Statistics and Calculus Methods for Data Analysis
By External Provider
About this course
This program focuses on the practical application of essential mathematical, statistical, and analytical techniques vital for advanced data science studies. Learn to calculate expected values, understand the normal distribution, perform derivative calculations, and solve complex integrals, all demonstrated with Python. Start with the concept of expected values and explore their relationship to the normal distribution, laying the groundwork for statistical analysis and predictive modeling. Move on to calculus, mastering derivatives and their applications in tasks like optimization and rate of change analysis. Advance further into solving integrals, including techniques for handling complex integrations and their significance in continuous data analysis. By the end of the course, you will possess a strong mathematical foundation to tackle more advanced data science topics. Engage in practical assignments and real-world projects to apply these methods in solving complex data problems. By leveraging tools like Python, you will gain hands-on understanding of these critical concepts.
What you will learn
- Calculate expected values and apply normal distribution for statistical analysis.
- Perform derivative calculations for optimization and rate of change analysis.
- Solve complex integrals using Python for continuous data analysis.
- Apply statistical and calculus methods in Python for predictive modeling.