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市場調查報告書
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2093023

資料科學教育市場預測至2034年—按學習形式、課程類型、交付模式、最終用戶和地區分類的全球分析

Data Science Education Market Forecasts to 2034 - Global Analysis By Learning Mode, Course Type, Delivery Model, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球資料科學教育市場規模將達到 80 億美元，並在預測期內以 15.8% 的複合年成長率成長，到 2034 年將達到 260 億美元。

資料科學教育涵蓋旨在教授數據分析、機器學習、人工智慧、統計學、程式設計及相關技能的培訓項目、課程和資源。該市場包括自學平台、講師主導的培訓計畫、大學學位課程、訓練營以及學生、在職人員、企業和政府機構的企業培訓解決方案。各行業對數據驅動決策的需求日益成長、人工智慧和分析技術的廣泛應用以及全球熟練數據專業人員的短缺是推動市場成長的主要因素。

各行各業對資料科學技能的需求都在成長。

各行業的快速數字化轉型以及對數據驅動決策日益成長的依賴，是資料科學教育市場發展的關鍵促進因素。金融、醫療保健、零售、製造和科技等行業的企業都急需具備數據分析、機器學習和人工智慧技能的專業人才。全球範圍內合格的資料科學家和分析師短缺，顯著提升了對相關教育和培訓課程的需求。隨著數據在商業策略和營運中扮演越來越重要的角色，各行各業對資料科學教育的需求持續成長。這種對專業人才的持續需求，正在推動對學術計畫和職業培訓的投資。

高品質教育課程高成本且取得難度高。

資料科學教育的高昂成本和有限的資源取得途徑是限制市場成長的主要阻礙因素。全面的資料科學課程，尤其是大學學位課程和密集訓練營，需要大量資金，這對許多學習者來說都是一道障礙。優質教育的取得在地域上並不均衡，已開發國家擁有較多的課程和資源。數位落差影響著服務低度開發地區線上學習的普及。為了保持課程的時效性，需要不斷更新，這給教育工作者帶來了沉重的負擔。這些成本和獲取障礙限制了市場覆蓋率和參與度，尤其對來自弱勢背景的人群而言更是如此。

生成式人工智慧與實踐學習平台的融合

生成式人工智慧技術的快速發展為資料科學教育市場的拓展帶來了巨大機會。人工智慧驅動的學習平台能夠提供個人化指導、即時回饋以及根據個人需求量身定做的自適應學習路徑。生成式人工智慧能夠創建逼真的資料集，用於實踐操作和企劃為基礎學習。虛擬實驗室和雲端環境無需昂貴的基礎架構即可提供實務經驗。整合人工智慧助理的互動式平台使資料科學對初學者更加友善。隨著人工智慧能力的提升以及越來越多的機構認知到實踐學習的價值，對整合人工智慧的資料科學教育的需求正在加速成長。

快速發展的技術和過時的課程

資料科學和人工智慧領域技術的快速發展對教育計畫構成了重大威脅。工具、框架和調查方法都在快速演進，需要不斷更新課程內容以保持其時效性。教育機構難以跟上行業趨勢，這可能導致畢業生的技能過時。包括生成式人工智慧在內的新興技術，有可能從根本上改變資料科學的工作流程和所需技能。如何在課程設計中平衡基礎與最新工具是一項極具挑戰性的任務。這種快速發展可能會抑制教育投資，並影響人們對課程價值的認知。

新型冠狀病毒（COVID-19）的影響：

新冠感染疾病顯著加速了資料科學教育的普及。遠距辦公和數位營運的興起，提升了各行業對數據分析技能的需求。疫情封鎖導致校園和培訓機構關閉，進而引發了線上學習的激增。虛擬協作和雲端工具的運用，使得教育得以持續進行。疫情凸顯了數據驅動決策在危機應變和業務韌性方面的重要性。隨著各組織加速數位轉型，對資料科學技能的需求持續成長。疫情結束後，混合式和線上學習模式成為常態，人們對資料科學教育的興趣也始終不減。此次危機也充分展現了線上學習的有效性和便利性。

