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BEGIN:VEVENT
DTSTART;VALUE=DATE:20211213
DTEND;VALUE=DATE:20211218
DTSTAMP:20260422T184730
CREATED:20220425T145328Z
LAST-MODIFIED:20220804T114533Z
UID:10000408-1639353600-1639785599@prstats.preprodw.com
SUMMARY:ONLINE COURSE - Remote Sensing With Aircraft And Drone LiDAR Sensors (RSLD01) This course will be delivered live
DESCRIPTION:ONLINE COURSE – Trait based ecology Using R: Theory and Practice (TBER01)  This course will be delivered live\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, December 12th\, 2021\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – GMT+1 – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you. \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				\nUnmanned Airborne Vehicles (UAVs) equipped with consumer-grade imaging/ranging and direct geo-referencing systems have been proven as a potential Remote Sensing platform that could satisfy the needs of a wide range of civilian applications. The continuous developments in direct georeferencing and Remote Sensing (i.e.\, passive and active imaging sensors in the visible and infrared range – RGB cameras and LiDAR) is providing the professional geospatial community with ever-growing opportunities to provide accurate 3D information used in environmental research to collect information about the Earth\, such as vegetation and tree species. \n\n\nThis 4-day course aims to provide participants with an integrated \n\n\nend-to-end perspective going from measurement techniques to end- \n\n\nuser applications\, covering issues related to LiDAR sensors coupled on aircraft and UAVs\, computing exercises on the processing of 3D point clouds to produce geospatial products. \n\n			\n				\n				\n				\n				\n				Intended Audiences\n				\nAny researchers (PhD and MSc students\, post-docs\, primary investigators) and environmental professionals who are specialised in a variety of Earth Science disciplines and wish to expand and improve their knowledge and skills. \n\n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely \n			\n				\n				\n				\n				\n				Course Details\n				Availability – 30 places \nDuration – 4 days \nContact hours – Approx. 24 hours \nECT’s – Equal to 2 ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Teaching Format\n				\nThe course will be divided into theoretical lectures to introduce and explain key concepts and theories\, and practices with computing exercises on the processing of LiDAR data and point clouds. Afternoon practicals will be based on the topics covered in the morning lectures. \n\n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				\nFamiliarity with Geographic Information Systems and geospatial data (i.e.\, raster and vector data) could be useful\, but not mandatory. A basic understanding of physics radiation and proprieties of electromagnetic spectrum could be also useful\, but not required. \n\n			\n				\n				\n				\n				\n				Assumed computer background\n				\nNo prior experience with LiDAR processing software\, point cloud data or any programming language is required. \n\n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nAttendees of the course must use a computer with any Operating System installed (GNU/Linux\, MS Windows or MacOS). The course will use Open-Source software (FOSS) and some proprietary software which will be downloaded\, installed and configured during the lectures. \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	Tickets are no longer available\n\n\n	\n		\n		\n		\n	\n\n\n\n\n\n	\n\n \n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited. \n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n\nMonday 6th February – Classes from 10:00 to 17:00 \n\n\nModule 1: Fundamentals of Light Detection and Ranging (LiDAR) technique. Theoretical principles of a LiDAR systems. Electronic and sensor components. Main differences between spatial\, aerial and terrestrial platforms. The physics of laser signals: Introduction to discrete and full-waveform LiDAR and signal return analysis. Resolutions and precisions achieved. Advantages and disadvantages of the technique. Practice: Introduction to LiDAR data\, platforms and services. Overview of the available processing software and programming languages/libraries. \n\n\nTuesday 7th February – Classes from 10:00 to 17:00 \n\n\nModule 2: Interpretation of LiDAR data. Introduction to metrics/products such as Digital Elevation Models\, Digital Terrain Models and Canopy Height Models. Tree delineation approaches and algorithms (ex. Watershed Algorithm). Discrete versus full-waveform LiDAR data. Echo Decomposition for peak point extraction. Voxelisation of full-waveform LiDAR data. Introduction to binary files: Discrete and full-waveform LiDAR LAS files formats. Practice: Tridimensional point cloud processing and analysis. Filtering\, measuring and classification of LiDAR point clouds. \n\n\nMonday 13th February – Classes from 10:00 to 17:00 \n\n\nModule 3: Managing and exploring a