Python for Data Science E-Learning

Order this great E-Learning Training Python for Data Science online course  1 year 24/7 access to rich interactive videos, voice, practice assignments, progress monitoring through reports and tests per subject to test the knowledge directly. After the course you will receive a certificate of participation.

In this course you will get an introduction to use Python for Data Science. You get acquainted with the components of IPython, NoteBook and NumPy module, among others. The second part of this online course covers complex data pieces such as pandas, machine learning via SciPy operations and the scikit-learn tool set.Topics covered include Anaconda, JSON, SciPy stack, developing a 3D plot, managing processes in data science and much more. 

Course content

Python for Data Science: Introduction to NumPy for Multi-dimentional Data

Course: 1 Hour

• Course Overview
• Introduction to NumPy and the NumPy Ecosystem
• Array Creation - Part 1
• Array Creation - Part 2
• Printing Arrays
• Basic Array Operations
• Universal Functions
• Indexing and Slicing
• Iterating Over Arrays
• Reshaping Arrays
• Exercise: Python NumPy Array Operations

Python for Data Science: Advanced Operations with NumPy Arrays

Course: 1 Hour, 8 Minutes

• Course Overview
• Splitting NumPy Arrays
• Images as Arrays
• Image Manipulation Using NumPy
• Views and NumPy Arrays
• Deep Copies of Arrays
• Introduction to Index Masks
• Applying Index Masks
• Indexing with Boolean Masks
• Structured Arrays
• Understanding Array Broadcasting
• Applying Broadcasting Rules on Array Operations
• Exercise: NumPy Multi-dimensional Array Operations

Python for Data Science: Introduction to Pandas

Course: 1 Hour, 6 Minutes

• Course Overview
• Features of Pandas and the Pandas Ecosystem
• Introduction to Pandas
• Work with Pandas
• Introduction to DataFrames
• Work with DataFrames
• Load Data into a DataFrame
• Add and Delete DataFrame Contents
• Select Parts of a DataFrame
• Access Pandas DataFrames
• Introduction to Multi-Indexing in a Dataframe
• Reshape DataFrames
• Reshape Dataframes Using Stack and Melt Operations
• Exercise: Pandas for Basic Tabular Data Manipulation

Python for Data Science: Manipulating and Analyzing Data in Pandas DataFrames

Course: 45 Minutes

• Course Overview
• Iterating Over the Contents of a DataFrame
• Exporting a DataFrame
• Sorting
• Handling Missing Data
• Grouping with a Multi-Index
• Merging DataFrames
• Applying Join Operations on DataFrames
• Pandas and Relational Databases
• Exercise: Pandas for Advanced Data Manipulation

Python for Data Science: Basic Data Visualization Using Seaborn

Course: 1 Hour, 7 Minutes

• Course Overview
• Introduction to Seaborn
• Install Seaborn
• Simple Univariate Distributions
• Configure Univariate Distribution Plots
• Simple Bivariate Distributions
• Explore Different Types of Bivariate Distributions
• Analyze Multiple Variable Pairs
• Regression Plots
• Themes and Styles in Seaborn
• Exercise: Basic Data Visualization Using Seaborn

Python for Data Science: Advanced Data Visualization Using Seaborn

Course: 1 Hour, 4 Minutes

• Course Overview
• Searching for Patterns in a Dataset
• Configuring Plot Aesthetics
• Normal Distribution and Outliers
• Distributions Within Categories - Part 1
• Distributions Within Categories - Part 2
• Analyzing Categories with Facet Grids - Part 1
• Analyzing Categories with Facet Grids - Part 2
• Introducing Color Palettes5
• Using Color Palettes
• Exercise: Advanced Data Visualization Using Seaborn