Part 1 :- Python Programming

Understanding Programming and Its Core Concepts
Why Python?
Compiler vs. Interpreter
Virtual Environments
Setting Up Python
Command Line Basics
Your First Python Code
Code Organization with Comments
Introduction to Variables
Data Types in Python
Rules for Creating Variables
Working with String Variables
Handling Quotations in Strings
String Features
String Slicing and Indexing
String Functions and Methods
Variable Injection in Strings

Numeric Data Types
Mathematical Operations
Comparison Operators
Boolean Variables
Working with Lists
List Features
List Built-in Functions
List Concatenation and Replication
Modifying Lists
Nested Lists
Advanced List Tools
Comparing Data Structures
Set Features
Set Built-in Functions
Joining Sets
Tuple Features
Modifying Tuples

Creating Dictionaries
Dictionary Features
Keys and Values
Modifying Dictionaries
Merging Dictionaries
Dictionary Built-in Methods
Functions and Their Purpose
Steps to Create a Function
Function Arguments
Local vs. Global Variables
Returning Values from Functions
Nested Functions
Lambda Functions
Understanding Control Flow and How Applications Work
Conditional Statements
While Loop
For Loop Iterates over a sequence
Try and Except Statements
Logical Operators (or, and, in) in Control Flow enhance decision-making.

OOP “Object oriented programming”

Difference Between Normal Programming and OOP
OOP Main Concepts
Encapsulation
Abstraction
Inheritance
Polymorphism

Files & OS

File Handling in Python
Reading Files
Writing to Files
System Commands with Python
What are Modules and How They Work
Built-in Modules
Renaming and Importing from Modules

Part 2:- Database

Data Types: Understand the different types of data
Database Types: Explore the various types of databases
What is a Relational Database
Database Data Types
MySQL Installation
MySQL Constraints (Rules)
Most Important SQL Commands
Connection Between Python and Databases
Dealing with Databases Using SQL in Python
Relations Between Tuples and Database Inputs/Outputs

Part 3:- Math & Calculus & Linear Algebra

calculus
Number Types
Sets & Intervals
Functions
Summations & Exponents
Logarithms
Limits, Derivatives & Integrals

Linear Algebra
Scalar, Vector, and Matrix
Special Types of Matrices
Operations on Matrices
Matrix Transpose
Matrix Inverse
Solving Systems of Linear Equations
NumPy

Part 4:- Statistics

Introduction
Descriptive and Inferential Statistics
Variables and Types of Data
Measures of Central Tendency
Measures of Variation
Measures of Position
Exploratory Data Analysis
Sample Spaces and Probability
The Addition Rules for Probability
The Multiplication Rules and Conditional Probability
Probability Distributions
Properties of the Normal Distribution
The Standard Normal Distribution
Applications of the Normal Distribution
Correlation

Part 5:- Data Analysis

Visualize data using different types of graphs
Ploting libs like Matplotlib , Seaborn and plotly
Pandas: Learn how to manipulate and analyze data efficiently
Missing Values
Outliers
Inconsistent Data
Data Conflict
Label Encoding
Entity Identification
Redundancy
Duplication
Normalization

Part 6:- Machine Learning

Regression
Linear Regression
Best Fit Line
Residuals and Squared Errors
Gradient Descent
Overfitting and Variance
The Correlation Coefficient
Model Analysis
K-Nearest Neighbors (KNN)
Decision Trees
Random Forest
Evaluation
Mean Squared Error
Mean Absolute Error
R^2

Classification
Logistic Function
Multivariable Logistic Regression
K-Nearest Neighbors (KNN)
Decision Trees
Random Forest
SVM
Evaluation
Confusion Matrices
Recall
Precision
Receiver Operator Characteristics/Area Under Curve

Clustering
K-Means
Agglomerative Clustering
DBSCAN
Evaluating

Part 7:- Deep Learning

Simple Neural Network “ANN”
Activation Functions
Forward Propagation
Backpropagation
Weight and Bias Derivatives
Computer Vision
Convolutional Neural Networks (CNN)
Image Classification
Object Detection
YOLO (You Only Look Once)
Natural language processing “NLP”
Recurrent neural network “RNN”
Hugging Face