LAS dataset. Visualization advanced techniques\, metadata analysis and content reports\, LiDAR points classification into ground points and non-ground points\, buildings and high vegetation classification. Coordinate Reference System transforms. LIDAR points triangulation into a TIN in order to create a Digital Elevation Model. Elevation contours extraction from a LiDAR point cloud and boundary polygon extraction. RGB colour sampled from an orthomosaic. \n\n\nTuesday 14th February – Classes from 10:00 to 17:00 \n\n\nModule 4: Different applications for LiDAR data: biodiversity monitoring\, forest health monitoring\, urban planning\, wood trade\, archaeology and heritage monitoring and automated driving. Other types of LiDAR systems: Space-based liDAR for measuring ice sheet mass balance\, cloud and aerosol heights. Bathymetric LiDAR for the study of underwater depth of ocean floors. Practice: Post-processing of LiDAR products\, Digital Terrain Model and elevation profile analysis. Measurements of distances\, areas and volumes. Integration with external geospatial data in a Geographic Information System (GIS). \n\n			\n				\n				\n				\n				\n				Course Instructor\n \nDr. Nelson Pires\n\n– Works at: University of Porto\, Portugal \n\n\n– Delivers: \n\n\nRemote Sensing with satellite multi-spectral sensors (RSMS01) \n\n\nRemote Sensing with drone RGB and Near Infrared cameras (RSWD01) \n\n\nRemote Sensing with aircraft and drone LiDAR sensors (RSLD) \n\n\nNelson holds a degree in Physics and Surveying Engineering\, a MSc and PhD degrees in Surveying Engineering from University of Porto. With more than 10 years of experience in teaching at higher education institutions and doing research work in several geospatial subjects. Past and recent research includes subjects in atmospheric corrections with high-precision Global Navigation Satellite Systems analysis\, aerial and close-range photogrammetric studies with drones for coastal monitoring and map production\, multi-spectral and SAR-imaging Remote Sensing for ocean wind-generated waves and ocean dynamics. \n\n\nORCID: https://orcid.org/0000-0002-6629-8060
URL:https://prstats.preprodw.com/course/online-course-remote-sensing-with-aircraft-and-drone-lidar-sensors-rsld01/
LOCATION:Delivered remotely (Portugal)\, Portugal
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/png:https://prstats.preprodw.com/wp-content/uploads/2022/02/VGNR04R.png
GEO:39.399872;-8.224454
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210920
DTEND;VALUE=DATE:20210921
DTSTAMP:20260422T184730
CREATED:20220219T015845Z
LAST-MODIFIED:20220804T113932Z
UID:10000314-1632096000-1632182399@prstats.preprodw.com
SUMMARY:ONLINE COURSE - Remote Sensing With Satellite Multi-Spectral Sensors (RSMS01) This course will be delivered live
DESCRIPTION:ONLINE COURSE – Trait based ecology Using R: Theory and Practice (TBER01)  This course will be delivered live\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, September 20th\, 2021\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – GMT+1 – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you. \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Details\n				\nSatellite Remote Sensing has become a common tool to investigate the different fields of Earth and environmental sciences. The progress of the performance capabilities of the optoelectronic and radar devices mounted on-board remote sensing platforms have further improved the capability of instruments to acquire information about the Earth and its resources for global\, regional and local assessments. Disciplines such as agriculture\, hydrology\, and ecosystem studies have all developed a strong Remote Sensing component\, facilitating our understanding of the environment and its processes over a broad range of spatial and temporal scales. \n\n\nThis 4-day course aims to provide participants with an integrated end-to-end perspective going from measurement techniques to end-user applications\, covering issues related to Remote Sensing\, Earth System Modelling and Data Assimilation as well as hands-on computing exercises on the processing of Earth Observation data. \n\n			\n				\n				\n				\n				\n				Intended Audiences\n				\nAny researchers (PhD and MSc students\, post-docs\, primary investigators) and environmental professionals who are specialised in a variety of Earth Science disciplines and wish to expand and improve their knowledge and skills. \n\n			\n				\n				\n				\n				\n				Venue\n				Delivered remotely \n			\n				\n				\n				\n				\n				Course Information\n				Availability – 30 places \nDuration – 4 days \nContact hours – Approx. 24 hours \nECT’s – Equal to 2 ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Teaching Format\n				\nThe course will be divided into theoretical lectures to introduce and explain key concepts and theories\, and practices with computing exercises on the processing of Earth Observation data. Afternoon practicals will be based on the topics covered in the morning lectures. \n\n			\n				\n				\n				\n				\n				Assumed quantitative knowledge\n				\nFamiliarity with Geographic Information Systems and geospatial data (i.e.