In 2023, the most common advice offered by alumni of online higher education programs in the United States, suggested by ** percent of alumni, was to do more research about cost and financial aid. A further ** percent of alumni of online programs said to compare more programs when researching schools.

Online and Distance Education at Postsecondary Institutions, 2006-07 (PEQIS 16), is a study that is part of the Postsecondary Education Quick Information System (PEQIS) program; program data is available since 1997 at . PEQIS 16 (https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2009044) is a survey that collects data on the prevalence and delivery of distance education courses in the 2006-07 12-month academic year, including the number of courses and enrollment for online courses, hybrid/blended online courses, and all other distance education courses. The survey also collects information about numbers of degree or certificate programs designed to be completed entirely through distance education and the technologies used for the instructional delivery of credit-granting distance education courses. The study was conducted using paper and web surveys. The weighted response rate was 87 percent. Postsecondary institutions were sample for this study. Key statistics produced from PEQIS 16 relate to information on the prevalence, types, delivery, policies, and acquisition or development of distance education courses and programs.

Like other sub-sectors in the education app market, skills and online training courses experienced significant growth at the beginning of the coronavirus pandemic, as many people lost jobs or were...

In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, 10 years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report, 2005, and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lecture-intensive course. In this article, we discuss various instructional approaches, activities, and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn’t require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. Supplementary materials, including code used to generate class plots and activity handouts, are available online. Received December 2014. Revised June 2015.

The online higher education market is experiencing robust growth, fueled by increasing accessibility, affordability demands, and technological advancements. The market's Compound Annual Growth Rate (CAGR) of 19.82% from 2019 to 2024 suggests a significant expansion, likely driven by factors such as the rising adoption of online learning platforms, flexible learning options catering to working professionals and geographically dispersed students, and the increasing recognition of online degrees by employers. The market segmentation, encompassing diverse types of online programs (e.g., bachelor's, master's, certificate programs) and applications across various fields (e.g., business, technology, healthcare), contributes to its broad appeal and expansion. Major players like American Public Education, Adtalem Global Education, and others are deploying competitive strategies focused on enhancing the learning experience, improving student support services, and expanding their program offerings to maintain a competitive edge. The geographic distribution indicates strong growth across North America and Asia-Pacific, driven by higher internet penetration and a growing young population seeking educational opportunities. However, challenges remain, including concerns about the perceived quality of online education compared to traditional institutions, the digital divide limiting access for certain demographics, and the need for continuous investment in technology and curriculum development to meet evolving learner needs. Looking ahead to 2033, the online higher education market is projected to maintain significant momentum, further expanding its reach and influence. Continued technological innovation, including advancements in virtual reality and artificial intelligence, will enhance the learning experience and attract a broader range of students. The growing importance of lifelong learning and upskilling will also drive demand for online courses and degree programs. Competitive pressures will likely lead to further innovation in pricing models, program offerings, and marketing strategies, fostering a dynamic and evolving market landscape. To fully capitalize on this growth, educational institutions must prioritize creating engaging and effective online learning environments, addressing concerns around quality and accessibility, and adapting to the ever-changing needs of students in a globally competitive market.

This statistic shows the program outcome data for online education providers that were the most requested by students in the United States in 2016. In 2016, ** percent of schools reported that students asked for placement and employment rates.

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Online Data Science Training Programs Market Size 2025-2029

The online data science training programs market size is forecast to increase by USD 8.67 billion, at a CAGR of 35.8% between 2024 and 2029.

The market is experiencing significant growth due to the increasing demand for data science professionals in various industries. The job market offers lucrative opportunities for individuals with data science skills, making online training programs an attractive option for those seeking to upskill or reskill. Another key driver in the market is the adoption of microlearning and gamification techniques in data science training. These approaches make learning more engaging and accessible, allowing individuals to acquire new skills at their own pace. Furthermore, the availability of open-source learning materials has democratized access to data science education, enabling a larger pool of learners to enter the field. However, the market also faces challenges, including the need for continuous updates to keep up with the rapidly evolving data science landscape and the lack of standardization in online training programs, which can make it difficult for employers to assess the quality of graduates. Companies seeking to capitalize on market opportunities should focus on offering up-to-date, high-quality training programs that incorporate microlearning and gamification techniques, while also addressing the challenges of continuous updates and standardization. By doing so, they can differentiate themselves in a competitive market and meet the evolving needs of learners and employers alike.

