The statistic displays the most wanted data science skills in the United States as of **********. As of the measured period, ***** percent of data scientist job openings on LinkedIn required a knowledge of the programming language Python.

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 2021, Poland asserted its dominance in the digital ITO arena by ranking first in the Central and Eastern European region for data analytics and science services, scoring ****. Slovakia and Croatia followed.

MODIS Water Lake Powell Toy Dataset

  Dataset Summary

Tabular dataset comprised of MODIS surface reflectance bands along with calculated indices and a label (water/not-water)

  Dataset Structure





  Data Fields

water: Label, water or not-water (binary) sur_refl_b01_1: MODIS surface reflection band 1 (-100, 16000) sur_refl_b02_1: MODIS surface reflection band 2 (-100, 16000) sur_refl_b03_1: MODIS surface reflection band 3 (-100, 16000) sur_refl_b04_1: MODIS… See the full description on the dataset page: https://huggingface.co/datasets/nasa-cisto-data-science-group/modis-lake-powell-toy-dataset.

Data files for the examples in the book Geographic Data Science in R: Visualizing and Analyzing Environmental Change by Michael C. Wimberly.

In 2022, over ** thousand data science job positions were available in the BFSI sector in India. An increase in the availability of data science jobs was seen over the years from 2019. E-commerce and internet followed suite with roughly ** thousand jobs during the same time period.

Stack Exchange is a network of question-and-answer websites on topics in diverse fields, each site covering a specific topic, where questions, answers, and users are subject to a reputation award process. The reputation system allows the sites to be self-moderating.

The dataset here is specific to one such network site of Stack Exchange named Data Science Stack Exchange. The dataset is distributed over multiple files. It contains information on various Posts on data science that can be used for language processing, it has data on which posts are being liked by users more, etc. A lot of analysis can be done on this dataset.

Data Science Notebook Platforms for Classes Market Outlook

According to our latest research, the global Data Science Notebook Platforms for Classes market size reached USD 1.42 billion in 2024, with a robust year-on-year growth driven by increasing digital transformation in education and corporate learning. The market is anticipated to expand at a compound annual growth rate (CAGR) of 18.7% from 2025 to 2033, reaching a projected value of USD 6.92 billion by 2033. This notable growth is fueled by the rising adoption of cloud-based educational tools, the integration of artificial intelligence in learning platforms, and a growing emphasis on data-driven decision-making skills across all levels of education and corporate training.

One of the primary growth drivers for the Data Science Notebook Platforms for Classes market is the increasing demand for interactive and collaborative learning environments. As educational institutions and corporations worldwide recognize the importance of data literacy, these platforms are being adopted to facilitate hands-on learning experiences. The ability to code, visualize data, and collaborate in real-time is transforming traditional classrooms and training sessions, making them more engaging and effective. Moreover, the integration of advanced analytics and machine learning modules within these platforms empowers learners to tackle real-world problems, thereby enhancing their employability and practical skillsets. This shift is particularly pronounced in higher education and professional development, where experiential learning is highly valued.

Another significant factor propelling the growth of the Data Science Notebook Platforms for Classes market is the widespread adoption of cloud technology. Cloud-based notebook platforms offer unparalleled scalability, accessibility, and cost-effectiveness, making them an attractive choice for both small educational institutions and large enterprises. The cloud model eliminates the need for complex on-premises infrastructure, reduces IT maintenance costs, and enables seamless updates and integration with other educational tools. Additionally, the flexibility of cloud-based solutions allows students and professionals to access learning resources from any location, fostering a more inclusive and adaptive learning environment. This trend has been accelerated by the global shift to remote and hybrid learning models, especially in the aftermath of the COVID-19 pandemic.

The market is also witnessing substantial growth due to the increasing role of EdTech companies and the proliferation of online courses. EdTech firms are leveraging data science notebook platforms to deliver customized and scalable learning experiences, catering to diverse learner needs across geographies. These platforms are being integrated with learning management systems (LMS), enabling seamless tracking of student progress and personalized feedback. Furthermore, the corporate sector is embracing these platforms for upskilling and reskilling initiatives, recognizing the critical importance of data-driven decision-making in today’s competitive landscape. As organizations invest in workforce development, the demand for advanced, interactive, and analytics-driven training solutions is expected to surge, further boosting market growth.

Regionally, North America continues to dominate the Data Science Notebook Platforms for Classes market, accounting for the largest revenue share in 2024, primarily due to the presence of leading technology providers, high digital literacy rates, and substantial investments in educational technology. However, the Asia Pacific region is emerging as the fastest-growing market, driven by rapid digitalization, government initiatives to modernize education, and a burgeoning EdTech ecosystem. Europe also holds a significant share, with increasing adoption of data science curricula in both academic and corporate settings. Latin America and the Middle East & Africa are gradually catching up, supported by rising internet penetration and the growing popularity of online learning. The global outlook remains highly positive, with all regions expected to contribute to sustained market expansion over the forecast period.

Product Type Analysis

The Product Type segment of the Data Science Notebook Platforms for Classes market is primarily divided into Cloud-Based and On-Premises solutions. C

DeepAnalyze: Agentic Large Language Models for Autonomous Data Science

Authors: Shaolei Zhang, Ju Fan*, Meihao Fan, Guoliang Li, Xiaoyong Du

DeepAnalyze is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data-centric tasks without human intervention, supporting: 🛠 Entire data science pipeline: Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation. 🔍… See the full description on the dataset page: https://huggingface.co/datasets/RUC-DataLab/DataScience-Instruct-500K.

