Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Python Essentials for Data Tasks
- Installing Python and configuring the development environment
- Core language concepts: variables, data types, and control flow structures
- Creating and executing basic Python scripts
File Management: CSV and Excel
- Reading and writing CSV files via the csv module and Pandas
- Handling Excel files using openpyxl/xlrd alongside Pandas
- Practical exercises: Automating file conversion processes
Getting Started with Pandas
- Foundations of DataFrames: creation, indexing, selection, and filtering
- Executing aggregation and grouping operations
- Standard cleaning tasks: addressing missing values, duplicates, and type conversions
Introduction to Polars
- Understanding Polars concepts and its performance benefits relative to Pandas
- Performing basic DataFrame operations within Polars
- Use-case analysis: Determining when to prefer Polars over Pandas
Advanced Data Transformation (Intermediate Level)
- Executing complex joins, window functions, and pivot operations in Pandas
- Implementing efficient data processing patterns with Polars
- Optimizing memory usage through operation chaining
Automating Processes with Python
- Developing scripts to streamline repetitive data tasks and ETL steps
- Scheduling scripts using OS or task schedulers
- Implementing logging, error handling, and notification systems
Script Packaging and Best Practices
- 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 exercise: Ingesting raw files, cleaning and transforming data, and generating outputs
- Automating the workflow and packaging it as an executable script or binary
- Evaluation and refinement based on peer review
Summary and Next Steps
Requirements
- Fundamental knowledge of programming concepts or a strong motivation to learn
- Proficiency in using a command-line or terminal for installing packages
- Prior experience working with spreadsheet formats (CSV/Excel)
Target Audience
- Data analysts and operations teams aiming to automate data tasks
- Analyst engineers looking for lightweight ETL scripting solutions
- Professionals seeking to implement 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.
