Graduate Conversion Program in Python Programming

  • Onsite and Online
  • Intakes: Jan, Apr, Jul, Oct
Course Description

This 12-module course offers a comprehensive introduction to Python, starting with essential syntax and foundational programming concepts before moving to real-world applications. Each module includes lectures, practical coding exercises and assignments to reinforce learning. By the end of the course, students will be able to create, troubleshoot and deploy Python programs and gain hands-on experience with Python libraries used in data manipulation and analysis.

The Graduate Conversion Program in Python Programming is designed for non-IT graduates with basic computer knowledge who wish to gain proficiency in Python, a versatile programming language widely used in data science, web development and automation. This course introduces fundamental programming concepts and problem-solving techniques, gradually progressing to more advanced topics such as data structures, file handling and libraries for data analysis. The program provides students with a practical understanding of Python, empowering them to pursue careers in tech, analytics or software development.

Module 1: Introduction to Python and Programming Basics

 
  • Overview: Introduction to Python, its applications and setting up the development environment.
  • Key Topics: Python syntax, variables, basic input/output, running scripts.
  • Practical Task: Write a simple “Hello, World!” program and basic calculations.
 
Module 2: Data Types and Variables 
  • Overview: Working with Python’s data types and variable assignments.
  • Key Topics: Integers, floats, strings, type conversions.
  • Practical Task: Create programs using different data types and perform basic operations.
 
Module 3: Control Structures 
  • Overview: Using loops and conditional statements to control program flow.
  • Key Topics: if, else, elif, for loops, while loops.
  • Practical Task: Write a program with loops and conditional logic for decision-making.
 
Module 4: Module 4: Functions and Modular Programming


 
  • Overview: Introduction to functions for code reusability.
  • Key Topics: Defining functions, parameters, return values, scope.
  • Practical Task: Create a modular program with multiple functions.
 
Module 5: Data Structures – Lists, Tuples and Dictionaries 
  • Overview: Introduction to common Python data structures.
  • Key Topics: Lists, tuples, dictionaries, indexing, and basic operations.
  • Practical Task: Manipulate data using lists and dictionaries.
 
Module 6: Working with Strings

 
  • Overview: String manipulation techniques for text-based data.
  • Key Topics: String methods, formatting, slicing and concatenation.
  • Practical Task: Write a program that processes text data.
 
Module 7: Introduction to Object-Oriented Programming (OOP) 
  • Overview: Basics of OOP in Python.
  • Key Topics: Classes, objects, attributes, methods.
  • Practical Task: Define a simple class and create instances.
 
Module 8: File Handling

 
  • Overview: Reading from and writing to files for data storage.
  • Key Topics: Open, read, write, append and file management.
  • Practical Task: Create a program that reads from and writes to text files.
 
Module 9: Error Handling and Debugging

 
  • Overview: Writing error-free programs with exception handling.
  • Key Topics: try, except, finally, debugging techniques.
  • Practical Task: Implement error handling in a program to manage user input errors.
 
Module 10: Introduction to Libraries and Modules

 
  • Overview: Using Python libraries to extend functionality.
  • Key Topics: Importing modules, using libraries (e.g., Math, Random).
  • Practical Task: Write a program using Math and Random libraries.
 
Module 11: Data Analysis with Pandas

 
  • Overview: Introduction to data analysis using Pandas.
  • Key Topics: DataFrames, data manipulation, data cleaning.
  • Practical Task: Load and manipulate a dataset using Pandas.
 
Module 12: Data Visualization with Matplotlib

 
  • Overview: Visualizing data with Python’s Matplotlib library.
  • Key Topics: Basic plots, histograms, scatter plots, data presentation.
  • Practical Task: Create visualizations for a dataset to communicate findings.
 
Assessment Methods
 
  • Coding Assignments: Practical exercises aligned with each module to reinforce understanding.
  • Quizzes: Periodic quizzes to evaluate knowledge of core concepts.
  • Final Project: A culminating project where students apply their skills to develop a Python program that solves a real-world problem.
 
    • Non-IT Graduates: Individuals from non-technical backgrounds who want to transition into tech-related roles.
    • Professionals Exploring Career Change: People aiming to shift to fields like data science, software development, or analytics.
    • Beginners in Programming: Anyone seeking a structured introduction to Python programming and its applications.

Upon completing this course, students will be able to:

  1. Write and debug Python code: Understand Python syntax, create variables, and debug programs.
  2. Use control structures effectively: Implement loops and conditional statements to manage program flow.
  3. Apply object-oriented programming (OOP) principles: Develop modular code using classes and objects.
  4. Work with data structures: Manipulate data using lists, dictionaries, and tuples.
  5. Utilize Python libraries for data analysis: Analyze and visualize data with popular libraries like Pandas and Matplotlib.

Prerequisites:

  • Basic understanding of computer operations (e.g., file management, internet browsing).
  • No prior programming knowledge required.
The delivery method for this certification is entirely online, requiring candidates to have access to a personal computer.

Simple English and Sinhala

60 Hours
3 Days per week, 2 Hours
Per Participant Fee: Rs 30,000/= 

How to Apply

  • You Apply

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  • We Connect

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  • You Get Ready

Once you’ve completed your application and connected with an admissions representative, you’re ready to create your schedule.

How To Apply

Your Application

Tell us a little about yourself and we’ll help with the rest. Our convenient online application tool only takes 10 minutes to complete.

Our Response

After you submit your application, an admissions representative will contact you and will help you to complete the process.

Your Journey

Once you’ve completed your application and connected with an admissions representative, you’re ready to create your schedule.

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