This blog post was posted on October 8, 2015 and was written by Robbie Barbero and Noemie Levy. This is a cross-post from the White House blog.

Dataset

This dataset was created by A. Richardson

Contents

Space Data Analytics Market Outlook

The global space data analytics market size was valued at approximately $3.2 billion in 2023 and is projected to reach around $11.8 billion by 2032, reflecting a robust CAGR of 15.6% over the forecast period. Driven by the increasing deployment of satellites and growing advancements in machine learning and data analytics technologies, the market is poised for substantial growth. The convergence of these technologies allows for more efficient data collection, processing, and utilization, which fuels the demand for space data analytics across various sectors.

The primary growth factor for the space data analytics market is the exponential increase in satellite deployments. Governments and private entities are launching satellites for diverse purposes such as communication, navigation, earth observation, and scientific research. This surge in satellite launches generates vast amounts of data that require sophisticated analytical tools to process and interpret. Consequently, the need for advanced analytics solutions to convert raw satellite data into actionable insights is driving the market forward. Additionally, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the capabilities of space data analytics, making them more accurate and efficient.

Another significant growth driver is the escalating demand for real-time data and analytics in various industries. Sectors such as agriculture, defense, and environmental monitoring increasingly rely on satellite data for applications like precision farming, border surveillance, and climate change assessment. The ability to obtain real-time data from satellites and analyze it promptly allows organizations to make informed decisions swiftly, thereby improving operational efficiency and outcomes. Furthermore, the growing awareness about the advantages of space data analytics in proactive decision-making is expanding its adoption across multiple sectors.

Moreover, international collaborations and government initiatives aimed at space exploration and satellite launches are propelling the market. Many countries are investing heavily in space missions and satellite projects, creating a fertile ground for the space data analytics market to thrive. These investments are accompanied by supportive regulatory frameworks and funding for research and development, further encouraging innovation and growth in the sector. Additionally, the commercialization of space activities and the emergence of private space enterprises are opening new avenues for market expansion.

Artificial Intelligence in Space is revolutionizing the way we approach space exploration and data analysis. By integrating AI technologies with space missions, scientists and researchers can process vast amounts of data more efficiently and accurately. This integration allows for real-time decision-making and predictive analytics, which are crucial for successful space missions. AI's ability to learn and adapt makes it an invaluable tool for navigating the complex and unpredictable environment of space. As AI continues to evolve, its applications in space exploration are expected to expand, offering new possibilities for understanding our universe and enhancing the capabilities of space data analytics.

From a regional perspective, North America holds the largest market share due to the presence of leading space agencies, like NASA, and prominent private space companies, such as SpaceX and Blue Origin. Europe follows closely, driven by robust investments in space research and development by the European Space Agency (ESA). The Asia Pacific region is expected to witness the fastest growth rate, attributed to increasing satellite launches by countries like China and India, alongside growing investments in space technology and analytics within the region.

Component Analysis

The space data analytics market can be segmented by component into software, hardware, and services. The software segment commands a significant share of the market due to the development of sophisticated analytics tools and platforms. These software solutions are crucial for processing and interpreting the vast amounts of data collected from satellites. Advanced algorithms and AI-powered analytics enable users to extract meaningful insights from raw data, driving the adoption of these solutions across various sectors. The continuous innovation in software capabilities, such as enhanced visualization t

Dataset

This dataset was created by sita berete

Released under MIT

Contents

The statistic shows the analytics tools currently in use by business organizations in the United States, as well as the analytics tools respondents believe they will be using in two years, according to a 2015 survey conducted by the Harvard Business Review Analytics Service. As of 2015, ** percent of respondents believed they were going to use predictive analytics for data analysis in two years' time.

The global market for data lens (visualizations of data) is experiencing robust growth, driven by the increasing adoption of data analytics across diverse industries. This market, estimated at $50 billion in 2025, is projected to achieve a compound annual growth rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the rising volume and complexity of data necessitate effective visualization tools for insightful analysis. Businesses are increasingly relying on interactive dashboards and data storytelling techniques to derive actionable intelligence from their data, fostering the demand for sophisticated data visualization solutions. Secondly, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the capabilities of data visualization platforms, enabling automated insights generation and predictive analytics. This creates new opportunities for vendors to offer more advanced and user-friendly tools. Finally, the growing adoption of cloud-based solutions is further accelerating market growth, offering enhanced scalability, accessibility, and cost-effectiveness. The market is segmented across various types, including points, lines, and bars, and applications, ranging from exploratory data analysis and interactive data visualization to descriptive statistics and advanced data science techniques. Major players like Tableau, Sisense, and Microsoft dominate the market, constantly innovating to meet evolving customer needs and competitive pressures. The geographical distribution of the market reveals strong growth across North America and Europe, driven by early adoption and technological advancements. However, emerging markets in Asia-Pacific and the Middle East & Africa are showing significant growth potential, fueled by increasing digitalization and investment in data analytics infrastructure. Restraints to growth include the high cost of implementation, the need for skilled professionals to effectively utilize these tools, and security concerns related to data privacy. Nonetheless, the overall market outlook remains positive, with continued expansion anticipated throughout the forecast period due to the fundamental importance of data visualization in informed decision-making across all sectors.

Dataset

This dataset was created by Talha Ashfaq

Released under Other (specified in description)

Contents

Data Science Platform Market is projected to grow at a CAGR of around 27% during the forecast period, i.e., 2022-27 says MarkNtel.

Dataset

This dataset was created by Chelsi

Released under Apache 2.0

Contents