What will be the Size of the Online Data Science Training Programs Market during the forecast period?

Request Free SampleThe online data science training market continues to evolve, driven by the increasing demand for data-driven insights and innovations across various sectors. Data science applications, from computer vision and deep learning to natural language processing and predictive analytics, are revolutionizing industries and transforming business operations. Industry case studies showcase the impact of data science in action, with big data and machine learning driving advancements in healthcare, finance, and retail. Virtual labs enable learners to gain hands-on experience, while data scientist salaries remain competitive and attractive. Cloud computing and data science platforms facilitate interactive learning and collaborative research, fostering a vibrant data science community. Data privacy and security concerns are addressed through advanced data governance and ethical frameworks. Data science libraries, such as TensorFlow and Scikit-Learn, streamline the development process, while data storytelling tools help communicate complex insights effectively. Data mining and predictive analytics enable organizations to uncover hidden trends and patterns, driving innovation and growth. The future of data science is bright, with ongoing research and development in areas like data ethics, data governance, and artificial intelligence. Data science conferences and education programs provide opportunities for professionals to expand their knowledge and expertise, ensuring they remain at the forefront of this dynamic field.

How is this Online Data Science Training Programs Industry segmented?

The online data science training programs industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeProfessional degree coursesCertification coursesApplicationStudentsWorking professionalsLanguageR programmingPythonBig MLSASOthersMethodLive streamingRecordedProgram TypeBootcampsCertificatesDegree ProgramsGeographyNorth AmericaUSMexicoEuropeFranceGermanyItalyUKMiddle East and AfricaUAEAPACAustraliaChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

By Type Insights

The professional degree courses segment is estimated to witness significant growth during the forecast period.The market encompasses various segments catering to diverse learning needs. The professional degree course segment holds a significant position, offering comprehensive and in-depth training in data science. This segment's curriculum covers essential aspects such as statistical analysis, machine learning, data visualization, and data engineering. Delivered by industry professionals and academic experts, these courses ensure a high-quality education experience. Interactive learning environments, including live lectures, webinars, and group discussions, foster a collaborative and engaging experience. Data science applications, including deep learning, computer vision, and natural language processing, are integral to the market's growth. Data analysis, a crucial application, is gaining traction due to the increasing demand for data-driven decisio

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).

As of June 2024, around ******* students were enrolled at an online bachelor's program in Italy. In addition, ****** individuals chose e-learning for their master's studies. Among the largest Italian universities, the Pegaso online University ranks at the second place, nationwide. In the academic year 2023/2024, the e-learning institute had more than ****** enrolled students.

During a survey conducted in Spring 2023 in the United States, the most popular factor for choosing online education was the affordability of the program, with ** percent of respondents reporting this as one of their top three reasons. The second most popular factor was the reputation of the school or program.

In 2024, around ** percent of internet users surveyed in Brazil said they had used the internet to do online courses. It is the third highest value registered so far, only down from ** percent in 2021 and ** percent in 2023. Online study and education is one of the main reasons for **** percent of internet users in Brazil to access web, thus being one of the most popular video content types consumed in the country.

Career and Technical Education Programs in Public School Districts, 2016-17 (FRSS 108) is a data collection that is part of the Fast Response Survey System (FRSS) program; program data are available since 1998-99 at . FRSS 108 (https://nces.ed.gov/surveys/frss/index.asp) is a cross-sectional data collection that provides nationally representative data on career and technical education (CTE) programs. Public local education agencies (LEAs) instructing either grades 11 or 12 in the 50 United States and the District of Columbia were sampled. The study was conducted using mailed questionnaires that could be completed on paper or online. The data collection's response rate was 86 percent. Key statistics produced from FRSS 108 include data on the entities that provide the CTE programs, the locations at which the CTE programs are offered, work-based learning activities and employer involvement in CTE programs, barriers to the district offering CTE programs, barriers to student participation in CTE programs, and the extent to which various factors influence the district's decisions on whether to add or phase out CTE programs.

