Data Science - Course Curriculum
Master the modern data stack with our comprehensive 7-module program
MODULE 1
Python, NumPy & Pandas
What You'll Learn
- Python programming
- Data structures
- NumPy arrays
- Pandas DataFrames
- Data cleaning
- Data manipulation
- Exploratory Data Analysis
Tools
- Python
- NumPy
- Pandas
- Jupyter Notebook
MODULE 2
Statistics
What You'll Learn
- Descriptive statistics
- Probability
- Sampling
- Hypothesis testing
- Confidence intervals
- Correlation
- Regression basics
Tools
- Python
- Excel
MODULE 3
Machine Learning & Scikit-learn
What You'll Learn
- Supervised Learning
- Unsupervised Learning
- Regression
- Classification
- Clustering
- Decision Trees
- Random Forest
- Ensemble Learning
- Model Evaluation
Tools
- Scikit-learn
- Python
MODULE 4
SQL & Power BI
What You'll Learn
- Data extraction
- SQL queries
- Data visualization
- Dashboard creation
- Business reporting
Tools
- SQL
- Power BI
MODULE 5
AI & Cloud
What You'll Learn
- AI fundamentals
- Generative AI basics
- Cloud AI services
- Model hosting
- Cloud deployment
- Responsible AI
Tools
- AWS
- Azure
- ChatGPT
- AI Services
MODULE 6
Feature Engineering & Deployment
What You'll Learn
- Feature selection
- Feature transformation
- Hyperparameter tuning
- Model deployment
- API basics
- Model monitoring
- Production pipelines
Tools
- Scikit-learn
- Python
- Cloud Platforms
MODULE 7
Business Case Studies
What You'll Learn
- Customer Churn Prediction
- Banking Analytics
- Healthcare Analytics
- Finance Analytics
- Retail Analytics
- Demand Forecasting
- Fraud Detection
- End-to-end ML projects
Career Opportunities
Major Tools Covered
Python
NumPy
Pandas
Scikit-learn
SQL
Power BI
AWS
Azure
ChatGPT
Machine Learning Libraries
Real-time Projects
Credit Card Fraud Detection
House Price Prediction
Sales Forecasting
Demand Forecasting
Stock Price Prediction
Recommendation System
