## Video Description

Take your data analytics and predictive modeling skills to the next level using the popular tools and libraries in Python

• Aimed for the beginner, this course contains in one place all you need to start analyzing data with Python

• Learn the foundations for doing Data Science and Predictive Analytics with Python through real-world examples

• Learn how ask questions and answer them effectively with the most widely used visualization and data analysis techniques

• In Detail

The Python programming language has become a major player in the world of Data Science and Analytics. This course introduces Python’s most important tools and libraries for doing Data Science; they are known in the community as "Python’s Data Science Stack".

This is a practical course where the viewer will learn through real-world examples how to use the most popular tools for doing Data Science and Analytics with Python.

1. Chapter 1 : The Anaconda Distribution and the Jupyter Notebook
1. The Course Overview 00:04:26
2. The Anaconda Distribution 00:07:44
3. Introduction to the Jupyter Notebook 00:09:51
4. Using the Jupyter Notebook 00:11:50
2. Chapter 2 : Vectorizing Operations with NumPy
1. NumPy: Python’s Vectorization Solution 00:07:48
2. NumPy Arrays: Creation, Methods and Attributes 00:23:24
3. Using NumPy for Simulations 00:11:58
3. Chapter 3 : Pandas: Everyone’s Favorite Data Analysis Library
1. The Pandas Library 00:14:09
2. Main Properties, Operations and Manipulations 00:13:37
4. Chapter 4 : Visualization and Exploratory Data Analysis
1. Basics of Matplotlib 00:07:01
2. Pyplot 00:10:22
3. The Object Oriented Interface 00:09:07
4. Common Customizations 00:11:48
5. EDA with Seaborn and Pandas 00:09:12
6. Analysing Variables Individually 00:17:23
7. Relationships between Variables 00:15:20
5. Chapter 5 : Statistical Computing with Python
1. SciPy and the Statistics Sub-Package 00:04:02
2. Alcohol Consumption – Confidence Intervals and Probability Calculations 00:10:37
3. Hypothesis Testing – Does Alcohol Consumption Affect Academic Performance? 00:08:07
4. Hypothesis Testing – Do Male Teenagers Drink More Than Females? 00:05:23
6. Chapter 6 : Introduction to Predictive Analytics Models
1. Introduction to Predictive Analytics Models 00:06:12
2. The Scikit-Learn Library – Building a Simple Predictive Model 00:06:41
3. Classification – Predicting the Drinking Habits of Teenagers 00:08:18
4. Regression – Predicting House Prices 00:08:07

## Product Information

• Title: Become a Python Data Analyst
• Author(s): Alvaro Fuentes
• Release date: May 2017
• Publisher(s): Packt Publishing
• ISBN: 9781787284302