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Duration 14 hours
Course Outline
Python Fundamentals for Data Work
- Installing Python and configuring the development environment
- Core language concepts: variables, data types, and control structures
- Writing and executing basic Python scripts
File Handling: CSV and Excel
- Reading and writing CSV files using the csv module and Pandas
- Handling Excel files with openpyxl/xlrd and Pandas
- Practical exercises: automating file conversion processes
Getting Started with 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 traits compared to Pandas
- Basic DataFrame operations in Polars
- Case study: determining when to prefer Polars over Pandas
Advanced Data Transformation (Intermediate)
- Complex joins, window functions, and pivot operations in Pandas
- Efficient data processing patterns using Polars
- Chaining operations and optimizing memory usage
Process Automation with Python
- Developing scripts to automate repetitive data tasks and ETL steps
- Scheduling scripts using OS schedulers or task schedulers
- Logging, error handling, and notification systems
Script Packaging and Best Practices
- Creating executables using PyInstaller or similar tools
- Project structuring, virtual environments, and dependency management
- Basics of version control and documenting workflows
Practical Mini-Project
- End-to-end task: reading raw files, cleaning and transforming data, and generating outputs
- Automating the workflow and packaging it as a runnable script or executable
- Reviewing and refining based on peer feedback
Summary and Next Steps
Requirements
- Basic understanding of programming concepts or a strong willingness to learn
- Proficiency in using the command line or terminal for installing packages
- Experience working with spreadsheets (CSV/Excel)
Target Audience
- Data analysts and operations staff looking to automate data tasks
- Analytical engineers seeking lightweight ETL scripting solutions
- Professionals interested in 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.
