Python for Data Science: Analyzing Data Using Python 2024 E-Learning Training

Python voor gegevenswetenschap: Gegevens analyseren met Python

Deze training biedt een uitgebreide inleiding tot de mogelijkheden van Python op het gebied van data science en data-analyse. Essentiële Python-bibliotheken zoals Pandas, NumPy, Matplotlib en Seaborn komen aan bod en cursisten worden begeleid bij het opschonen, manipuleren, visualiseren en analyseren van gegevens. Deelnemers leren datasets importeren, verwerken en visualiseren om inzichten af te leiden, en de training bevat hands-on projecten om deze vaardigheden toe te passen in real-world scenario's.

Deze cursus is ideaal voor beginners of mensen met enige ervaring met codering en is ontworpen om een solide basis te leggen voor iedereen die zich wil toeleggen op data science, analytics of machine learning met behulp van Python.

Cursusinhoud

Python for Data Science

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

Analyzing Data Using Python

Analyzing Data Using Python: Data Analytics Using Pandas

Course: 1 Hour, 15 Minutes

• Course Overview
• Creating a pandas Series
• Performing Basic Series Operations
• Performing Casting Operations Using Series
• Performing Logical Operations Using Series
• Creating and Editing pandas DataFrames
• Performing Data Lookup Using DataFrames
• Constructing DataFrames from Dictionaries and Tuples
• Course Summary

Analyzing Data Using Python: Importing, Exporting, & Analyzing Data With Pandas

Course: 1 Hour, 23 Minutes

• Course Overview
• Importing and Exporting CSV Files
• Importing and Exporting Data in HTML and JSON Files
• Reading and Writing Excel Files Using DataFrames
• Performing Basic DataFrame Operations
• Computing Unique Values and Renaming Columns
• Sorting Data Based on Specific Columns
• Computing Basic Statistics
• Computing Univariate and Bivariate Statistics
• Course Summary

Analyzing Data Using Python: Analyzing Data Using Python: Filtering Data in Pandas

Course: 1 Hour, 26 Minutes

• Course Overview
• Performing Data Lookup Operations
• Leveraging the loc and iloc Functions
• Using the loc, iloc, at, and iat Functions to Filter Data
• Filtering Data Using Wildcards and Boolean Predicates
• Using the Query Function to Filter Data
• Manipulating Data Using Datetime Values
• Selecting and Dropping Columns
• Applying Advanced Techniques to Select and Drop Columns
• Course Summary

Analyzing Data Using Python: Cleaning & Analyzing Data in Pandas

Course: 1 Hour, 53 Minutes

• Course Overview
• Identifying Duplicates in Data
• Categorizing and Binning Data
• Computing Aggregations on Data
• Grouping and Aggregating Data1
• Viewing Data Using Pivot Tables
• Summarizing Data Using Pivot Tables
• Combining Data in DataFrames
• Implementing Inner Joins
• Implementing Left and Right Joins
• Performing Joins Using DataFrame Indexes
• Analyzing Time Series Data
• Course Summary