This course will provide learners with comprehensive knowledge of Python, starting from the basics and progressing to proficient data analysis skills. It will commence with an introduction to Python, covering fundamental topics such as syntax, variable declaration, loops, conditions, and various predefined modules. Advancing further, the course will delve into interacting with files, including Excel sheets, and data exchange. A solid understanding of object-oriented programming (OOP) and inheritance will be provided to facilitate deeper exploration of Pandas, NumPy, Matplotlib, and Seaborn modules. Practical application of the knowledge gained in the course will culminate in the creation of a real-life project.

Introduction to Python Programming

• Syntax
  
• Variables
  
• Inputs

Control Flow

• Loops
  
• Conditions

Functions and Modules

• Functions
  
• Modules

Object-Oriented Programming (OOP)

• Classes and Objects
  
• Inheritance
  

Data Analysis with Python

• Introduction to DataFrames
  
• Reading CSV Files
  

Cleaning Data

• Handling Empty Cells
  
• Removing Data Duplication

Data Visualization

• Plotting Data
  
• Customizing Plots
  

On completion of this course, learners will be able to:

• Write clean Python code and develop small projects proficiently.
  
• Utilize object-oriented programming (OOP), inheritance, and polymorphism to create and interact with objects, effectively passing data between them.
  
• Apply OOP principles to integrate data analysis modules in Python, enabling efficient manipulation and analysis of data sets.
  
• Retrieve data from Excel sheets and perform customized processing, facilitating the transformation and injection of data into new Excel sheets.
  
• Demonstrate mastery of course concepts by leveraging acquired knowledge to design and execute a comprehensive data analysis project encompassing all necessary steps.
  

This course takes a hands-on, practical and interactive approach. Concepts will be explained and illustrated with real-world examples. Complex topics are broken down into smaller, manageable parts, allowing learners to focus on mastering one aspect at a time before moving on to the next. Live coding and practical application with Python is done from the outset. Participants are encouraged to have a proactive learning approach. Regular question and answer sessions, and sharing experience and results of the project work afford a collective leaning opportunity for all participants.