Gain essential probability and statistics knowledge needed for machine learning. This course covers foundational concepts, data summarization, probability rules, common distributions, and basic statistical inference using practical examples and Python.
Prerequisites Basic Python helpful
Level:
Core Concepts
Understand the role of probability and statistics in machine learning contexts.
Descriptive Statistics
Calculate and interpret measures of central tendency and dispersion for datasets.
Data Visualization
Create and interpret basic data visualizations like histograms and box plots.
Probability Basics
Apply fundamental probability rules and understand conditional probability.
Probability Distributions
Identify and understand common discrete and continuous probability distributions.
Statistical Inference Introduction
Grasp the basic ideas behind statistical inference, confidence intervals, and hypothesis testing.
Python Implementation
Use Python libraries like NumPy and Pandas to perform basic statistical calculations and data analysis.