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Become a Python Data Analyst
The Anaconda Distribution and the Jupyter Notebook
The Course Overview (4:25)
The Anaconda Distribution (7:43)
Introduction to the Jupyter Notebook (9:51)
Using the Jupyter Notebook (11:49)
Vectorizing Operations with NumPy
NumPy: Python’s Vectorization Solution (7:48)
NumPy Arrays: Creation, Methods and Attributes (23:23)
Using NumPy for Simulations (11:58)
Everyone’s Favorite Data Analysis Library
The Pandas Library (14:09)
Main Properties, Operations and Manipulations (13:36)
Answering Simple Questions about a Dataset – Part 1 (11:46)
Answering Simple Questions about a Dataset – Part 2 (15:55)
Visualization and Exploratory Data Analysis
Basics of Matplotlib (7:00)
Pyplot (10:21)
The Object Oriented Interface (9:06)
Common Customizations (11:47)
EDA with Seaborn and Pandas (9:12)
Analysing Variables Individually (17:22)
Relationships between Variables (15:20)
Statistical Computing with Python
SciPy and the Statistics Sub-Package
Alcohol Consumption – Confidence Intervals and Probability Calculations (10:37)
Hypothesis Testing – Does Alcohol Consumption Affect Academic Performance? (8:07)
Hypothesis Testing – Do Male Teenagers Drink More Than Females? (5:22)
Introduction to Predictive Analytics Models
Introduction to Predictive Analytics Models (6:11)
The Scikit-Learn Library – Building a Simple Predictive Model (6:41)
Classification – Predicting the Drinking Habits of Teenagers (8:18)
Regression – Predicting House Prices (8:07)
NumPy: Python’s Vectorization Solution
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