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Duration 14 hours
Course Outline
Python Essentials for Data Operations
- Installing Python and configuring the development environment
- Core language concepts: variables, data types, and control structures
- Developing and executing basic Python scripts
Managing Files: CSV and Excel
- Reading and writing CSV files via the csv module and Pandas
- Handling Excel files using openpyxl/xlrd and Pandas
- Practical drills: automating file format conversions
Foundations of Pandas
- DataFrame fundamentals: creation, indexing, selection, and filtering
- Executing aggregation and grouping operations
- Standard cleaning procedures: addressing missing values, duplicates, and type casting
Introduction to Polars
- Polars core concepts and performance metrics relative to Pandas
- Basic DataFrame operations within the Polars framework
- Scenario-based analysis: determining when to prefer Polars over Pandas
Advanced Data Transformation (Intermediate Level)
- Complex joins, window functions, and pivot operations in Pandas
- Optimized data processing patterns using Polars
- Operation chaining and memory usage optimization
Automating Processes with Python
- Scripting the automation of repetitive data tasks and ETL stages
- Scheduling scripts via OS or task schedulers
- Implementing logging, error management, and notification systems
Script Packaging and Best Practices
- Generating executables using PyInstaller or comparable tools
- Project architecture, virtual environments, and dependency control
- Version control fundamentals and workflow documentation
Practical Mini-Project
- End-to-end exercise: ingesting raw files, refining data, and generating outputs
- Automating the workflow and packaging it as a runnable script or executable
- Review and refinement based on peer insights
Conclusion and Future Pathways
Requirements
- A foundational understanding of programming concepts or a strong motivation to learn
- Confidence in using the command line or terminal for installing packages
- Proficiency in handling spreadsheet formats (CSV/Excel)
Target Audience
- Data analysts and operations teams looking to automate data workflows
- Analytics engineers requiring lightweight ETL scripting solutions
- Professionals seeking to implement practical Python-based data processes
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.
