Advanced Diploma in Data Science & Machine Learning – Course Modules

Python Programming for Data Science
Python Setup (Anaconda, Jupyter)
Variables, Data Types & Operators
Conditional Statements (If-Else)
Loops (For, While)
Functions & Lambda Expressions
Numerical Computing with NumPy
NumPy Arrays vs Python Lists
Array Creation Methods
Indexing, Slicing & Reshaping
Mathematical & Statistical Operations
Broadcasting & Vectorized Operations
Data Manipulation with Pandas
Series & DataFrame Creation
Import Data (CSV, Excel)
Data Inspection (info, describe, head)
Indexing & Selection (loc, iloc)
Filtering & Sorting Data
Data Cleaning & Preprocessing
Handling Missing Values
Duplicate Detection & Removal
Outlier Detection (IQR, Z-Score)
Fixing Inconsistent Data
Data Type Conversion
Data Visualization & Exploratory Analysis
Matplotlib Fundamentals
Line, Bar, Scatter & Histogram Charts
Multi-Chart Dashboards
Seaborn Visualizations
Correlation Matrix Analysis
Machine Learning Foundations
Introduction to Machine Learning
Supervised vs Unsupervised Learning
ML Workflow & Pipeline
Train-Test Split
Model Evaluation Basics
Supervised Learning Algorithms
Linear Regression
Polynomial Regression
Logistic Regression
Decision Trees
Random Forest
Unsupervised Learning & Optimization
K-Means Clustering
Feature Scaling Techniques
Feature Selection Basics
Cross Validation
Hyperparameter Tuning
Statistics & Probability for Data Science
Population vs Sample
Mean, Median & Mode
Variance & Standard Deviation
Probability Fundamentals
Conditional Probability
SQL for Data Science
SQL Fundamentals
SELECT, WHERE, ORDER BY
Aggregate Functions
GROUP BY & HAVING
JOIN Operations
Model Deployment
Deployment Concepts
Building Apps with Streamlit
Loading Trained Models
User Input Interfaces
Basic Deployment Workflow
Capstone Projects & Portfolio
Classification Project
Regression Project
Data Cleaning Project
Visualization Dashboard Project
SQL Data Analysis Project
GitHub Portfolio Development
Final Assessment
And many more