Pandas cleaning & preprocessing hands-on

Description

This practical session focuses on real-world data cleaning and preprocessing using Pandas. Participants will work hands-on with messy datasets, applying essential techniques to transform raw data into clean, structured, and ready-to-use formats.

Indicative Duration: 2 training hours
*Duration is adjusted based on the final scope and the target audience.

Scope

Learning Objectives

Upon completion of the course participants will be able to:

1. Load, explore, and audit datasets using Pandas DataFrames.
2. Handle missing, duplicate, and inconsistent data effectively.
3. Apply data type conversions, renaming, filtering, and indexing.
4. Perform feature engineering and column transformations with Pandas.
5. Prepare datasets for analysis or machine learning workflows.

Target Audience

• Roles: Data Analysts, Junior Data Scientists, BI Developers, Python Programmers
• Seniority: Entry-level to Mid-level professionals working with data preparation tasks

Prerequisite Knowledge

• Basic Python programming skills
• Familiarity with Pandas syntax (e.g., DataFrame operations) is helpful but not required

Delivery Method

Sessions can be delivered via the following formats:

• Live Online – Interactive virtual sessions via video conferencing
• On-Site – At your organization’s premises
• In-Person – At Code.Hub’s training center
• Hybrid – A combination of online and in-person sessions

The training methodology combines presentations, live demonstrations, hands-on exercises and interactive discussions to ensure participants actively practice AI in realistic work scenarios.