Kurzusleírás
Python Fundamentals for Data Tasks
- Installing Python and setting up the development environment
- Language fundamentals: variables, data types, control structures
- Writing and running simple Python scripts
File Handling: CSV and Excel
- Reading and writing CSV files using the csv module and Pandas
- Working with Excel files using openpyxl/xlrd and Pandas
- Practical exercises: automating file conversions
Introduction to Pandas
- DataFrame basics: creation, indexing, selection, and filtering
- Aggregation and grouping operations
- Common cleaning operations: missing values, duplicates, and type conversions
Introduction to Polars
- Polars concepts and performance characteristics compared to Pandas
- Basic DataFrame operations in Polars
- Use-case example: when to choose Polars over Pandas
Advanced Data Transformation (Intermediate)
- Complex joins, window functions, and pivot operations in Pandas
- Efficient data processing patterns with Polars
- Chaining operations and optimizing memory usage
Process Automation with Python
- Writing scripts to automate repetitive data tasks and ETL steps
- Scheduling scripts with OS schedulers or task schedulers
- Logging, error handling, and notifications
Packaging Scripts and Best Practices
- Creating executables with PyInstaller or similar tools
- Project structuring, virtual environments, and dependency management
- Version control basics and documenting workflows
Hands-on Mini-Project
- End-to-end task: read raw files, clean and transform data, produce outputs
- Automate the workflow and package as a runnable script or executable
- Review and improvements based on peer feedback
Summary and Next Steps
Követelmények
- Basic familiarity with programming concepts or willingness to learn
- Comfort using command-line or terminal for package installation
- Experience working with spreadsheets (CSV/Excel)
Audience
- Data analysts and operations staff automating data tasks
- Analytical engineers seeking lightweight ETL scripting
- Professionals interested in practical Python-based data workflows
Vélemények (5)
Az a tény, hogy több gyakorlati gyakorlatunk van, több hasonló adat felhasználásával, mint amit projekteinkben használunk (műholdképek raszteres formátumban)
Matthieu - CS Group
Kurzus - Scaling Data Analysis with Python and Dask
Gépi fordítás
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding. Képzeltem, hogy a tréner nagyon tudós volt, és bátorsággal válaszolt a kérdésekre, hogy tisztázza a megértést.
Jenna - TCMT
Kurzus - Machine Learning with Python – 2 Days
Gépi fordítás
Jó előkészület és szakértelem a tréner részéről, tökéletes angol kommunikáció. A kurzus gyakorlati volt (gyakorlatok + használati példák megosztása).
Monika - Procter & Gamble Polska Sp. z o.o.
Kurzus - Developing APIs with Python and FastAPI
Gépi fordítás
A magyarázat
Wei Yang Teo - Ministry of Defence, Singapore
Kurzus - Machine Learning with Python – 4 Days
Gépi fordítás
Trainer a saját tempójához igazítva fejleszti ki a képzéseket.
Farris Chua
Kurzus - Data Analysis in Python using Pandas and Numpy
Gépi fordítás