Description:
Exam Syllabus (Chapter Wise):Chapter 1: Introduction to Python
- What is Python?
- History of Python
- Features of Python
- Advantages of using Python
- Setting up the Python environment
- Running a Python program
- Variables and Naming Conventions
- Data Types: Numbers, Strings, Booleans
- Type Conversion and Type Checking
- Operators: Arithmetic, Assignment, Comparison, Logical, Bitwise
- Conditional Statements: if, else, elif
- Looping Statements: for loop, while loop
- Loop Control Statements: break, continue, pass
- Nested loops and conditional statements
- Defining and calling a function
- Function Arguments: Positional, Keyword, Default and Variable-length arguments
- Returning values from a function
- Modules: Creating and importing modules
- Standard Libraries
- Classes and Objects
- Data Hiding and Encapsulation
- Inheritance and Polymorphism
- Abstract classes and Interfaces
- Opening and Closing Files
- Reading and Writing to Files
- Binary Files and File Modes
- Working with Directories
- What are exceptions?
- Handling exceptions using try and except blocks
- Multiple except blocks and else clause
- Raising exceptions
- What are regular expressions?
- Pattern matching and substitution
- Meta-characters and Character Classes
- Regular Expression functions in Python
- Connecting to a database
- Creating tables and inserting data
- Retrieving data from tables
- Updating and Deleting data
- SQL Injection and Prevention
- Lists
- Tuples
- Dictionaries
- Sets
- Arrays
- Introduction to NumPy and SciPy
- Arrays in NumPy
- Mathematical Operations on Arrays
- Linear Algebra using SciPy
- Introduction to Pandas
- Data Structures in Pandas
- Data Manipulation using Pandas
- Data Analysis using Pandas
- Introduction to Matplotlib
- Types of Plots: Line, Bar, Scatter, Histogram, etc.
- Customizing Plots
- Subplots and Figures
- Introduction to Flask
- Creating a Flask Application
- Routing and Requests
- Templates and Forms
- Introduction to Django
- Creating a Django Application
- Models, Views, and Templates
- Admin Interface
- Introduction to Machine Learning
- Scikit-Learn Library
- Linear Regression
- Classification
- Clustering
- Introduction to NLP
- Text Preprocessing
- Text Classification and Sentiment Analysis
- Named Entity Recognition
- Introduction to Tkinter
- Creating a GUI Application
- Widgets and Layouts
- Event Handling
- Multithreading and Concurrency
- Networking
- GUI Toolkits: PyQt, Kivy, etc.
- Debugging and Profiling
- Secret!