Item number: 90829001
Python for Data Science: Analyzing Data Using Python Training
Item number: 90829001
Python for Data Science: Analyzing Data Using Python Training
159,00
192,39 Incl. tax
Order now and start the best online E-Learning Training Python for Data Science: Analyzing Data Using Python today. 365 days of training when it suits you.
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Python for Data Science: Analyzing Data Using Python 2024 E-Learning
This training provides a comprehensive introduction to Python's capabilities in data science and data analysis. It covers essential Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn, guiding learners through data cleaning, manipulation, visualization, and analysis. Participants will learn to import, process, and visualize datasets to derive insights, and the training includes hands-on projects to apply these skills in real-world scenarios.
Ideal for beginners or those with some coding experience, this course is designed to build a solid foundation for anyone looking to pursue data science, analytics, or machine learning using Python.
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
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
| Language | English |
|---|---|
| Qualifications of the Instructor | Certified |
| Course Format and Length | Teaching videos with subtitles, interactive elements and assignments and tests |
| Lesson duration | 12:09 Hours |
| Progress monitoring | Yes |
| Access to Material | 365 days |
| Technical Requirements | Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge. |
| Support or Assistance | Helpdesk and online knowledge base 24/7 |
| Certification | Certificate of participation in PDF format |
| Price and costs | Course price at no extra cost |
| Cancellation policy and money-back guarantee | We assess this on a case-by-case basis |
| Award Winning E-learning | Yes |
| Tip! | Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform. |
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