Python Programming

Python Programming Course Module

Python Programming Training by Technofine24

Welcome to Technofine24’s Python Programming Training! As the best training institute for Python, we provide a comprehensive program designed for both beginners and experienced developers. Our training ensures you master Python, one of the most versatile and in-demand programming languages.

Why Learn Python?

  • Easy to Learn
  • Versatile
  • Strong Community Support

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Technofine24, recognized as the **best Python training institute**, offers a training program that covers everything from basic to advanced Python concepts, ensuring you gain both theoretical knowledge and practical experience.

Key Features:

  • Comprehensive Curriculum
  • Expert Instructors
  • Interactive Learning
  • Flexible Options
  • Support and Resources
  • Certification

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1. Introduction To Python

  1. Installation and Working with Python
  2. Understanding Python variables
  3. Python basic Operators
  4. Understanding the Python blocks.

3. Introduction To Variables

  1. Variables, expression condition and function
  2. Global and Local Variables in Python
  3. Packing and Unpacking Arguments
  4. Type Casting in Python
  5. Byte objects vs. string in Python
  6. Variable Scope

5. Control Structure & Flow

  1. Statements – if, else, elif
  2. How to use nested IF and Else in Python
  3. Loops
  4. Loops and Control Statements.
  5. Jumping Statements – Break, Continue, pass
  6. How to use Range function in Loop?
  7. Programs for printing Patterns in Python
  8. How to use if and else with Loop
  9. Use of Switch Function in Loop
  10. How to use nested Loop in Python
  11. Use If and Else in for and While Loop
  12. Examples of Looping with Break and Continue Statement

7. List

  1. What is a List?
  2. Advantage of using a list.
  3. Creation of a list.
  4. Different operations on a list using inbuilt functions.
  5. Operations on a list using user-defined functions.
  6. Indexing and Slicing in list.
  7. Implementation of list data structure in the form of a micro-project.
  8. Using List Comprehension.

9. Dictionary

  1. What is a Dictionary?
  2. Advantage of using a Dictionary.
  3. Creation of a Dictionary.
  4. Different operations on a Dictionary using inbuilt functions.
  5. Operations on a Dictionary using user-defined functions.
  6. Implementation of Dictionary data structure in the form of a mini-project.
  7. Ordered Dictionary

11. Strings

  1. What is a String?
  2. Advantage of using a String.
  3. Creation of a String.
  4. Different operations on a String using inbuilt functions.
  5. Operations on a String using user-defined functions.
  6. Implementation of String data structure in the form of a micro-project.

13. File Handling

  1. What is File Handling?
  2. Different modes in file handling.
  3. Opening a file in different modes.
  4. Reading, Writing and Appending to a file.
  5. Configuring the current working directory for files.
  6. List Directories and Files.
  7. Making new directory.
  8. Changing the file directory.

15. Data Analysis - NUMPY

  1. Introduction to Numpy – Numerical Python
  2. Importing Numpy
  3. Introduction to Arrays
  4. Operations on an array using Numpy
  5. Two Dimensional Arrays
  6. Operations on 1-D and 2-D Arrays
  7. Logical Operations with Arrays

17. Data Analysis - MATPLOTLIB

  1. Introduction to Matplotlib.
  2. Importing Matplotlib.
  3. Working on different types of charts using matplotlib.
  4. Exporting the chart as an image.
  5. Customization of the charts using matplotlib.
  6. Implementing pandas and matplotlib to create interactive visualizations.

19. Statistics using Python

  1. Introduction to Descriptive statistics.
  2. Importing Inferential statistics.
  3. Understanding the data using mean, median ,mode, standard deviation.
  4. Using python’s statistics module to understand the data.

2. Python Keywords and Identifiers

  1. Python Keyword and Identifiers
  2. Python Comments, Multiline Comments.
  3. Python Indentation
  4. Understating the concepts of Operators
    1. Arithmetic
    2. Relational
    3. Logical
    4. Assignment
    5. Membership
    6. Identity

4. Data Types

  1. Declaring and using Numeric data types
  2. Using string data type and string operations
  3. Understanding Non-numeric data types
  4. Understanding the concept of Casting and Boolean.
  5. Strings
  6. List
  7. Tuples
  8. Dictionary
  9. Sets

6. Functions, Modules and Packages

  1. What is a Function?
  2. Function Call and Return Statement
  3. Arguments in a function : Required, Default, Positional and Variable-length
  4. Lambda Functions
  5. Scope and lifetime of a variable in python
  6. Recursion and recursive functions
  7. Organizing python codes into functions and modules
  8. Importing the modules
  9. Random Functions
  10. Map, Filter and Reduce Functions

8. Tuple

  1. What is a Tuple?
  2. Advantage of using a Tuple.
  3. Creation of a Tuple.
  4. Different operations on a Tuple using inbuilt functions.
  5. Operations on a Tuple using user-defined functions.
  6. Indexing and Slicing in Tuple.
  7. Implementation of Tuple data structure in the form of a micro-project.

10. Sets

  1. What is a Set?
  2. Advantage of using a Set.
  3. Creation of a Set.
  4. Different operations on a Set using inbuilt functions.
  5. Operations on a Set using user-defined functions.
  6. Implementation of Set data structure in the form of a micro-project.
  7. Frozen Sets.

12. Exceptional Handling

  1. What is Exceptional Handling?
  2. Error, Bug and Exception.
  3. Python Errors and built-in exceptions.
  4. Try, Except and Finally.
  5. Catching exceptions in Python.
  6. Raising Exceptions.
  7. Using else with Python Try and Except Block.

14. Database Handling

  1. What is a database?
  2. Introduction to mysql database and its queries using xampp.
  3. Establishing the connection using mysql-connector.
  4. Inserting the data in database using python.
  5. Reading and fetching the data from database.
  6. Updating the data in the database tables using python.

16. Data Analysis - PANDAS

  1. Introduction to Pandas.
  2. Importing Pandas.
  3. Working with excel and csv files using pandas.
  4. Working with dataframes and series.
  5. Data cleaning and data preprocessing using pandas.
  6. Writing to excel or csv files using pandas.
  7. Getting the data from web urls.

18. Data Analysis - SEABORN

  1. Introduction to Seaborn.
  2. Importing Seaborn.
  3. Working on different types of charts using Seaborn.
  4. Exporting the chart as an image.
  5. Customization of the charts using seaborn.
  6. Implementing pandas and Seaborn to create interactive visualizations.
  7. Working on advanced functions of seaborn.

19. EDA - Exploratory Data Analysis

  1. Introduction to EDA.
  2. Data Pre-Processing steps.
  3. Working on different types of unstructured data using python to explore them.
  4. EDA – Projects
    1. Covid Data
    2. IPL Data
    3. Analysis of Olympics dataset
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