Python Practical Programming

Categories: Programming and FrameWork

About Course

Master the essentials of Python programming and build a strong foundation in data handling, object-oriented programming (OOP), and real-world application development. This course takes you step by step from Python basics to advanced concepts, empowering you to write efficient, scalable, and reusable code.

You will learn how to work with variables, operators, loops, functions, modules, and packages, along with powerful data structures like lists, dictionaries, and tuples. Gain hands-on experience in file operations, exception handling, and database interactions, while exploring advanced features like regular expressions and OOP principles.

The course also introduces you to NumPy and Pandas, enabling you to efficiently analyze, manipulate, and manage data—skills essential for modern programming, data science, and machine learning.

By the end of this course, you’ll have the expertise to develop robust Python applications, handle data effectively, and apply OOP concepts to solve complex programming challenges.

Understand the fundamentals of Python programming for Machine Learning
Work with NumPy, Pandas, and Matplotlib for data analysis and visualization
Preprocess, clean, and prepare data for ML models
Build and evaluate supervised and unsupervised machine learning models
Implement popular algorithms like Linear Regression, Decision Trees, Random Forest, KNN, and Clustering
Work with Scikit-learn and TensorFlow basics for model building
Solve real-world business problems using ML techniques
Deploy ML models and understand their applications in industries

Course Content

Introduction to Python
This module introduces you to Python, its setup, and the foundational concepts like variables, operators, and code blocks. You’ll be able to write and execute your first Python program confidently.

Installation and Working with Python
Understanding Python Variables
Python Basic Operators
Understanding Python Blocks

Python Data Types
Explore Python’s data types and their operations. Learn how to store and manipulate data using numbers, strings, lists, and tuples.

Python Program Flow Control
Control the flow of your Python programs with conditionals and loops. Learn to iterate over data structures and control loop execution.

Python Functions, Modules, and Packages
Learn modular programming with Python functions, modules, and packages. Master reusable code and functional programming with lambdas.

Python String, List, and Dictionary Manipulations
Gain mastery over Python’s most powerful built-in data structures and their operations.

Python File Operations
Learn how to read, write, and manipulate files for handling configurations and logs.

Module 7: Python Object-Oriented Programming (OOPs)
Understand the fundamentals of OOP and apply them to build scalable, maintainable applications.

Module 8: Python Exception Handling
Protect your applications from crashes by managing runtime errors with exception handling.

Module 9: Python Database Interaction
Integrate Python with databases to build data-driven applications.

Module 10: Introduction to NumPy and Pandas
Master NumPy and Pandas for powerful data manipulation and analysis, preparing you for data science and machine learning.

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Python Practical Programming

About Course

What Will You Learn?

Course Content

Introduction to Python This module introduces you to Python, its setup, and the foundational concepts like variables, operators, and code blocks. You’ll be able to write and execute your first Python program confidently.

Installation and Working with Python

Understanding Python Variables

Python Basic Operators

Understanding Python Blocks

Python Data Types Explore Python’s data types and their operations. Learn how to store and manipulate data using numbers, strings, lists, and tuples.

Declaring and using Numeric Data Types: int, float, complex

Using String Data Type and String Operations

Defining List and List Slicing

Use of Tuple Data Type

Python Program Flow Control Control the flow of your Python programs with conditionals and loops. Learn to iterate over data structures and control loop execution.

Conditional Blocks using if, else, elif

Simple For Loops in Python

For Loop using ranges, string, list, and dictionaries

While Loops in Python

Loop manipulation using pass, continue, break, else

Programming using conditionals and loops

Python Functions, Modules, and Packages Learn modular programming with Python functions, modules, and packages. Master reusable code and functional programming with lambdas.

Organizing Python Code using Functions

Creating and Importing Modules

Working with External Modules

Understanding Packages

Powerful Lambda Functions

Programming with Functions and Modules

Python String, List, and Dictionary Manipulations Gain mastery over Python’s most powerful built-in data structures and their operations.

String In-Built Methods

List Manipulations with In-Built Functions

Dictionary Manipulations

Programming with Strings, Lists, and Dictionaries

Python File Operations Learn how to read, write, and manipulate files for handling configurations and logs.

Reading Config Files in Python

Writing Log Files in Python

Read Functions: read(), readline(), readlines()

Write Functions: write(), writelines()

Manipulating File Pointer with seek()

Programming with File Operations

Module 7: Python Object-Oriented Programming (OOPs) Understand the fundamentals of OOP and apply them to build scalable, maintainable applications.

Concepts of Class, Object, and Instances

Constructors, Attributes, and Destructors

Real-Time Use of Classes in Projects

Inheritance, Overloading, and Overriding

Adding and Retrieving Dynamic Attributes

Module 8: Python Exception Handling Protect your applications from crashes by managing runtime errors with exception handling.

Avoiding Code Breaks with Exceptions

Handling File Operation Errors

Debugging with Exception Handling

Module 9: Python Database Interaction Integrate Python with databases to build data-driven applications.

SQL Database Connection with Python

Creating and Searching Tables

Reading and Storing Config Information

Database Programming

Module 10: Introduction to NumPy and Pandas Master NumPy and Pandas for powerful data manipulation and analysis, preparing you for data science and machine learning.

NumPy Arrays and Operations

Indexing, Slicing, and Iteration

Reading/Writing Arrays to Files

Pandas Data Structures & Indexing

Reading/Writing CSV and Excel Files

Pandas Functions: ndim(), axes(), head(), tail()

GroupBy, Aggregation, Concatenation, Merging, Joining

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