Take off on a data-driven journey with 'Soaring Through Data: An Intro to Python for Data Analysis.'

This 100-minute session is your pre-flight checklist for mastering Python's role in data analytics.
We'll start at the runway with the basics of Python syntax and programming constructs.
Ascend into the clouds as we explore essential data structures like lists and NumPy arrays.
Reach cruising altitude with the Pandas library, your cockpit for data manipulation. Navigate through data cleaning techniques and set your coordinates for basic yet powerful data analysis methods.
Finally, prepare for landing with a Q&A session, ensuring you're ready to pilot your own data projects.
Buckle up and prepare for takeoff into the world of Python for data analysis.

Target Audience - those attendees that are interested in understanding what Python is and how to use it.
The data set will be aviation themed.
This session hasn't been delivered previously, but in my previous life I've taught Python within the GCSE and A Level syllabus in the UK.

The session will be broken down into these areas:
Part 1: Introduction (10 mins)
• Brief on Python's importance in data analysis (3 mins)
• Agenda overview (2 mins)
• Required tools: Python, Jupyter Notebook (5 mins)
Part 2: Basics of Python (15 mins)
• Syntax, variables, and data types (5 mins)
• Control structures: loops, if-else (5 mins)
• Functions and libraries (5 mins)
Part 3: Data Structures (10 mins)
• Lists and dictionaries (5 mins)
• NumPy arrays (5 mins)
Part 4: Pandas Library (20 mins)
• DataFrames and Series (5 mins)
• Data import/export (5 mins)
• Basic operations: filter, sort, groupby (10 mins)
Part 5: Data Cleaning (15 mins)
• Handling missing data (5 mins)
• Data transformation (5 mins)
• Data visualization: Matplotlib/Seaborn basics (5 mins)
Part 6: Basic Analysis (15 mins)
• Descriptive statistics (5 mins)
• Correlation and basic inference (5 mins)
• Simple linear regression (5 mins)
Part 7: Q&A and Wrap-up (15 mins)
• Questions (10 mins)
• Summary and next steps (5 mins)