CN108665396A - A kind of big data education practical training method and system - Google Patents
A kind of big data education practical training method and system Download PDFInfo
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- CN108665396A CN108665396A CN201810459537.2A CN201810459537A CN108665396A CN 108665396 A CN108665396 A CN 108665396A CN 201810459537 A CN201810459537 A CN 201810459537A CN 108665396 A CN108665396 A CN 108665396A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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- G06Q50/20—Education
- G06Q50/205—Education administration or guidance
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- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
Abstract
The invention discloses a kind of big data education practical training methods and system to obtain the environmental characteristic of Practice Curriculum the method includes parsing Practice Curriculum demand；Corresponding one or more environment templates are called according to the environmental characteristic of Practice Curriculum, and one or more of environment templates are changed according to Practice Curriculum demand；One environment templates correspond to a big data cluster environment；Real training experimental situation is created according to the emulation data of the Practice Curriculum demand and modified one or more environment templates；Trainee accesses the real training experimental situation by interactive tool, and big data real training is carried out in the real training experimental situation；The method and system realize the flexible quick establishment of a variety of real training experimental situations, by calling the data of real case to be used as emulation data, make real training experiment closer to reality；The method and system use container technique so that can create and carry out multinomial real training experiment simultaneously, improve the rich and availability of real training experiment.
Description
Technical field
The present invention relates to fields of communication technology, and practical training method and system are educated more particularly, to a kind of big data.
Background technology
With the fast development of the communication technology, the magnitude grows exponentially of Various types of data, the epoch of big data have arrived
Come, big data analysis has the characteristics that data volume is big, query analysis is complicated compared to traditional data warehouse applications.Big data
Technology can be very good to adapt to current development in science and technology, thus tradesman include in the industry company for the learning demand of big data technology
Strongly, mode of learning traditional at present includes mainly network or the theory and technology personally instructed explanation, passes through PPT displayings or execute-in-place
Demonstration is assisted, then by voluntarily practicing after students in class；But since Internet technology applies upper particularity in study, only with reason
Demonstration auxiliary is technologically explained and operated by voluntarily practicing, and real training condition can not be provided, it is difficult to obtain good study
Effect.
Invention content
Education and study in order to solve to be directed to big data at present existing for background technology is only explained and is grasped by theory and technology
Make demonstration auxiliary, make student that can not obtain actual operation training, it is difficult to obtain good learning effect problem, the present invention provides
A kind of big data education practical training method and system, the method and system are pre-set by the parsing calling to course demand
Good environment templates, and by creating real training experimental situation to the modification of environment templates, make trainee that can be existed according to curriculum requirements
The Training for practice of big data is carried out under real training experimental situation, it is more efficient that learning training is carried out to big data technology；Described one kind
Big data educates practical training method：
Practice Curriculum demand is parsed, the environmental characteristic of Practice Curriculum is obtained；The environmental characteristic corresponds to needed for Practice Curriculum
One or more big data cluster environment；
Corresponding one or more environment templates are called according to the environmental characteristic of Practice Curriculum, and according to Practice Curriculum demand
Change one or more of environment templates；One environment templates correspond to a big data cluster environment, described to environment
The modification of template includes changing the parameter of the big data cluster environment；The parameter includes that clustered node number, node correlation are matched
It sets and node resource quota；
It is real that real training is created according to the emulation data of the Practice Curriculum demand and modified one or more environment templates
Test environment；
Trainee accesses the real training experimental situation by interactive tool, and big data is carried out in the real training experimental situation
Real training；
Further, environmental management is carried out to the real training experimental situation being currently running；The environmental management includes to
The operating status of the environmental management of operation is monitored in real time, and stops or delete the real training experimental situation being currently running；
Further, the environmental management includes being adjusted on backstage to the parameter of real training experimental situation according to Practice Curriculum demand
It is whole, and backstage debugging is carried out to the real training experimental situation of operation exception；When it is described real time monitoring deposit when abnormal, pass through environment
Administration interface is alarmed；
Further, manager by transfer trainee access real training experimental situation interactive operation interface, to trained
The real training situation of person is patrolled in real time；The manager is issued to one or more trainees by interactive operation interface and is broadcasted
Information, the trainee are putd question to by interactive operation interface to manager；
Further, the emulation data include multigroup real case data for a variety of big data cluster environment；Institute
It states emulation data to be stored in database, corresponding real case number is transferred according to the Practice Curriculum demand in the database
According to；
Further, the multiple real training experimental situation can be run simultaneously；It creates and transports simultaneously by using container technique
The multiple real training experimental situations of row；Each operation in the multiple real training experimental situation in a vessel, each container phase
Mutually isolation.
