Executive Development Programme in Data Wrangling with Python and Pandas

This course is designed for business executives and data professionals aiming to enhance their data management skills using Python and Pandas. Participants will learn essential data wrangling techniques to clean, transform, and prepare data for analysis, directly applicable in their roles.

By the end of the program, attendees will be proficient in using Python and Pandas for data manipulation, capable of handling real-world data challenges efficiently, and equipped with the skills to drive data-informed decision-making in their organizations.

1. 1. Introduction to Data Wrangling: Learners will understand the importance of data wrangling and explore foundational concepts. They will gain the practical skills to identify and describe data types and structures.
2. 2. Data Cleaning Basics: This module covers the basics of cleaning data, including handling missing values, removing duplicates, and correcting data format errors. Learners will practice these skills on real-world datasets.
3. 3. Data Transformation Techniques: Learners will study various data transformation techniques such as merging, joining, and reshaping data. Practical skills include manipulating data to meet analysis requirements.
4. 4. Handling Text Data with Python: This module focuses on working with text data, including text cleaning, normalization, and text processing using Python libraries. Learners will gain skills in text preprocessing for natural language processing tasks.
5. 5. Advanced Data Filtering and Selection: In this module, learners will delve into advanced filtering and selection techniques to subset data based on complex conditions. Practical exercises will help them refine their data handling skills.
6. 6. Data Validation and Quality Assurance: Learners will learn how to validate data and ensure its quality through various techniques. Practical skills include implementing checks and creating data validation pipelines.
7. 7. Working with Time Series Data: This module covers the specific challenges and techniques for working with time series data. Learners will gain hands-on experience in analyzing and manipulating temporal data.
8. 8. Introduction to Data Visualization: In this module, learners will learn how to visualize data effectively using Python libraries. They will practice creating and interpreting visualizations to communicate data insights.
9. 9. Advanced Data Wrangling Projects: Learners will work on real-world projects that require advanced data wrangling skills. This module focuses on applying learned techniques to complex datasets and solving practical business problems.
10. 10. Final Project and Presentation: For the capstone project, learners will apply all learned skills to a comprehensive data wrangling challenge. They will present their findings and solutions in a professional setting.