2020-2029 Report on Global Machine Learning in Education Market by Player, Region, Type, Application and Sales Channel
- Report Code : MAR2141360
- Published On: Nov, 2020
- Category : Internet Software & Services
- Pages : 136
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The global Machine Learning in Education market was valued at $XX million in 2019, and Research analysts predict the global market size will reach $XX million by the end of 2029, growing at a CAGR of XX% between 2020 and 2029.
Since the COVID-19 virus outbreak in December 2019, the disease has spread to over 210 countries and territories around the world and 2 international conveyances. The global impacts of COVID-19 are already starting to be felt, and will significantly affect this industry in 2020.
This report analyses the impact of COVID-19 on this industry. COVID-19 can affect the global market in 3 ways: by directly affecting production and demand, by creating supply chain and market disruption, and by its financial impact on enterprises and financial markets.
This report provides detailed historical analysis of global market for Machine Learning in Education from 2014-2019, and provides extensive market forecasts from 2020-2029 by region/country and subsectors. It covers the sales volume, price, revenue, gross margin, historical growth and future perspectives in the Machine Learning in Education market.
Leading players of Machine Learning in Education including:
IBM
Microsoft
Google
AWS
Cognizant
Pearson
Bridge-U
DreamBox Learning
Fishtree
Jellynote
Quantum Adaptive Learning
Nuance Communications
OSMO
Querium
Third Space Learning
Aleks
Blackboard
Carnegie Learning
Century
Cognii
Elemental Path
Jenzabar
Knewton
Luilishuo
Metacog
Market split by Type, can be divided into:
Deep Learning and Machine Learning
Natural Language Processing (NLP)
Market split by Application, can be divided into:
Intelligent Tutoring Systems
Virtual Facilitators
Content Delivery Systems
Interactive Websites
Others
Market split by Sales Channel, can be divided into:
Direct Channel
Distribution Channel
Market segment by Region/Country including:
North America (United States, Canada and Mexico)
Europe (Germany, UK, France, Italy, Russia and Spain etc.)
Asia-Pacific (China, Japan, Korea, India, Australia and Southeast Asia etc.)
South America (Brazil, Argentina and Colombia etc.)
Middle East & Africa (South Africa, UAE and Saudi Arabia etc.)
If you have any special requirements, please let us know and we can provide you the customized report as you want.
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With tables and figures helping analyze worldwide Report on Global Machine Learning in Education Market market, this research provides key statistics on the state of the industry and is a valuable source of guidance and direction for companies and individuals interested in the market.
Chapter 1 Machine Learning in Education Market Overview1.1 Machine Learning in Education Definition
1.2 Global Machine Learning in Education Market Size Status and Outlook (2014-2029)
1.3 Global Machine Learning in Education Market Size Comparison by Region (2014-2029)
1.4 Global Machine Learning in Education Market Size Comparison by Type (2014-2029)
1.5 Global Machine Learning in Education Market Size Comparison by Application (2014-2029)
1.6 Global Machine Learning in Education Market Size Comparison by Sales Channel (2014-2029)
1.7 Machine Learning in Education Market Dynamics (COVID-19 Impacts)
1.7.1 Market Drivers/Opportunities
1.7.2 Market Challenges/Risks
1.7.3 Market News (Mergers/Acquisitions/Expansion)
1.7.4 COVID-19 Impacts on Current Market
1.7.5 Post-Strategies of COVID-19 Outbreak
Chapter 2 Machine Learning in Education Market Segment Analysis by Player2.1 Global Machine Learning in Education Sales and Market Share by Player (2017-2019)
2.2 Global Machine Learning in Education Revenue and Market Share by Player (2017-2019)
2.3 Global Machine Learning in Education Average Price by Player (2017-2019)
2.4 Players Competition Situation & Trends
2.5 Conclusion of Segment by Player
Chapter 3 Machine Learning in Education Market Segment Analysis by Type3.1 Global Machine Learning in Education Market by Type
3.1.1 Deep Learning and Machine Learning
3.1.2 Natural Language Processing (NLP)3.2 Global Machine Learning in Education Sales and Market Share by Type (2014-2019)
3.3 Global Machine Learning in Education Revenue and Market Share by Type (2014-2019)
3.4 Global Machine Learning in Education Average Price by Type (2014-2019)
3.5 Leading Players of Machine Learning in Education by Type in 2019
3.6 Conclusion of Segment by Type
Chapter 4 Machine Learning in Education Market Segment Analysis by Application4.1 Global Machine Learning in Education Market by Application
4.1.1 Intelligent Tutoring Systems
4.1.2 Virtual Facilitators
4.1.3 Content Delivery Systems
4.1.4 Interactive Websites
4.1.5 Others4.2 Global Machine Learning in Education Sales and Market Share by Application (2014-2019)
4.3 Leading Consumers of Machine Learning in Education by Application in 2019
4.4 Conclusion of Segment by Application
Chapter 5 Machine Learning in Education Market Segment Analysis by Sales Channel5.1 Global Machine Learning in Education Market by Sales Channel
