Learn statistical analysis and geospatial visualization techniques for agricultural data. Use spatial data analysis to monitor crop yields, soil health, and other key metrics, applying Python and GIS tools to optimize farming practices and land management.

Dive into statistical analysis and visualization techniques for marketing. Learn how to analyze customer data, visualize trends, and use statistical methods to make data-driven marketing decisions that drive business growth.

This course demonstrates how Python and Matplotlib are used to work on different statistical distributions. Standard charts like histograms, boxplots, and violinplots are used to display statistical distributions.

Thoroughly understand statistical concepts, apply them in R and interpret the results correctly with maximum validity

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Build the foundation you need to think statistically and to speak the language of your data.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Delve into statistical theory and its applications in data analysis and research methodologies.

Master the fundamentals of statistics with Statistics 101. Learn key concepts like probability, hypothesis testing, and statistical inference, and apply them to real-world data analysis and decision-making scenarios in various industries.

Learn statistical methods and techniques for analyzing and interpreting data.

Data science

We live in a world of big data, and someone needs to make sense of all this data. In this course, you will learn to efficiently analyze data, formulate hypotheses, and generally reason about what the ocean of data out there is telling you.