A kind of big data educates experience system：Creating environments unit and interactive access unit；
The creating environments unit obtains the environmental characteristic of Practice Curriculum for parsing Practice Curriculum demand；The ring
Border feature corresponds to one or more big data cluster environment needed for Practice Curriculum；
The creating environments unit includes the template library for storage environment template, and the creating environments unit is used for basis
The environmental characteristic of Practice Curriculum calls corresponding one or more environment templates in template library, and is repaiied according to Practice Curriculum demand
Change one or more of environment templates；One environment templates correspond to a big data cluster environment, described to environment mould
The modification of plate includes changing the parameter of the big data cluster environment；The parameter includes clustered node number, node relevant configuration
And node resource quota；
The creating environments unit is used for according to the emulation data of the Practice Curriculum demand and one or more modified
A environment templates create real training experimental situation；
The interactive access unit for making trainee by real training experimental situation described in the interactive access unit access,
Big data real training is carried out in the real training experimental situation.
Further, the system comprises environmental management unit, the environmental management unit is used for the reality to being currently running
It instructs experimental situation and carries out environmental management；The environmental management includes being carried out in real time to the operating status for the environmental management being currently running
Monitoring, and stop or delete the real training experimental situation being currently running；
Further, the environmental management includes being adjusted on backstage to the parameter of real training experimental situation according to Practice Curriculum demand
It is whole, and backstage debugging is carried out to the real training experimental situation of operation exception；When it is described real time monitoring deposit when abnormal, pass through environment
The interactive interface of administrative unit is alarmed；
Further, manager transfers the interaction of the real training experimental situation of trainee's access by the interactive access unit
Operation interface patrols in real time to the real training situation of trainee；The interactive operation that the manager passes through interactive access unit
Broadcast message is issued in interface to one or more trainees, the trainee by the interactive operation interface of interactive access unit to
Manager puts question to；
Further, the creating environments unit includes database, and the emulation data are stored in database；It is described imitative
True data includes multigroup real case data for a variety of big data cluster environment；The creating environments unit is according to the reality
Instruction course demand transfers corresponding real case data in the database；
Further, the multiple real training experimental situation can be run simultaneously；The creating environments unit is by using container
Technology creates and runs multiple real training experimental situations simultaneously；Each in the multiple real training experimental situation operates in an appearance
In device, each container is mutually isolated；
Further, the creating environments unit increases the new of corresponding cluster environment according to big data project real case
Environment templates simultaneously update template library；According to the data update database of the big data project real case.
Beneficial effects of the present invention are：Technical scheme of the present invention gives a kind of big data education practical training method and is
System, the method and system obtain the environmental characteristic of Practice Curriculum by parsing Practice Curriculum demand, and according to environment spy
Requisition use changes environment templates, and then creates real training experimental situation, to realize flexible, quick, high-adaptability experimental situation wound
Construction method effectively realizes the establishment of various real training experimental situations by the combination of multiple environment templates, by calling practical case
The data of example make real training experiment closer to reality as emulation data；Meanwhile the method and system are made by providing interaction
Trainee can obtain better experience in actual mechanical process, while also can complete real training at any time with manager's interaction；Institute
It states method and system and uses container technique so that can create and carry out multinomial real training experiment simultaneously, improve the rich of real training experiment
Richness and availability.
Description of the drawings
By reference to the following drawings, exemplary embodiments of the present invention can be more fully understood by：
Fig. 1 is that a kind of big data of the specific embodiment of the invention educates the flow chart of practical training method；
Fig. 2 is that a kind of big data of the specific embodiment of the invention educates the structure chart of experience system.
Specific implementation mode
Exemplary embodiments of the present invention are introduced referring now to the drawings, however, the present invention can use many different shapes
Formula is implemented, and is not limited to the embodiment described herein, and to provide these embodiments be to disclose at large and fully
The present invention, and fully convey the scope of the present invention to person of ordinary skill in the field.Show for what is be illustrated in the accompanying drawings
Term in example property embodiment is not limitation of the invention.In the accompanying drawings, identical cells/elements use identical attached
Icon is remembered.