在預測期內，「自主學習」細分市場預計將佔據最大的市場佔有率。

在預測期內，「自主學習」預計將佔據最大的市場佔有率。這主要得益於其相比結構化課程的柔軟性、可及性和經濟性優勢。自主學習讓個人可以按照自己的步調學習，從而適應不同的時間安排和學習風格。線上平台提供豐富的課程庫，涵蓋從入門到進階的各種資料科學。訂閱和按課程付費的定價模式使學習惠及更廣泛的受眾。尤其對於希望在職涯發展的同時提陞技能的在職人士而言，自主學習尤其重要。隨著終身學習變得日益重要，以及線上平台的不斷擴展，自主學習將繼續保持其最大的市場佔有率。

在預測期內，「目前在職專業人士」細分市場預計將呈現最高的複合年成長率。

在預測期內，「職場專業人士」群體預計將呈現最高的成長率，這主要得益於數據驅動型產業對技能提升和再培訓需求的不斷成長。職場專業人士尋求資料科學技能，以促進職業發展、保障工作安全並轉型至更技術性的角色。雇主對所有職位的數據素養要求也日益提高。數位轉型的加速凸顯了數據技能的缺口。短期靈活的課程，例如線上課程、訓練營和非全日制學位課程，使職場人士能夠在不中斷職業生涯的情況下提陞技能。隨著企業將數據能力置於優先地位，作為最終用戶的職場專業人士數量成長最為迅速。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於對資料科學技能的強勁需求、完善的教育基礎設施以及企業在培訓方面的大量投入。美國擁有眾多頂尖大學、訓練營和線上平台，提供資料科學教育。蓬勃發展的科技業和數據驅動型商業實踐的廣泛應用正在推動巨大的市場需求。各行業的企業培訓和職業發展項目都已相當完善。政府推行的STEM教育措施也為市場成長提供了支持。強大的教育基礎設施和持續的需求確保北美能夠保持其市場主導地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於數位轉型、龐大的學生和專業人士群體以及政府在技術教育領域的舉措。印度、中國、新加坡和澳洲等國家在學術界和專業領域對資料科學教育的需求日益成長。該地區大規模的IT從業人員和不斷發展的數位經濟正在創造巨大的市場潛力。政府為促進數位技能發展的措施也為市場擴張提供了支持。隨著該地區各組織機構採用數據驅動型策略，對資料科學教育的需求正在加速成長。憑藉龐大的人口基數和技術進步，亞太地區正經歷著全球最快的市場成長。

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    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球資料科學教育市場：依學習模式分類

  • 課堂學習
  • 線上學習
  • 混合式學習

第6章：全球資料科學教育市場：依課程類型分類

  • 證書課程
  • 文憑課程
  • 大學部課程
  • 研究生課程
  • 企業培訓
  • 訓練營

第7章：全球資料科學教育市場：依交付模式分類

  • 自主學習
  • 講師主導培訓

第8章：全球資料科學教育市場：以最終用戶分類

  • 學生
  • 社會活躍成員
  • 公司
  • 政府機構

第9章：全球資料科學教育市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第10章 戰略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第11章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第12章：公司簡介

  • Coursera, Inc.
  • Udacity, Inc.
  • Udemy, Inc.
  • edX LLC
  • Simplilearn Solutions Pvt. Ltd.
  • DataCamp, Inc.
  • Great Learning Education Services Private Limited
  • upGrad Education Private Limited
  • Pluralsight, LLC
  • LinkedIn Corporation
  • Skillsoft Corporation
  • Springboard, Inc.
  • Scaler Academy
  • NIIT Limited
  • Emeritus Institute of Management Pte. Ltd.
  • General Assembly Space, Inc.
  • 365 Data Science Ltd.
  • Codecademy LLC
Product Code: SMRC38193

According to Stratistics MRC, the Global Data Science Education Market is accounted for $8.0 billion in 2026 and is expected to reach $26.0 billion by 2034 growing at a CAGR of 15.8% during the forecast period. Data science education encompasses training programs, courses, and resources designed to teach data analysis, machine learning, artificial intelligence, statistics, programming, and related skills. This market includes self-paced learning platforms, instructor-led training programs, university degrees, bootcamps, and corporate training solutions serving students, working professionals, enterprises, and government organizations. Growing demand for data-driven decision-making across industries, increasing adoption of AI and analytics, and the global shortage of skilled data professionals are key drivers of market expansion.