Online college courses are a rapidly expanding feature of higher education, yet little research identifies their effects relative to traditional in-person classes. Using an instrumental variables approach, we find that taking a course online, instead of in-person, reduces student success and progress in college. Grades are lower both for the course taken online and in future courses. Students are less likely to remain enrolled at the university. These estimates are local average treatment effects for students with access to both online and in-person options; for other students, online classes may be the only option for accessing college-level courses.

The online data science training programs market is experiencing explosive growth, projected to reach $1.90 billion in 2025 and exhibiting a robust Compound Annual Growth Rate (CAGR) of 34.73% from 2025 to 2033. This surge is driven by the escalating demand for data scientists across various industries, coupled with the accessibility and flexibility offered by online learning platforms. The increasing availability of high-quality online courses, encompassing both professional degree programs and specialized certifications, caters to a diverse learner base, ranging from career changers to experienced professionals seeking upskilling. North America, particularly the U.S. and Canada, currently holds a significant market share, fueled by a strong technological ecosystem and high adoption rates. However, the Asia-Pacific region (APAC), especially China and India, is poised for substantial growth, driven by a burgeoning tech sector and a large pool of young professionals. The market is highly competitive, with established players like Coursera, Udacity, and Udemy competing with specialized platforms like DataCamp and AnalytixLabs, as well as traditional universities offering online programs. This competitive landscape fosters innovation and ensures a diverse range of courses and pricing models, further contributing to market expansion. Continued growth is anticipated due to several factors. The increasing integration of data science into various sectors, from finance and healthcare to marketing and e-commerce, continuously necessitates skilled professionals. Furthermore, the ongoing advancements in artificial intelligence (AI) and machine learning (ML) are expanding the scope of data science applications, thereby increasing the demand for training programs that address these emerging technologies. While the market faces certain challenges, such as ensuring the quality and relevance of online courses and addressing the digital divide, the overall trajectory indicates a sustained period of growth, promising significant opportunities for both established and emerging players in the online data science education sector.

In this article, we consider how to make data more meaningful to students through the choice of data and the activities we use them in drawing upon students lived experiences more in the teaching of statistics and data science courses. In translating scholarship around culturally relevant pedagogy from the fields of education and mathematics education we develop the idea of culturally relevant data. We see this development as a key ingredient to implementing culturally relevant pedagogy in teaching data-intensive courses leveraging the centrality of context through data in both statistics and data science to engage students particularly from historically marginalized groups in STEM. We provide suggestions as to ways of finding or creating culturally relevant data and using them in implementing culturally relevant pedagogy to support the learning and flourishing of students in statistics and data science courses. We also present findings from pilot work we have done in implementing these data in statistics courses. Finally, we discuss lingering questions and possible next steps for research in this area. Supplementary materials for this article are available online.

Programs and Services for High School English Learners, 2015-16 (FRSS 107) is a study that is part of the Fast Response Survey System (FRSS) program; program data is available since 1998-99 at . FRSS 107 (https://nces.ed.gov/surveys/frss/index.asp) is a study that provides nationally representative data on programs and services for high-school English learners (Els), including instructional approaches, newcomer programs, online or computer-based programs, and programs or services (e.g., tutoring) designed specifically for high school Els. The study was conducted using mailed questionnaires that could be completed on paper or online. Public local education agencies (LEAs) instructing either of Grades 11 or 12 in the 50 United States and the District of Columbia were sampled. The study's weighted response rate was 89 percent. Key statistics produced from FRSS 107 include data on the use of native language(s) for content instruction, instructional support, materials, and services; information that LEAs provide about educational programs or services to Els aged 18 to 21 years-old seeking to newly enroll in the LEA; and factors LEAs consider when providing information about these programs and services to Els in this group.

