Module 1. Introduction to Programming

Concepts:

• What is programming?
• How software works (Input → Process → Output)
• Compilation vs Interpretation

Real-world:

• ATM machine → Input (PIN) → Process (verify) → Output (cash)

Module 2. Python Basics

Topics:

• Variables & Data Types (int, float, string, boolean)
• Type conversion
• Input/Output functions

Practicals:

• Take user input and calculate age
  Temperature converter

Module 3. Control Flow

Topics:

• if, elif, else
• Nested conditions
• Logical operators (AND, OR, NOT)

Real-world:

• Loan approval system

Module 4. Loops

Topics:

• for loop
• while loop
• break, continue, pass

Practicals:

• Print patterns
• Multiplication tables

Module 5. Data Structures

Topics:

• List (mutable)
• Tuple (immutable)
• Dictionary (key-value)
• Set (unique values)

Practicals:

• Store student marks
• Remove duplicates

Module 6. Functions

Topics:

• Function creation
• Parameters & return
• Default arguments

Practicals:

• Calculator using functions

Module 7. File Handling

Topics:

• Read/write files
• CSV handling

Project:

• Student Record System (save data in file)

Module 1. Advanced Python

Topics:

• Lambda functions
• map(), filter()
• List comprehensions

Real-world:

• Filter customers with salary > 50k

Module 2. OOP (Object-Oriented Programming)

Topics:

• Class & Object
• Inheritance
• Encapsulation
• Polymorphism

Practicals:

• Bank system simulation

Module 3. DSA Basics

Topics:

• Searching (Linear, Binary)
• Sorting (Bubble, Merge)
• Time Complexity (Big-O)

Real-world:

• Google search → optimized search algorithm

Module 4. SQL Basics

Topics:

• Database & Tables
• SELECT, INSERT, UPDATE, DELETE
• WHERE, ORDER BY

Module 5. SQL Advanced

Topics:

• Joins (Inner, Left, Right)
• Group By, Having
• Subqueries

Project:

• Library Management System (Python + SQL)

Module 1. NumPy

Topics:

• Arrays
• Vector operations
• Broadcasting

Real-world:

• Image = matrix of pixels

Module 2. Pandas Basics

Topics:

• Series & DataFrame
• Reading CSV, Excel
• Indexing & Filtering

Module 3. Data Cleaning

Topics:

• Handling missing values
• Duplicate removal
• Data formatting

Real-world:

• Customer database with missing phone numbers

Module 4. Data Transformation

Topics:

• GroupBy
• Merge & Join
• Pivot tables

Project:

• Sales Data Analysis
• Find top-selling products
  Monthly revenue

Module 1. Probability

Topics:

• Sample space
• Events
• Bayes Theorem

Real-world:

• Spam email detection probability

Module 2. Statistics

Topics:

• Mean, Median, Mode
• Variance, Standard Deviation
• Normal Distribution

Module 3. Hypothesis Testing

Topics:

• Null hypothesis
• p-value
• Confidence interval

Real-world:

• Testing new marketing strategy success

Module 4. Data Visualization

Tools:

• Matplotlib
• Seaborn

Charts:

• Bar, Line, Pie, Histogram
  Heatmap

Module 5. BI Tools

Topics:

• Power BI
• Tableau

Project:

• Customer Dashboard (interactive)

Module 1. ML Introduction

Topics:

• Supervised vs Unsupervised
• Training vs Testing

Module 2. Regression

Topics:

• Linear Regression
• Multiple Regression

Real-world:

• Predict house price

Module 3. Model Evaluation

Topics:

• MAE, MSE, RMSE
• R² score

Module 4. Feature Engineering

Topics:

• Feature selection
• Scaling (Normalization)

Project:

• House Price Prediction

Module 1. Classification

Topics:

• Logistic Regression
• KNN
• SVM

Real-world:

• Spam vs Not Spam

Module 2. Tree Models

Topics:

• Decision Trees
• Random Forest
• Gradient Boosting

Module 3. Imbalanced Data

Topics:

• SMOTE
• Oversampling

Module 1. Neural Networks

Topics:

• Neuron
• Activation functions (ReLU, Sigmoid)
• Backpropagation

Module 2. Deep Learning Frameworks

Tools:

• TensorFlow
• PyTorch

Module 3. CNN (Computer Vision)

Topics:

• Image processing
• Convolution layers

Project:

• Image classifier

Module 4. NLP

Topics:

• Tokenization
• Stopwords
• Sentiment Analysis

Module 5. Transformers

Tools:

• Hugging Face

• Flask
• Streamlit

• Amazon Web Services
• EC2, S3

• Git
• GitHub

• Resume building
• Mock interviews
• Portfolio creation