\, raster and vector data) could be useful\, but not mandatory. A basic understanding of physics radiation and proprieties of electromagnetic spectrum could be also useful\, but not required. \n\n			\n				\n				\n				\n				\n				Assumed computer background\n				\nNo prior experience with Remote Sensing software and data or any programming language is required. Familiarity with any digital image processing technique will be helpful\, but is not required. \n\n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nAttendees of the course must use a computer with any Operating System installed (GNU/Linux\, MS Windows or MacOS). The course will use only Open-Source software (FOSS) which will be downloaded\, installed and configured during the lectures. \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	Tickets are no longer available\n\n\n	\n		\n		\n		\n	\n\n\n\n\n\n	\n\n \n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited. \n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n\nMonday 26th September – Classes from 10:00 to 17:00 \n\n\nModule 1: Fundamentals of Remote Sensing. Concepts of satellite orbits\, spacial resolutions\, temporal resolutions\, spectral and radiometric resolutions. Different types of sensors and processing levels of Earth Observation satellites. The physics of atmosphere and spectral signatures. Conceptual understanding of Remote Sensing\, where the participants will be able to identify its advantages and disadvantages. Introduction to data platforms\, software tools\, web portals\, and environmental monitoring applications. Practice: Introduction to Remote Sensing software. \n\n\nTuesday 27th September – Classes from 10:00 to 17:00 \n\n\nModule 2: Earth Observation Programmes. The National Aeronautics and Space Administration (NASA) LANDSAT Program and the European Space Agency (ESA) Copernicus/SENTINEL Program. History and Objectives. Satellite missions chronology. Different spatial\, temporal\, spectral and radiometric resolutions. LANDSAT Multispectral Scanner (MSS) and SENTINEL-2 Multispectral Instrument (MSI) sensor designs. Uses of Earth Observation satellite imagery for natural resources management\, climate change\, environmental disasters and ecology. Practice: Introduction to satellite image processing.  \n\n\nThursday 29th September – Classes from 10:00 to 17:00 \n\n\nModule 3: Remote Sensing for Vegetation Monitoring and Agricultural Applications. Satellite observations to assess a wide variety of geophysical and biophysical parameters\, including precipitation\, temperature\, evapotranspiration\, soil moisture\, and vegetation health. Band combination e index classification for vegetation monitoring. Remote Sensing data for agriculture monitoring\, specifically drought and crop monitoring. Practice: Supervised and unsupervised classification methods. \n\n\nFriday 30th September – Classes from 10:00 to 17:00 \n\n\nModule 4: Satellite Applications for Biodiversity Conservation. Specific applications and hands-on demonstrations of how to use Remote Sensing data to derive conservation policies and management decisions. Remote Sensing for Conservation and Biodiversity: Animal Movement\, Dynamic Habitat Index for Biodiversity\, Vegetation Carbon Stock Corridors and techniques for Land Change Detection. Land Management and Ecosystem Based Tools: Coral Reef Watch and MODIS NDVI Anomalies and Time Series. Practice: Image fusion and Pansharpening techniques. \n\n			\n				\n				\n				\n				\n				Course Instructor\n \n \n \n \n \n \nDr. Nelson Pires\n\n– Works at: University of Porto\, Portugal \n\n\n– Delivers: \n\n\nRemote Sensing with satellite multi-spectral sensors (RSMS01) \n\n\nRemote Sensing with drone RGB and Near Infrared cameras (RSWD01) \n\n\nRemote Sensing with aircraft and drone LiDAR sensors (RSLD) \n\n\nNelson holds a degree in Physics and Surveying Engineering\, a MSc and PhD degrees in Surveying Engineering from University of Porto. With more than 10 years of experience in teaching at higher education institutions and doing research work in several geospatial subjects. Past and recent research includes subjects in atmospheric corrections with high-precision Global Navigation Satellite Systems analysis\, aerial and close-range photogrammetric studies with drones for coastal monitoring and map production\, multi-spectral and SAR-imaging Remote Sensing for ocean wind-generated waves and ocean dynamics. \n\n\nORCID: https://orcid.org/0000-0002-6629-8060 \n\n 
URL:https://prstats.preprodw.com/course/remote-sensing-with-satellite-multi-spectral-sensors-rsms01/
LOCATION:Delivered remotely (Portugal)\, Portugal
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/png:https://prstats.preprodw.com/wp-content/uploads/2022/03/RSMS01.png
GEO:39.399872;-8.224454
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210809
