD in 2017. Morocco MA: Export: Cost: Documentary Compliance data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Trade Statistics. Documentary compliance captures the time and cost associated with compliance with the documentary requirements of all government agencies of the origin economy, the destination economy and any transit economies. The aim is to measure the total burden of preparing the bundle of documents that will enable completion of the international trade for the product and partner pair assumed in the case study.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Insurance cost and informal payments for which no receipt is issued are excluded from the costs recorded. Costs are reported in U.S. dollars. Contributors are asked to convert local currency into U.S. dollars based on the exchange rate prevailing on the day they answer the questionnaire. Contributors are private sector experts in international trade logistics and are informed about exchange rates and their movements. Data are presented for the survey year instead of publication year.