Python for Advance
Overview
Course Objective
By the end of this 3-day course, participants will be able to:
Understand fundamental programming concepts and how they apply to Python.
Write and execute Python programs using basic syntax and programming structures.
Utilize Python’s core data types, variables, collections, and operators effectively.
Develop reusable code through functions, modules, and packages.
Handle files and perform basic input/output operations.
Implement object-oriented programming concepts such as classes, attributes, and methods.
Use Jupyter Notebook for interactive development and data analysis tasks.
Perform matrix processing with NumPy and carry out basic data analysis using Pandas.
Visualize data using Matplotlib with various chart types and customization features.
Who Should Attend
This course is suitable for:
Beginners with little to no programming experience who want to start learning Python.
Professionals looking to switch careers or upskill in data science, software development, or automation.
Students or fresh graduates seeking to strengthen their foundation in programming.
Individuals interested in exploring Python for web development, data analysis, or scientific computing.
Prerequisites
Participants should have:
Basic computer literacy and familiarity with using a PC/laptop.
An interest in programming and problem-solving.
No prior programming experience is required.
Training Calendar
Intake
Duration
Program Fees
Module
Module 1 - AN INTRODUCTION TO PROGRAMMING
• What Is Algorithm
• What Is Programming
• What Is Program
• Machine Language
• Programming Language
• What Is Translator
Module 2 - AN INTRODUCTION TO PYTHON
• Brief History of Python
• Python Versions
• Installing Python
• Environment Variables
• Installing Pycharm
• Python Documentation
• Hello world from python
• Modes Of Programming
Module 3 - BASIC PYTHON SYNTAX
• Identifiers
• Reserved Words
• Lines and Indentation
• Comments Managing research
Module 4 - VARIABLES AND COLLECTIONS IN PYTHON
• Numbers
• Python Lists
• Python Tuples
• Python Dictionaries
• Python Sets
• Copying
• Python Strings
• String formatting
• Regular Expressions
Module 5 - PYTHON OPERATORS
• Arithmetic Operators
• Comparison (Relational) Operators
• Assignment Operators
• Logical Operators
• Membership Operators
• Operators Precedence
Module 6 - LANGUAGE COMPONENTS
• Decision Making
• The if Statement
• The if else Statement
• For Loop
• While Loop
• Break And Continue
Module 7 - FUNCTIONS IN PYTHON
• Defining Your Own Functions
• Parameters
• Function Documentation
• Passing Collections to a Function
• Variable Number of Arguments
• Scope
• map
• Fillter
• Lambda
Module 8 - MODULES AND PACKAGES
• What Are Modules
• Importing Modules
• Aliasing
• Importing Set Of Element From A Module
• Namespace
• What Are Packages
• dir function
• help function
Module 9 - EXCEPTIONS
• What Is Exception
• Exception Types
• Try Except Component
• Handling General Exception
• Handling Specific Exception
• Raise
Module 10 - INPUT AND OUTPUT
• Introduction
• Access Modes
• Writing Data to a File
• Reading Data From a File
• Read Functions
• What Is CSV
Module 11 - OBJECT ORIENTED PROGRAMMING (OOP)
• What is OOP
• Why OOP Is Important
• Classes
• Attributes
• Methods
• Constructor
Module 12 - JUPYTER NOTEBOOK
• What Is Jupyter Notebook
• Why Jupyter Notebook Is Important
• Installing Jupyter Notebook
• Main Components of Jupyter Notebook
• Edit Mode And Command Mode
• Exporting Notebook Documents
Module 13 - MATRIX PROCESSING (NUMPY MODULE)
• What is Numpy
• 1D and 2D Array
• Array Arithmetic
• Special Functions
• Math Functions
• Slicing, Filtering, and Transforming Array
Module 14 - DATA ANALYSIS (PANDAS MODULE)
• What is Pandas
• Pandas Data Types
• Selecting/Slicing Data
• Import/Export Data – CSV, Excel
• Filtering Data
• Process Missing Data and Duplicated Data
• Joining Data from Different Sources
• Transforming Data
• Aggregating Data
Module 15 - JUPYTER NOTEBOOK
• What is Matplotlib
• Line Graph
• Bar Graph
• Pie Chart
• Histogram
• Scatter Plot
• Graph Attributes
• Text Annotation
FAQs
General Questions:
Q: What is the Python for Beginners course about?
This 3-day course introduces learners to Python programming from the ground up. It covers basic programming concepts, Python syntax, variables, data structures, operators, control flow, functions, and object-oriented programming. The course also includes practical hands-on exercises using Jupyter Notebook and introduces key Python modules like NumPy and Pandas for data processing and analysis. The aim is to equip learners with the foundational skills to write Python programs and handle basic data analysis tasks.
Q: Who should attend this course?
This course is suitable for beginners with little to no programming experience, as well as professionals looking to switch careers or upskill in Python. It is also ideal for students or fresh graduates who wish to build a solid foundation in programming and for anyone interested in exploring Python for web development, data analysis, or automation.
Q: What are the prerequisites for this course?
Participants should have basic computer literacy and familiarity with using a PC or laptop. No prior programming experience is required, but an interest in programming and problem-solving is essential.
Q: How long is the course?
The course spans 3 days and is delivered through instructor-led sessions, focusing on interactive learning and hands-on practice.
Q: What key topics are covered in this course?
The course covers fundamental programming concepts, Python syntax, variables, data types, operators, control flow, functions, modules and packages, exception handling, input/output operations, object-oriented programming, data processing with NumPy and Pandas, and basic data visualization with Matplotlib.
Q: Will I receive a certification after completing the course?
Yes, participants will receive a certificate of completion, validating their proficiency in Python programming at the beginner level.
Program Content & Skills:
Q: What foundational Python concepts will I strengthen in this course?
You’ll reinforce key Python fundamentals such as working with data types, control flow, sequences, mappings, file I/O, and program structure. This will ensure you have a solid understanding of the basics before moving on to more complex tasks.
Q: How does the course help me apply Python to real-world problems?
Through practical hands-on exercises, you’ll build Python programs that handle tasks like working with files, processing data, and interacting with operating systems. These real-world applications will prepare you for roles in data science, web development, automation, and more.
Q: What skills will I develop in managing and structuring Python applications?
You’ll learn to organize your code effectively using functions, modules, and packages. The course will cover object-oriented programming, handling exceptions, and creating maintainable code. You’ll also explore basic testing and debugging techniques to ensure your applications run smoothly.
Q: Will I learn how to work with different data and systems in Python?
Yes, you’ll work with core Python data structures such as lists, dictionaries, and sets. You’ll also manipulate strings, work with regular expressions, and perform basic data analysis with tools like NumPy and Pandas, giving you a broad understanding of how to handle various data types.
Q: How does this course prepare me for using Python professionally?
By covering essential concepts like functions, file handling, object-oriented programming, and libraries such as NumPy and Pandas, this course lays a strong foundation for professional Python use. Whether you’re automating tasks or processing data, you’ll gain the skills necessary for real-world Python development.
Submit your interest today !