DTEND;VALUE=DATE:20210814
DTSTAMP:20260422T184730
CREATED:20220302T143216Z
LAST-MODIFIED:20220804T111614Z
UID:10000403-1628467200-1628899199@prstats.preprodw.com
SUMMARY:ONLINE COURSE - Landscape genetic data analysis using R (LNDG04) This course will be delivered live
DESCRIPTION:ONLINE COURSE – Trait based ecology Using R: Theory and Practice (TBER01)  This course will be delivered live\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Event Date \nMonday\, 9th August\, 2021\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n					\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n				\n					\n						\n						\n							\n							\n						\n					\n				\n				\n				\n				\n			\n			\n				\n				\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you. \nTIME ZONE\nTIME ZONE – Eastern Standard Time – Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you). \n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				About This Course\n				The term ‘landscape genetics’ has been applied studies that integrate ecological context and intervening landscape into population genetic analyses of contemporary processes such as gene flow and migration. This course will cover the basics of both quantitative landscape ecology and population genetics\, focusing on how we develop and evaluate spatial/genetic analyses using the R platform. \n			\n				\n				\n				\n				\n				Intended Audiences\n				This course is suitable for graduate students\, postdoctoral researchers\, and primary investigators interested in learning how to integrate landscape ecological and population genetic tools using the R software. \n			\n				\n				\n				\n				\n				Course Details\n				Availability – 24 places \nDuration – 5 days \nContact hours – Approx. 35 hours \nECT’s – Equal to 3 ECT’s \nLanguage – English \n			\n				\n				\n				\n				\n				Venue\n				Delivered Remotely \n			\n				\n				\n				\n				\n				Teaching Format\n				There will be morning lectures based on the modules outlined in the course timetable. In the afternoon there will be practicals based on the topics covered that morning. Data sets for computer practicals will be provided by the instructors\, but participants are welcome to bring their own data. \n			\n				\n				\n				\n				\n				Assumed quantative knowledge\n				A basic understanding of statistical concepts. Specifically\, generalised linear regression models\, statistical significance\, hypothesis testing. \n			\n				\n				\n				\n				\n				Assumed computer background\n				Familiarity with R. Ability to import/export data\, manipulate data frames\, fit basic statistical models & generate simple exploratory and diagnostic plots. \n			\n				\n				\n				\n				\n				Equipment and software requirements\n				\nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n			\n			\n			\n				\n				\n				\n				\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				\n	\n		Tickets	\n	\n	\n	\n	\n	\n	\n		The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.	\n\n\n\n	\n	Tickets are no longer available\n\n\n	\n		\n		\n		\n	\n\n\n\n\n\n	\n\n\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited. \n			\n				\n				\n				\n				\n				\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n  \n			\n			\n				\n				\n				\n				\n			\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				COURSE PROGRAMME\n			\n				\n				\n				\n				\n				\n				\n				\n				\n				\n				Monday 15th\n				Classes from 9:30 to 17:30 \nModule 1: Spatial & Ecological Data.Installation & configuring R & RStudioAcquiring spatial data\, projections\, and visualizationVector and raster data \n  \n			\n				\n				\n				\n				\n				Tuesday 16th\n				Classes from 9:30 to 17:30 \nModule 2: Genetic markers and basic analysesGenetic markers and samplingGenetic distance\, diversity\, and structureOrdination techniques based upon genetic markers \n  \n			\n				\n				\n				\n				\n				Wednesday 17th\n				Classes from 9:30 to 17:30 \nModule 3: Integrating spatial and genetic dataBarrier detection & population divisionResistance ModelingMantel and distance regressionsRemote sensing – LiDAR and Hyperspectral data \n  \n			\n				\n				\n				\n				\n				Thursday 18th\n				Classes from 9:30 to 17:30 \nModule 4: Integrating spatial and genetic dataSpatial autocorrelationNetwork ApproachesPCMN & Redundancy \n  \n			\n				\n				\n				\n				\n				Friday 19th\n				Classes from 9:30 to 17:30 \nModule 5: Adaptive Genetic VarianceOutliers & gradientsQuantitative genetics\, why we should care.Chromosome walking \n  \n			\n			\n				\n				\n				\n				\n				Course Instructor\n \nProf. Rodney Dyer\nComing Soon
URL:https://prstats.preprodw.com/course/landscape-genetic-data-analysis-using-r-lndg04/
LOCATION:Delivered remotely (USA)\, Eastern Daylight Time\, MD United States\, United States
CATEGORIES:All Live Courses,Home Courses,Live Online Courses
ATTACH;FMTTYPE=image/png:https://prstats.preprodw.com/wp-content/uploads/2022/03/LNDG05.png
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