Unless otherwise indicated, term (including scientific and technical terminology) used herein has person of ordinary skill in the field
It is common to understand meaning.Further it will be understood that with the term that usually used dictionary limits, should be understood as and its
The context of related field has consistent meaning, and is not construed as Utopian or too formal meaning.
Fig. 1 is that a kind of big data of the specific embodiment of the invention educates the flow chart of practical training method；The method passes through
The environmental characteristic that Practice Curriculum demand obtains Practice Curriculum is parsed, and is called according to the environmental characteristic, modification environment templates, into
And it creates real training experimental situation and passes through interactive tool visit study for trainee；A kind of big data educates practical training method packet
It includes：
Step 110, Practice Curriculum demand is parsed, the environmental characteristic of Practice Curriculum is obtained；The environmental characteristic corresponds to real training
One or more big data cluster environment needed for course；
By parsing Practice Curriculum demand, one or more big data cluster environment needed for Practice Curriculum are confirmed；With this
For embodiment, if Practice Curriculum demand is " to write spark programs, complete based on 10 years school student achievements of history on hdfs
The trend analysis of table data ", then by parsing, confirm the big data cluster environment of needs include HDFS cluster environment and
Spark cluster environment；
Step 120, corresponding one or more environment templates are called according to the environmental characteristic of Practice Curriculum, and according to real training
Course demand changes one or more of environment templates；One environment templates correspond to a big data cluster environment, institute
It includes changing the parameter of the big data cluster environment to state to the modification of environment templates；The parameter includes clustered node number, section
Point relevant configuration and node resource quota；
Store multiple environment templates in the corresponding system of the method, each correspondence in the multiple environment templates
One big data cluster；A kind of big data cluster environment can correspond to multiple environment templates；If HDFS cluster environment is because of it
The difference of clustered node number, relevant configuration can store multiple environment templates in systems, and system is according to Practice Curriculum demand tune
Most similar environment templates are taken to carry out next step modification；
The environment templates are made of one group of parameter and description, cover the Docker mirror images to big data component in environment
The relevant configuration of mark, clustered node number, node and node resource quota etc.；
Step 130, according to the emulation data of the Practice Curriculum demand and modified one or more environment templates wounds
Build real training experimental situation；
Further, the environment templates are modified according to course demand, and the modification includes according to course demand
Content, difficulty etc. are by the number of clustered node, and resource quota etc. is adjusted and changes between the configuration and node of each node；Make
Can be mutually coordinated between multiple environment templates, each environment templates meet the requirement of course；
Further, the emulation data include multigroup real case data for a variety of big data cluster environment；Institute
It states emulation data to be stored in database, corresponding real case number is transferred according to the Practice Curriculum demand in the database
According to；
Real training is carried out according to a certain real case if being write exactly in course demand, transfers the data of the case as emulation number
According to using；If not write exactly in course demand, the number of a certain real case of dynamic select can be required according to other in course demand
It is used according to as emulation data.
After manager creates completion experimental situation, the experimental situation is issued by interactive tool；
Step 140, trainee accesses the real training experimental situation by interactive tool, in the real training experimental situation into
Row big data real training；
The trainee accesses experimental situation according to curriculum requirements, by interactive tool, and in the experimental situation into
Row real training education；
Further, the trainee can be putd question to by interactive operation interface to manager, be answered by specific aim
Complete real training education；
Further, the administrator can carry out environmental management to the real training experimental situation being currently running；The environment pipe
Reason includes that the operating status of the environmental management to being currently running monitors in real time, and stops or delete the real training being currently running
Experimental situation；
The real time monitoring includes the state of reaching the standard grade that monitoring is respectively carrying out real training trainee, the fortune of each real training experimental situation
Row state；When the real time monitoring is deposited when abnormal, such as operating status exception, system is alarmed by environmental management interface；
Further, the environmental management include the parameter of real training experimental situation is adjusted on backstage according to Practice Curriculum demand, and
Backstage debugging is carried out to the real training experimental situation of operation exception；
Further, manager by transfer trainee access real training experimental situation interactive operation interface, to trained
The real training situation of person is patrolled in real time；The content of the inspection includes browsing trainee's interactive interface, confirms a trainee's
Real training progress；
Further, the manager issues broadcast message, institute by interactive operation interface to one or more trainees
It includes the points for attention issued during curriculum requirements, course to state broadcast message, and remind etc..
