Environmental data as such does not speak much as it involves a large degree of complexity. The data starts speaking when it is analyzed and interpreted effectively and efficiently. The huge amount of environmental data being generated every hour which is not being used for making decisions, can help in restoring the environmental quality which is good for not only humans but also for the entire ecosystem. It is in this regard that CSE is organizing an online training course to address how environmental data can be made meaningful and presented in a understandable and relatable manner to the relevant stakeholders.

This training programme will include technical sessions, class exercises and live Q&A sessions with experts for better and in-depth understanding of the basics to the participants. The module makes sure that the participants discuss, debate and understand different aspects of data management and presentation with the experts. The aspect of analyzing and presenting data in a more efficient manner through Microsoft Excel will also be a part of this training.

Mode of Training 
The online course will majorly be based on self study basis wherein recorded sessions from experts, presentations and reading material will be uploaded on the training platform for the participants to study. The training portal has a dedicated discussion forum where all the queries can be posted and answered by the experts. Additionally, live online sessions will be organized with experts for Q& A and further discussions. The course is designed in a manner to help the participants in attending this course along with their regular work and study the course material at their own convenience.

Who should attend?
This training programme will be useful for students, academicians, environmental consultants, government regulators and to any person working or studying in the field of environment, as data is one aspect that all have to work with to make their work relevant.

Topics to be covered

  • Data collection
  • Basics of Statistical methods- Range, standard deviation, mean , media, mode and frequency
  • Distribution of data and fault finding
  • Trend analysis
  • Environmental load calculation
  • How to do forecasting? Ð Analysis of variance, correlation and regression analysis
  • Data Management and Analysis using Microsoft Excel
  • Class exercises and presentation of data