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Duration 14 hours
Course Outline
Python Fundamentals for Data Tasks
- Installing Python and configuring the development environment
- Core language concepts: variables, data types, and control structures
- Creating and executing basic Python scripts
File Handling: CSV and Excel
- Reading and writing CSV files via the csv module and Pandas
- Managing Excel files using openpyxl/xlrd and Pandas
- Practical exercises: automating file conversion processes
Introduction to Pandas
- DataFrame essentials: creation, indexing, selection, and filtering
- Aggregation and grouping operations
- Standard cleaning tasks: handling missing values, duplicates, and type conversions
Introduction to Polars
- Polars concepts and performance metrics relative to Pandas
- Core DataFrame operations within Polars
- Case study: determining when to prefer Polars over Pandas
Advanced Data Transformation (Intermediate)
- Complex joins, window functions, and pivot operations in Pandas
- Optimized data processing patterns with Polars
- Chaining operations and memory usage optimization
Process Automation with Python
- Developing scripts to automate repetitive data tasks and ETL steps
- Scheduling scripts using OS or task schedulers
- Implementing logging, error handling, and notification systems
Packaging Scripts and Best Practices
- Building executables using PyInstaller or equivalent tools
- Project structuring, virtual environments, and dependency management
- Version control basics and workflow documentation
Hands-on Mini-Project
- End-to-end exercise: reading raw files, cleaning/transforming data, and generating outputs
- Automating the workflow and packaging it as a runnable script or executable
- Review and refinement based on peer feedback
Summary and Next Steps
Requirements
- Basic understanding of programming concepts or a strong willingness to learn
- Proficiency in using a command-line or terminal for installing packages
- Experience handling spreadsheet data (CSV/Excel)
Target Audience
- Data analysts and operations teams looking to automate data tasks
- Analytical engineers seeking lightweight ETL scripting solutions
- Professionals aiming to build practical Python-based 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.