Further, the multiple real training experimental situation can be run simultaneously；It creates and transports simultaneously by using container technique
The multiple real training experimental situations of row；Each operation in the multiple real training experimental situation in a vessel, each container phase
Mutually isolation.
A kind of big data educates practical training method, and the method obtains Practice Curriculum by parsing Practice Curriculum demand
Environmental characteristic, and according to environmental characteristic calling, modification environment templates, and then real training experimental situation is created, to realize spirit
Living, quick, high-adaptability experimental situation creation method effectively realizes various big datas by the combination of multiple environment templates
The establishment of real training experimental situation makes real training experiment closer to reality by calling the data of real case to be used as emulation data；Together
When, the method and system make trainee that can obtain better experience in actual mechanical process by providing interaction.
Fig. 2 is that a kind of big data of the specific embodiment of the invention educates the structure chart of experience system, as shown in Fig. 2, institute
The system of stating includes：Creating environments unit 210 and interactive access unit 220；
The creating environments unit 210 obtains the environmental characteristic of Practice Curriculum for parsing Practice Curriculum demand；It is described
Environmental characteristic corresponds to one or more big data cluster environment needed for Practice Curriculum；
The creating environments unit 210 includes the template library for storage environment template, and the creating environments unit 210 is used
In calling corresponding one or more environment templates in template library according to the environmental characteristic of Practice Curriculum, and according to Practice Curriculum
Demand changes one or more of environment templates；One environment templates correspond to a big data cluster environment, described right
The modification of environment templates includes changing the parameter of the big data cluster environment；The parameter includes clustered node number, node phase
Close configuration and node resource quota；
The creating environments unit 210 be used for according to the emulation data of the Practice Curriculum demand and it is modified one or
Multiple environment templates create real training experimental situation；
Further, the creating environments unit 210 includes database, and the emulation data are stored in database；Institute
It includes multigroup real case data for a variety of big data cluster environment to state emulation data；The creating environments unit 210
Corresponding real case data are transferred in the database according to the Practice Curriculum demand；
Further, the creating environments unit 210 increases corresponding cluster environment according to big data project real case
New environment templates simultaneously update template library；According to the data update database of the big data project real case.
The interactive access unit 220 is for making trainee access the real training reality by the interactive access unit 220
Environment is tested, big data real training is carried out in the real training experimental situation.
Further, manager transfers the real training experimental situation of trainee's access by the interactive access unit 220
Interactive operation interface patrols in real time to the real training situation of trainee；The friendship that the manager passes through interactive access unit 220
Broadcast message, the interaction that the trainee passes through interactive access unit 220 are issued to one or more trainees in interoperability interface
Operation interface is putd question to manager；
Further, the system comprises environmental management unit 230, the environmental management unit 230 is used for transporting
Capable real training experimental situation carries out environmental management；The environmental management include to the operating status of the environmental management being currently running into
Row real time monitoring, and stop or delete the real training experimental situation being currently running；
Further, the environmental management includes being adjusted on backstage to the parameter of real training experimental situation according to Practice Curriculum demand
It is whole, and backstage debugging is carried out to the real training experimental situation of operation exception；When it is described real time monitoring deposit when abnormal, pass through environment
The interactive interface of administrative unit 230 is alarmed；
Further, the multiple real training experimental situation can be run simultaneously；The creating environments unit 210 is by using appearance
Device technology creates and runs multiple real training experimental situations simultaneously；Each in the multiple real training experimental situation operates in one
In container, each container is mutually isolated.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that the implementation of the disclosure
Example can be put into practice without these specific details.In some instances, well known method, structure is not been shown in detail
And technology, so as not to obscure the understanding of this description.