In 2024, about **** percent of all students who chose online degree programs in the United States said they did so because COVID-19 made it the only option available to them, a slight decrease from ** percent in the previous year. In both 2023 and 2024, however, the most commonly cited reason for students to choose online degree programs was due to existing commitments, such as work and family, preventing their attendance in campus-based courses.

Introduction

E-Learning Statistics: In today’s fast-moving digital world, e-learning has become a key tool for businesses and people who want to keep improving and growing. E-learning is convenient, easy to access, and flexible, making it a game-changer for traditional education. It’s now an essential resource for staying competitive and adaptable in various industries.

Before the global COVID-19 pandemic, online learning was already starting to show up in schools, from elementary through university, as well as in corporate training. Both students and teachers liked the flexibility it offered to everyone taking part in the lessons.

Don't worry; we've put together a list of important E-Learning Statistics for 2024, bringing together the most useful insights in one handy place.

Background: The concept of health has undergone profound changes. Lifestyle Medicine (LSM) consists of therapeutic approaches that focus on the prevention and treatment of diseases. It follows that the quality of life of university students directly affects their health and educational progress. Experimental Methodology: Socioeconomic, lifestyle (LS), and sense of coherence (SOC) questionnaires were administered to college students from three different areas. The results were analyzed for normality and homogeneity, followed by ANOVA variance analysis and Dunn and Tukey post hoc test for multiple comparisons. Spearman's correlation coefficient evaluated the correlation between lifestyle and sense of coherence; p values < 0.05 were considered statistically significant. Results: The correlation between LS and SOC was higher among males and higher among Medical and Human sciences students compared to Exact sciences. Medical students' scores were higher than Applied sciences and Human sciences students on the LS questionnaire. Exact science students' scores on the SOC questionnaire were higher than Human sciences students. In the LS areas related to alcohol intake, sleeping quality, and behavior, there were no differences between the areas. However, women scored better in the nutrition domain and alcohol intake. The SOC was also higher in men compared to women. Conclusion: The results obtained demonstrate in an unprecedented way in the literature that the correlation between the LS and SOC of college students varies according to gender and areas of knowledge, reflecting the importance of actions on improving students' quality of life and enabling better academic performance. Methods Data gathering The researchers invited the students to answer an online form - through Google Forms virtual platform - containing the questionnaires: sociodemographic information, FANTASTIC questionnaire on Lifestyle, and a questionnaire on Sense of Coherence. The researchers clearly explained the research objectives and collection procedures on the home page, and the participants were given the Free and Informed Consent Form. The data gathered in the online form were transferred to a spreadsheet in Microsoft Excel. The results were filtered, classified, and treated in order to be in line with the desired statistical analysis and could feed the statistical programs used. Statistical analysis The statistical analyses were performed by the JASP statistical software, and part of the graphics by the SPSS software. First, the researchers submitted the results to normality (Shapiro Wilk) and homogeneity (Levene test) analysis. Next, the normal homogeneous data were submitted to the ANOVA analysis of variance and Kruskal Wallis non-parametric test, followed by Dunn's post hoc test of multiple comparisons and Tukey's correction. Spearman's correlation coefficient evaluated the correlation between Lifestyle and Sense of Coherence by determining the value of R. Values of p < 0.05 were considered statistically significant. The normality of data was checked by the Shapiro-Wilk test, and since the distribution was not normal, analyses were performed as described below:

Descriptive results are presented by the median and interquartile ranges.

The comparisons between the study variables in HA, ESA and HM (age, BMI, lifestyle, sense of coherence and domains of the questionnaires) and by gender (Lifestyle and Sense of Coherence) were performed by the Mann-Whitney test.

The domains of the questionnaires in each group (HA, ESA, and HM) were compared by analyzing repeated measures, Friedman test, and the Post Hoc by Dunn's multiple comparisons test.

The comparisons between lifestyle and Sense of Coherence among students in each of the selected courses were performed by analysis of variance, Kruskal-Wallis non-parametric test and Post Hoc by Dunn's multiple comparisons test.

The correlations between the profile of lifestyle and sense of coherence of students in each area of knowledge and by gender were performed by Spearman's correlation coefficient.

The significance index adopted in all analyses was 5% (p ≤ 0.05).