Market Dynamics:

Driver:

Growing demand for data science skills across all industries

The rapid digital transformation across industries and the increasing reliance on data-driven decision-making are primary drivers for the data science education market. Organizations across finance, healthcare, retail, manufacturing, and technology sectors require professionals with data analysis, machine learning, and AI skills. The global shortage of qualified data scientists and analysts is creating significant demand for education and training programs. As data becomes increasingly central to business strategy and operations, demand for data science education continues growing across all industry verticals. This sustained demand for skilled professionals is driving investment in both academic programs and professional training.

Restraint:

High cost and accessibility of quality education programs

The significant costs associated with data science education and limited accessibility represent major restraints for market growth. Comprehensive data science programs, particularly university degrees and intensive bootcamps, require substantial financial investment that may be prohibitive for many learners. Access to quality education is uneven across regions, with developed countries offering more programs and resources. The digital divide affects access to online learning in underserved regions. Maintaining curriculum relevance requires continuous updates, straining educational providers. These cost and accessibility barriers limit market reach and participation, particularly among individuals from disadvantaged backgrounds.

Opportunity:

Integration of generative AI and hands-on learning platforms

The rapid advancement of generative AI technologies presents significant opportunities for data science education market expansion. AI-powered learning platforms can provide personalized instruction, real-time feedback, and adaptive learning paths tailored to individual needs. Generative AI enables creation of realistic datasets for practice and project-based learning. Virtual labs and cloud-based environments provide hands-on experience without expensive infrastructure. Interactive platforms incorporating AI assistance are making data science more accessible to beginners. As AI capabilities advance and more organizations recognize the value of hands-on learning, demand for AI-integrated data science education accelerates.

Threat:

Rapidly evolving technology and curriculum obsolescence

The extremely rapid pace of technological change in data science and AI poses significant threats to educational programs. Tools, frameworks, and methodologies evolve quickly, requiring continuous curriculum updates to remain relevant. Educational providers may struggle to keep pace with industry developments, leading to graduates with outdated skills. The emergence of new technologies including generative AI may fundamentally change data science workflows and required skillsets. Balancing foundational knowledge with current tools is challenging for program design. This rapid evolution may discourage educational investment and affect perceived program value.

Covid-19 Impact:

The COVID-19 pandemic significantly accelerated data science education adoption. The shift to remote work and digital operations increased demand for data analytics skills across industries. Online learning adoption surged as lockdowns closed campuses and training facilities. Virtual collaboration and cloud-based tools enabled continued instruction. The pandemic highlighted the importance of data-driven decision-making for crisis response and business resilience. Demand for data science skills continued growing as organizations accelerated digital transformation. Post-pandemic, hybrid and online learning models have become standard, with sustained interest in data science education. The crisis also demonstrated the effectiveness and accessibility of online learning.

The Self-Paced Learning segment is expected to be the largest during the forecast period

The Self-Paced Learning segment is expected to account for the largest market share during the forecast period, driven by flexibility, accessibility, and affordability advantages over structured programs. Self-paced learning enables individuals to study at their own speed, accommodating diverse schedules and learning styles. Online platforms offer extensive course libraries covering data science topics at various levels, from beginner to advanced. Subscription and per-course pricing models make learning accessible to a broad audience. Working professionals seeking skill enhancement while maintaining employment particularly benefit. As lifelong learning becomes essential and online platforms expand, self-paced learning maintains the largest market share.

The Working Professionals segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the Working Professionals segment is predicted to witness the highest growth rate, fueled by the increasing need for upskilling and reskilling in data-driven industries. Working professionals seek data science skills for career advancement, job security, and transition to more technical roles. Employers increasingly require data literacy across all functions. The acceleration of digital transformation has highlighted data skill gaps. Short-term, flexible programs including online courses, bootcamps, and part-time degrees enable professionals to enhance skills without career interruption. As organizations prioritize data capabilities, working professionals deliver the fastest end-user growth.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, supported by strong demand for data science skills, established educational infrastructure, and significant corporate training investment. The United States is home to numerous leading universities, bootcamps, and online platforms offering data science education. Strong technology sector and high adoption of data-driven business practices create substantial demand. Corporate training and professional development programs are well-established across industries. Government initiatives promoting STEM education support market growth. With strong educational infrastructure and sustained demand, North America maintains its dominant market position.

