Data Analysis with Python [Video]

Data Analysis with Python [Video]

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Marco Bonzanini

Start your journey to become a Data Science practitioner using Python
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Video Details

ISBN 139781788290548
Course Length2 hours and 26 minutes

Video Description

Python is a popular programming language ,widely used in many scenarios and easy to use to use. Data Science is an interdisciplinary field that employs techniques to extract knowledge from data. As one of the fast growing fields in technology, the interest for Data Science is booming, and the demand for specialized talent is on the rise.

This course introduces the audience to the field of Data Science using Python tools to manage and analyze data. You can learn some of the fundamental tools of the trade and apply them to real data problems. And along the way it discusses the use of Python stack for data analysis and scientific computing, and expands on concepts of data acquisition, data cleaning, data analysis and machine learning.

Style and Approach

A fun and friendly course packed with step by step instructions, it shows you how to get up and running with Python virtual environments using Conda. This course is divided into clear chunks so you can learn at your own pace.

We’ll discuss the creation and management of different environment, how to install Python packages for Data Science and how to use Jupyter notebooks as development tool.

Table of Contents

Python Core
The Course Overview
Python Core Concepts and Data Types
Understanding Iterables
List Comprehensions
Dates and Times
Accessing Raw Data
NumPy for Array Computation
Creating NumPy Arrays
Basic Stats and Linear Algebra
Reshaping, Indexing, and Slicing
Pandas for Data Frames
Getting Started with Pandas
Essential Operations with Data Frames
Summary Statistics from a Data Frame
Data Aggregation over a Data Frame
Exercise – Titanic Survivor Analysis
Exercise – Titanic Survivor Analysis
Predicting Titanic survival – A Supervised Learning Problem
Performing Supervised Learning with Scikit-Learn

What You Will Learn

  • Installing the core Python tools for data analysis
  • Dealing with different data types in Python
  • Using NumPy for fast array computation
  • Using Pandas for data analysis
  • Framing a Data Science problem and using Python tools to solve it

Authors

Table of Contents

Python Core
The Course Overview
Python Core Concepts and Data Types
Understanding Iterables
List Comprehensions
Dates and Times
Accessing Raw Data
NumPy for Array Computation
Creating NumPy Arrays
Basic Stats and Linear Algebra
Reshaping, Indexing, and Slicing
Pandas for Data Frames
Getting Started with Pandas
Essential Operations with Data Frames
Summary Statistics from a Data Frame
Data Aggregation over a Data Frame
Exercise – Titanic Survivor Analysis
Exercise – Titanic Survivor Analysis
Predicting Titanic survival – A Supervised Learning Problem
Performing Supervised Learning with Scikit-Learn

Video Details

ISBN 139781788290548
Course Length2 hours and 26 minutes
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