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Duration 14 hours
Course Outline
Python Fundamentals for Data Applications
- Installing Python and configuring the development environment
- Core language features: variables, data types, and control structures
- Developing and executing basic Python scripts
File Management: CSV and Excel
- Importing and exporting CSV files using the csv module and Pandas
- Processing Excel files with openpyxl/xlrd and Pandas
- Practical tasks: automating file format conversions
Getting Started with Pandas
- Core DataFrame concepts: creation, indexing, selection, and filtering
- Executing aggregation and grouping operations
- Standard cleansing tasks: managing missing values, duplicates, and data types
Getting Started with Polars
- Understanding Polars concepts and performance metrics relative to Pandas
- Executing fundamental DataFrame operations in Polars
- Practical scenario: determining when to prefer Polars over Pandas
Advanced Data Transformation (Intermediate Level)
- Executing complex joins, window functions, and pivots in Pandas
- Implementing efficient data processing patterns with Polars
- Chaining operations and optimising memory consumption
Workflow Automation with Python
- Developing scripts to automate repetitive data tasks and ETL stages
- Scheduling scripts via OS schedulers or task schedulers
- Implementing logging, error management, and notification systems
Script Packaging and Professional Standards
- Generating executables using PyInstaller or comparable tools
- Structuring projects, managing virtual environments, and handling dependencies
- Foundations of version control and documenting workflows
Practical Mini-Project
- End-to-end assignment: ingesting raw files, cleansing and transforming data, and generating outputs
- Automating the workflow and packaging it as an executable script or application
- Evaluation and refinement based on peer feedback
Conclusion and Future Directions
Requirements
- Familiarity with basic programming concepts or a strong desire to learn
- Confidence in using a command-line interface or terminal for installing packages
- Experience handling spreadsheet formats (CSV/Excel)
Target Audience
- Data analysts and operations teams looking to automate data tasks
- Engineering professionals seeking lightweight solutions for ETL scripting
- Professionals keen on implementing practical, Python-driven data workflows
Testimonials (2)
everything was perfect
Florin Vrincianu
Course - Python Programming Fundamentals
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
