Python for Data Science - Python - Big Data - Programmeren (algemeen) - Data Science - Data Science Python - Functioneel programmeren - Programmeren voor beginners

Python for Data Science / Python / Programmeren (algemeen) / Data Science / Data Science Python. 

Bestel deze geweldige E-Learning Training Python for Data Science online cursus, 1 jaar 24/ 7 toegang tot rijke interactieve video’s, spraak, praktijkopdrachten, voortgangsbewaking door rapportages en testen per onderwerp om de kennis direct te toetsen. Na de cursus ontvangt u een certificaat van deelname.

In deze cursus krijgt u een introductie van Python te gebruiken voor Data Science. U maakt kennis met onder andere de componenten van IPython, NoteBook en NumPy module. In het tweede gedeelte van deze online cursus komen complexe data stukken aan bod zoals pandas, machine learning via SciPy operations en de scikit-learn toolset.Onderwerpen die onder andere aan bod komen zijn Anaconda, JSON, SciPy stack, ontwikkelen van 3D plot, beheren van processen in data science en nog veel meer.

Cursusinhoud

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