Microplastic Monitoring and Data Analysis
Sampling, Lab Processing, Characterisation, Instrumentation, OpenSpecy Polymer Identification, AI-Assisted Coding & Statistical Analysis Using R
Environmental Data Science Training
Master R, Python, QGIS, statistics, GIS, and real-world environmental data analysis through live, project-based training.
Upcoming Live Courses
Learn tools and workflows that directly support research, analysis, visualization, and scientific reporting.
Sampling, Lab Processing, Characterisation, Instrumentation, OpenSpecy Polymer Identification, AI-Assisted Coding & Statistical Analysis Using R
Statistical Data Analysis, AI-Assisted Coding, Geospatial Analysis, Data Visualization, Environmental Case Studies
Time Series Analysis & Forecasting, Wind & Pollution Roses, Trend Analysis, Meteorological Data Analysis, Statistical Analysis, AI-Assisted Coding in R
Build trajectory, dispersion, and source interpretation workflows for research.
Why Envischolar
Each course is designed around real datasets, guided workflows, and research-oriented outputs that learners can reuse in academic and professional work.
Attend live sessions and revise later using recordings.
Examples from environmental science, GIS, pollution, and data analysis.
Structured teaching with clear steps and practical explanations.
Receive a completion certificate after finishing the course.
Learning Workflow
Choose a course and complete payment securely through Razorpay.
Join interactive sessions with explanations, demonstrations, and Q&A.
Use recordings, datasets, and examples to repeat the workflow.
Receive your Envischolar certificate after completion.
FAQs
Quick answers before you enroll.
Select your preferred course, complete the registration form, and make the payment. Course details will be shared by email.
Yes. Recorded sessions will be shared so that you can revise and practice later.
Yes. Participants receive an Envischolar e-certificate after successful completion of the course.
Yes. Courses are structured step by step and use practical examples from environmental science.
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