Region with highest CAGR:

Over the forecast period, the Asia-Pacific region is anticipated to exhibit the highest CAGR, driven by digital transformation, large populations of students and professionals, and government technology education initiatives. Countries including India, China, Singapore, and Australia are experiencing growing demand for data science education across academic and professional segments. The region's large technology workforce and expanding digital economy create substantial addressable market. Government initiatives promoting digital skills development support market expansion. As organizations across the region adopt data-driven strategies, demand for data science education accelerates. With large populations and technology advancement, Asia Pacific delivers the fastest market growth globally.

Key players in the market

Some of the key players in Data Science Education Market include Coursera, Inc., Udacity, Inc., Udemy, Inc., edX LLC, Simplilearn Solutions Pvt. Ltd., DataCamp, Inc., Great Learning Education Services Private Limited, upGrad Education Private Limited, Pluralsight, LLC, LinkedIn Corporation, Skillsoft Corporation, Springboard, Inc., Scaler Academy, NIIT Limited, Emeritus Institute of Management Pte. Ltd., General Assembly Space, Inc., 365 Data Science Ltd., and Codecademy LLC.

Key Developments:

In June 2026, Simplilearn introduced a portfolio of specialized programs focused on the emerging enterprise landscape, releasing dedicated courses in Applied Agentic AI alongside corporate certifications from Michigan Engineering and IIT Madras to train data teams in system verification.

In May 2026, Skillsoft entered into a definitive agreement to divest its Global Knowledge instructor-led training (ILT) business to Enduring Ventures for up to $20 million, allowing the company to strictly focus resources on scaling its core, cloud-based "AI-native skills management platform."

In May 2026, upGrad School of Technology launched a comprehensive merit-and-need-based scholarship initiative, offering up to 100% tuition coverage for its specialized four-year B.Tech programmes in Computer Science, Artificial Intelligence, and Machine Learning to bridge the advanced tech skills gap.

Learning Modes Covered:

  • Classroom Learning
  • Online Learning
  • Blended Learning

Course Types Covered:

  • Certificate Programs
  • Diploma Programs
  • Undergraduate Programs
  • Postgraduate Programs
  • Corporate Training
  • Bootcamps

Delivery Models Covered:

  • Self-Paced Learning
  • Instructor-Led Training

End Users Covered:

  • Students
  • Working Professionals
  • Enterprises
  • Government Organizations

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global Data Science Education Market, By Learning Mode

  • 5.1 Classroom Learning
  • 5.2 Online Learning
  • 5.3 Blended Learning

6 Global Data Science Education Market, By Course Type

  • 6.1 Certificate Programs
  • 6.2 Diploma Programs
  • 6.3 Undergraduate Programs
  • 6.4 Postgraduate Programs
  • 6.5 Corporate Training
  • 6.6 Bootcamps

7 Global Data Science Education Market, By Delivery Model

  • 7.1 Self-Paced Learning
  • 7.2 Instructor-Led Training

8 Global Data Science Education Market, By End User

  • 8.1 Students
  • 8.2 Working Professionals
  • 8.3 Enterprises
  • 8.4 Government Organizations

9 Global Data Science Education Market, By Geography

  • 9.1 North America
    • 9.1.1 United States
    • 9.1.2 Canada
    • 9.1.3 Mexico
  • 9.2 Europe
    • 9.2.1 United Kingdom
    • 9.2.2 Germany
    • 9.2.3 France
    • 9.2.4 Italy
    • 9.2.5 Spain
    • 9.2.6 Netherlands
    • 9.2.7 Belgium
    • 9.2.8 Sweden
    • 9.2.9 Switzerland
    • 9.2.10 Poland
    • 9.2.11 Rest of Europe
  • 9.3 Asia Pacific
    • 9.3.1 China
    • 9.3.2 Japan
    • 9.3.3 India
    • 9.3.4 South Korea
    • 9.3.5 Australia
    • 9.3.6 Indonesia
    • 9.3.7 Thailand
    • 9.3.8 Malaysia
    • 9.3.9 Singapore
    • 9.3.10 Vietnam
    • 9.3.11 Rest of Asia Pacific
  • 9.4 South America
    • 9.4.1 Brazil
    • 9.4.2 Argentina
    • 9.4.3 Colombia
    • 9.4.4 Chile
    • 9.4.5 Peru
    • 9.4.6 Rest of South America
  • 9.5 Rest of the World (RoW)
    • 9.5.1 Middle East
      • 9.5.1.1 Saudi Arabia
      • 9.5.1.2 United Arab Emirates
      • 9.5.1.3 Qatar
      • 9.5.1.4 Israel
      • 9.5.1.5 Rest of Middle East
    • 9.5.2 Africa
      • 9.5.2.1 South Africa
      • 9.5.2.2 Egypt
      • 9.5.2.3 Morocco
      • 9.5.2.4 Rest of Africa