Those skilled in the art, which are appreciated that, to carry out adaptively the module in the equipment in embodiment
Change and they are arranged in the one or more equipment different from the embodiment.It can be the module or list in embodiment
Member or component be combined into a module or unit or component, and can be divided into addition multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it may be used any
Combination is disclosed to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so to appoint
Where all processes or unit of method or equipment are combined.Unless expressly stated otherwise, this specification (including adjoint power
Profit requires, abstract and attached drawing) disclosed in each feature can be by providing the alternative features of identical, equivalent or similar purpose come generation
It replaces.Involved in this specification to the step of number be only used for distinguishing each step, and time being not limited between each step
Or the relationship of logic, restriction unless the context clearly, otherwise the relationship between each step includes various possible situations.
In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments
In included certain features rather than other feature, but the combination of the feature of different embodiments means to be in the disclosure
Within the scope of and form different embodiments.For example, embodiment claimed in detail in the claims is one of arbitrary
It mode can use in any combination.
The all parts embodiment of the disclosure can be with hardware realization, or to run on one or more processors
Software module realize, or realized with combination thereof.The disclosure is also implemented as executing side as described herein
Some or all equipment or system program (for example, computer program and computer program product) of method.It is such
Realize that the program of the disclosure can may be stored on the computer-readable medium, or can be with the shape of one or more signal
Formula.Such signal can be downloaded from internet website and be obtained, and either be provided on carrier signal or with any other shape
Formula provides.
The disclosure is limited it should be noted that above-described embodiment illustrates rather than the disclosure, and ability
Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.Word "comprising" is not arranged
Except there are element or steps not listed in the claims.Word "a" or "an" before element does not exclude the presence of more
A such element.The disclosure can be by means of including the hardware of several different elements and by means of properly programmed calculating
Machine is realized.If in the unit claim for listing dry systems, several in these systems can be by same
Hardware branch embodies.
The above is only the specific implementation mode of the disclosure, it is noted that for the ordinary skill people of this field
Member for, under the premise of not departing from disclosure spirit, can make several improvements, change and deform, these improve, modification,
It is regarded as falling within the scope of protection of this application with deformation.
Claims (10)
1. a kind of big data educates practical training method, the method includes：
Practice Curriculum demand is parsed, the environmental characteristic of Practice Curriculum is obtained；The environmental characteristic corresponds to one needed for Practice Curriculum
A or multiple big data cluster environment；
Corresponding one or more environment templates are called according to the environmental characteristic of Practice Curriculum, and are changed according to Practice Curriculum demand
One or more of environment templates；One environment templates correspond to a big data cluster environment, described to environment templates
Modification include changing the parameter of the big data cluster environment；The parameter include clustered node number, node relevant configuration with
And node resource quota；
Real training experimental ring is created according to the emulation data of the Practice Curriculum demand and modified one or more environment templates
Border；
Trainee accesses the real training experimental situation by interactive tool, and it is real that big data is carried out in the real training experimental situation
Instruction.
2. according to the method described in claim 1, it is characterized in that, the method includes：To the real training experimental ring being currently running
Border carries out environmental management；The environmental management includes that the operating status of the environmental management to being currently running monitors in real time, with
And stop or delete the real training experimental situation being currently running.
3. according to the method described in claim 2, it is characterized in that：The environmental management includes according to Practice Curriculum demand to reality
The parameter for instructing experimental situation adjusts on backstage, and carries out backstage debugging to the real training experimental situation of operation exception；When the reality
When monitoring deposit when abnormal, alarmed by environmental management interface.
4. according to the method described in claim 1, it is characterized in that：The real training experimental ring that manager is accessed by transferring trainee
The interactive operation interface in border patrols in real time to the real training situation of trainee；The manager by interactive operation interface to
One or more trainees issue broadcast message, and the trainee is putd question to by interactive operation interface to manager.
5. according to the method described in claim 1, it is characterized in that：The multiple real training experimental situation can be run simultaneously；Pass through
It is created simultaneously using container technique and runs multiple real training experimental situations；Each operation in the multiple real training experimental situation
In a vessel, each container is mutually isolated.
