Students will learn essential skills, including describing data, understanding probability theory, designing experiments, interpreting statistical results, and applying statistical models with Python. After successfully completing this Nanodegree program, graduates will be armed with a robust foundation in statistical analysis that can be applied to Data Analyst, Business Analyst, and Data Scientist roles.
Overview
Syllabus
- Welcome to the Statistics for Data Analysis Nanodegree Program
- Welcome to Udacity! We're excited to share more about your Nanodegree program and start this journey with you!
- Descriptive Statistics
- Learn how to describe data in terms of data types, measures of center, measures of spread, shape, and outliers. These essential skills in descriptive statistics provide the foundation for more advanced statistical techniques that are used for data science, data analysis, and machine learning.
- Probability
- This course is a comprehensive dive into the fundamental concepts and principles of probability. You’ll begin with basic probability theory, then progress to more complex topics such as binomial distributions, conditional probability, and Bayes’ Rule. These skills will enhance your ability to reason about uncertainty and make claims using data.
- Experimentation
- Experimentation is one of the most important topics in all of statistics because it tells us whether our conclusions are statistically significant. In this course, you will learn about the fundamental role statistics plays in experimentation as well as how to implement statistical concepts in Python.
- Algorithms
- The algorithms course offers a detailed introduction to fundamental statistical and machine learning algorithms, particularly focusing on regression techniques. The course begins with simple linear regression and progresses to multiple linear regression, equipping students with the ability to analyze relationships between multiple variables. Finally, it covers logistic regression, a powerful tool for classification problems.
- Statistics for Data Analysis - Capstone Project
- This capstone project gives you hands-on experience with A/B testing, a key practical application of statistical analysis. Students will produce a detailed technical analysis in a Jupyter Notebook, along with a non-technical slide deck presentation designed to effectively communicate their findings and recommendations to business stakeholders.
- Congratulations!
- Congratulations on finishing your program!
- Career Services
- The Careers team at Udacity is here to help you move forward in your career - whether it's finding a new job, exploring a new career path, or applying new skills to your current job.
Taught by
Josh Bernhard_color and Sebastian Thrun
