Are you an environmental professional interested in improving your Data Management skills?
This course explains the importance to understand Data Science and Statistics concepts for environmental data management and help environmental professionals to draw the best conclusions when analyzing any data set.
This is your course if you work in the environmental field and want to take your first steps with the Data Science and Statistics and:
You want to learn the basics concepts of data science and statistics and how to use them effectively.
You want to carry out environmental consulting in the field of environmental data analyzes and management.
You want to learn how to use Exploratory Data Analysis techniques to help in the Data Storytelling process.
In this course, you will learn the fundamentals principles and concepts of Environmental Data Management using data science and statistical methods and techniques, this will help you to understand the first steps needed when evaluating and analyzing your data set.
To achieve that, you will be encouraged to learn and use software, languages and tools used to evaluate data and extract relevant information out of it, such as:
R for statistics
Pro UCL, from EPA
Visual Sampling Plan
Excel
MAROS
GWSDAT
Minitab
Etc.
The software mentioned above will not be explained in details, on the other hand, throughout the course the students will be stimulate to use the tool(s) that they fell more confortable with, in order to develop their skills in the tools that make more sense for each one.
Currently, developing these skills of data science statistics to manage your data are important because:
Big Data: every day the generation and collection of data in every field, including the environmental field, are huge in volume, and it is still growing with time. The amount and complexity of data generated need competent professionals to assess and interpret it effectively.
Career Improvement: the field of data science and statistics are some of the most popular in the market today, so environmental professionals with these skills are one step ahead.
In summary, the course presents explanations and examples, as well as hands-on exercises for the implementation of Data Science and Statistics to be used in the Environmental Data Management activities of professionals.
470
22
TAKE THIS COURSE