6. a kind of big data educates experience system, the system comprises：Creating environments unit and interactive access unit；
The creating environments unit obtains the environmental characteristic of Practice Curriculum for parsing Practice Curriculum demand；The environment is special
One or more big data cluster environment needed for the corresponding Practice Curriculum of sign；
The creating environments unit includes the template library for storage environment template, and the creating environments unit is used for according to real training
The environmental characteristic of course calls corresponding one or more environment templates in template library, and changes institute according to Practice Curriculum demand
State one or more environment templates；One environment templates correspond to a big data cluster environment, described to environment templates
Modification includes the parameter for changing the big data cluster environment；The parameter include clustered node number, node relevant configuration and
Node resource quota；
The creating environments unit is used for the emulation data according to the Practice Curriculum demand and modified one or more rings
Border template creates real training experimental situation；
The interactive access unit is for making trainee by real training experimental situation described in the interactive access unit access, in institute
State progress big data real training in real training experimental situation.
7. system according to claim 6, it is characterised in that：The system comprises environmental management unit, the environment pipe
Reason unit is used to carry out environmental management to the real training experimental situation being currently running；The environmental management includes the ring to being currently running
The operating status of border management is monitored in real time, and stops or delete the real training experimental situation being currently running.
The environmental management includes being adjusted on backstage to the parameter of real training experimental situation according to Practice Curriculum demand, and to operation
Abnormal real training experimental situation carries out backstage debugging；When it is described real time monitoring deposit when abnormal, pass through the friendship of environmental management unit
It alarms at mutual interface.
8. according to the method described in claim 6, it is characterized in that：Manager transfers trainee by the interactive access unit
The interactive operation interface of the real training experimental situation of access patrols in real time to the real training situation of trainee；The manager is logical
Broadcast message is issued in the interactive operation interface for crossing interactive access unit to one or more trainees, and the trainee passes through interaction
It is putd question to manager at the interactive operation interface of access unit.
9. system according to claim 6, it is characterised in that：The creating environments unit includes database, the emulation
Data are stored in database；The emulation data include multigroup real case data for a variety of big data cluster environment；
The creating environments unit transfers corresponding real case data in the database according to the Practice Curriculum demand.
The creating environments unit increases the new environment templates and more of corresponding cluster environment according to big data project real case
New template library；According to the data update database of the big data project real case.
10. system according to claim 6, it is characterised in that：The multiple real training experimental situation can be run simultaneously；It is described
Creating environments unit is created by using container technique and runs multiple real training experimental situations simultaneously；The multiple real training experimental ring
In a vessel, each container is mutually isolated for each operation in border.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110516934A (en) * | 2019-08-13 | 2019-11-29 | 湖南智擎科技有限公司 | Intelligent big data practical training method and system based on scalable cluster |
| CN111260969A (en) * | 2020-03-06 | 2020-06-09 | 华南农业大学 | Data mining course teaching practice system and teaching practice method based on system |
| CN111612409A (en) * | 2020-03-30 | 2020-09-01 | 青岛青软实训教育科技股份有限公司 | Big data experiment practical training double-project operation system |
| CN111612408A (en) * | 2020-03-30 | 2020-09-01 | 青岛青软实训教育科技股份有限公司 | Cloud resource management system for big data experiment training |
| CN113504903A (en) * | 2021-07-06 | 2021-10-15 | 上海商汤智能科技有限公司 | Experiment generation method and device, electronic equipment and storage medium |
| CN117711234A (en) * | 2024-02-01 | 2024-03-15 | 南昌菱形信息技术有限公司 | Vocational education practical training system and method based on meta-universe technology |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004294701A (en) * | 2003-03-26 | 2004-10-21 | Hiroshima Gas Kk | Scientific experiment simulation system in virtual reality space |
| CN101853590A (en) * | 2009-03-30 | 2010-10-06 | 无锡职业技术学院 | Automatic flexible comprehensive training system and method |
| CN104468844A (en) * | 2014-12-31 | 2015-03-25 | 蓝盾信息安全技术股份有限公司 | Cloud-computing IAAS education experiment platform device |
| CN106803218A (en) * | 2017-03-17 | 2017-06-06 | 西安优盛信息技术有限公司 | A kind of big data tutoring system based on virtualization and cloud computing |
-
2018
- 2018-05-14 CN CN201810459537.2A patent/CN108665396A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004294701A (en) * | 2003-03-26 | 2004-10-21 | Hiroshima Gas Kk | Scientific experiment simulation system in virtual reality space |
| CN101853590A (en) * | 2009-03-30 | 2010-10-06 | 无锡职业技术学院 | Automatic flexible comprehensive training system and method |
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