5.1.1 Direct Channel
5.1.2 Distribution Channel5.2 Global Machine Learning in Education Sales and Market Share by Sales Channel (2014-2019)
5.3 Leading Distributors/Dealers of Machine Learning in Education by Sales Channel in 2019
5.4 Conclusion of Segment by Sales Channel
Chapter 6 Machine Learning in Education Market Segment Analysis by Region6.1 Global Machine Learning in Education Market Size and CAGR by Region (2014-2029)
6.2 Global Machine Learning in Education Sales and Market Share by Region (2014-2019)
6.3 Global Machine Learning in Education Revenue and Market Share by Region (2014-2019)
6.4 North America
6.4.1 North America Market by Country
6.4.2 North America Machine Learning in Education Market Share by Type
6.4.3 North America Machine Learning in Education Market Share by Application
6.4.4 United States
6.4.5 Canada
6.4.6 Mexico6.5 Europe
6.5.1 Europe Market by Country
6.5.2 Europe Machine Learning in Education Market Share by Type
6.5.3 Europe Machine Learning in Education Market Share by Application
6.5.4 Germany
6.5.5 UK
6.5.6 France
6.5.7 Italy
6.5.8 Russia
6.5.9 Spain6.6 Asia-Pacific
6.6.1 Asia-Pacific Market by Country
6.6.2 Asia-Pacific Machine Learning in Education Market Share by Type
6.6.3 Asia-Pacific Machine Learning in Education Market Share by Application
6.6.4 China
6.6.5 Japan
6.6.6 Korea
6.6.7 India
6.6.8 Southeast Asia
6.6.9 Australia
6.7 South America
6.7.1 South America Market by Country
6.7.2 South America Machine Learning in Education Market Share by Type
6.7.3 South America Machine Learning in Education Market Share by Application
6.7.4 Brazil
6.7.5 Argentina
6.7.6 Colombia
6.8 Middle East & Africa
6.8.1 Middle East & Africa Market by Country
6.8.2 Middle East & Africa Machine Learning in Education Market Share by Type
6.8.3 Middle East & Africa Machine Learning in Education Market Share by Application
6.8.4 UAE
6.8.5 Saudi Arabia
6.8.6 South Africa
6.9 Conclusion of Segment by Region
Chapter 7 Profile of Leading Machine Learning in Education Players7.1 IBM
7.1.1 Company Snapshot
7.1.2 Product/Service Offered
7.1.3 Business Performance (Sales, Price, Revenue, Gross Margin and Market Share)
7.1.4 COVID-19 Impact on IBM7.2 Microsoft
7.3 Google
7.4 AWS
7.5 Cognizant
7.6 Pearson
7.7 Bridge-U
7.8 DreamBox Learning
7.9 Fishtree7.10 Jellynote
7.11 Quantum Adaptive Learning
7.12 Nuance Communications
7.13 OSMO
7.14 Querium
7.15 Third Space Learning
7.16 Aleks
7.17 Blackboard
7.18 Carnegie Learning
7.19 Century7.20 Cognii
7.21 Elemental Path
7.22 Jenzabar
7.23 Knewton
7.24 Luilishuo
7.25 Metacog
Chapter 8 Upstream and Downstream Analysis of Machine Learning in Education8.1 Industrial Chain of Machine Learning in Education
8.2 Upstream of Machine Learning in Education
8.2.1 Raw Materials
8.2.2 Labor Cost
8.2.3 Manufacturing Expenses
8.2.4 Manufacturing Cost Structure
8.2.5 Manufacturing Process8.3 Downstream of Machine Learning in Education
8.3.1 Leading Distributors/Dealers of Machine Learning in Education
8.3.2 Leading Consumers of Machine Learning in Education
Chapter 9 Development Trend of Machine Learning in Education (2020-2029)9.1 Global Machine Learning in Education Market Size (Sales and Revenue) Forecast (2020-2029)
9.2 Global Machine Learning in Education Market Size and CAGR Forecast by Region (2020-2029)
9.3 Global Machine Learning in Education Market Size and CAGR Forecast by Type (2020-2029)
9.4 Global Machine Learning in Education Market Size and CAGR Forecast by Application (2020-2029)
9.5 Global Machine Learning in Education Market Size and CAGR Forecast by Sales Channel (2020-2029)
Chapter 10 Appendix10.1 Research Methodology
10.2 Data Sources
10.3 Disclaimer
10.4 Analysts Certification
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The Report on Global Machine Learning in Education Market Market has been segregated into various crucial divisions including applications, types, and regions. Each market segment is intensively studied in the report contemplating its market acceptance, worthiness, demand, and growth prospects. The segmentation analysis will help the client to customize their marketing approach to have a better command of each segment and to identify the most prospective customer base.
Report Objectives / Segmentation Covered :
By Companies / players:
By Regions:
By Type:
By Application:
Frequently asked questions(FAQ's):
The Report on Global Machine Learning in Education Market study includes a diverse group of participants, including both market leaders and up-and-comers. Contact our sales representative to receive a complete list of companies covered in the study.
It is expected that the Report on Global Machine Learning in Education Market Market will reach USD XX million by 2029.
A handful of disruptive trends, nevertheless, will have a contradictory and significant impact on the development of the Report on Global Machine Learning in Education Market Market as well as its distribution among its players
This latest research publication on the Report on Global Machine Learning in Education Market Market is an in-depth market tracker that provides a comprehensive assessment of the challenges that manufacturers face in achieving new growth cycles in the current scenario.