10 Strategic Market Intelligence

  • 10.1 Industry Value Network and Supply Chain Assessment
  • 10.2 White-Space and Opportunity Mapping
  • 10.3 Product Evolution and Market Life Cycle Analysis
  • 10.4 Channel, Distributor, and Go-to-Market Assessment

11 Industry Developments and Strategic Initiatives

  • 11.1 Mergers and Acquisitions
  • 11.2 Partnerships, Alliances, and Joint Ventures
  • 11.3 New Product Launches and Certifications
  • 11.4 Capacity Expansion and Investments
  • 11.5 Other Strategic Initiatives

12 Company Profiles

  • 12.1 Coursera, Inc.
  • 12.2 Udacity, Inc.
  • 12.3 Udemy, Inc.
  • 12.4 edX LLC
  • 12.5 Simplilearn Solutions Pvt. Ltd.
  • 12.6 DataCamp, Inc.
  • 12.7 Great Learning Education Services Private Limited
  • 12.8 upGrad Education Private Limited
  • 12.9 Pluralsight, LLC
  • 12.10 LinkedIn Corporation
  • 12.11 Skillsoft Corporation
  • 12.12 Springboard, Inc.
  • 12.13 Scaler Academy
  • 12.14 NIIT Limited
  • 12.15 Emeritus Institute of Management Pte. Ltd.
  • 12.16 General Assembly Space, Inc.
  • 12.17 365 Data Science Ltd.
  • 12.18 Codecademy LLC

List of Tables

  • Table 1 Global Data Science Education Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global Data Science Education Market Outlook, By Learning Mode (2023-2034) ($MN)
  • Table 3 Global Data Science Education Market Outlook, By Classroom Learning (2023-2034) ($MN)
  • Table 4 Global Data Science Education Market Outlook, By Online Learning (2023-2034) ($MN)
  • Table 5 Global Data Science Education Market Outlook, By Blended Learning (2023-2034) ($MN)
  • Table 6 Global Data Science Education Market Outlook, By Course Type (2023-2034) ($MN)
  • Table 7 Global Data Science Education Market Outlook, By Certificate Programs (2023-2034) ($MN)
  • Table 8 Global Data Science Education Market Outlook, By Diploma Programs (2023-2034) ($MN)
  • Table 9 Global Data Science Education Market Outlook, By Undergraduate Programs (2023-2034) ($MN)
  • Table 10 Global Data Science Education Market Outlook, By Postgraduate Programs (2023-2034) ($MN)
  • Table 11 Global Data Science Education Market Outlook, By Corporate Training (2023-2034) ($MN)
  • Table 12 Global Data Science Education Market Outlook, By Bootcamps (2023-2034) ($MN)
  • Table 13 Global Data Science Education Market Outlook, By Delivery Model (2023-2034) ($MN)
  • Table 14 Global Data Science Education Market Outlook, By Self-Paced Learning (2023-2034) ($MN)
  • Table 15 Global Data Science Education Market Outlook, By Instructor-Led Training (2023-2034) ($MN)
  • Table 16 Global Data Science Education Market Outlook, By End User (2023-2034) ($MN)
  • Table 17 Global Data Science Education Market Outlook, By Students (2023-2034) ($MN)
  • Table 18 Global Data Science Education Market Outlook, By Working Professionals (2023-2034) ($MN)
  • Table 19 Global Data Science Education Market Outlook, By Enterprises (2023-2034) ($MN)
  • Table 20 Global Data Science Education Market Outlook, By Government Organizations (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.