IRL & Online Program
Enterprise Data Science Bootcamp
A comprehensive bootcamp covering statistics, classical ML, and big data tools for aspiring data scientists.
Hands-on Highlights
- Clean and process big data using PySpark
- Build an end-to-end customer churn prediction pipeline
- Develop interactive data dashboards using Streamlit
- Perform A/B testing and statistical significance analysis
Detailed Syllabus
Week 1-2
Data Engineering & SQL
- Advanced SQL for data analysis
- ETL pipelines and data warehousing
- Handling big data with PySpark
- Data cleaning and feature engineering
Week 3-4
Statistics & Experimentation
- Probability distributions and hypothesis testing
- Designing and analyzing A/B tests
- Causal inference basics
- Interpreting statistical significance (p-values)
Week 5-6
Classical Machine Learning
- Linear and Logistic Regression
- Decision Trees and Random Forests
- Gradient Boosting (XGBoost/LightGBM)
- Model evaluation metrics (ROC-AUC, F1-Score)
Week 7-8
Visualization & Deployment
- Data visualization with Plotly and Seaborn
- Building interactive dashboards with Streamlit
- Communicating insights to stakeholders
- Deploying a churn prediction model
Target Roles & Career Paths
Data Scientist
Machine Learning Analyst
Data Engineer
Product Data Scientist
These are the primary roles you will be equipped to apply for upon successful completion of the course and portfolio projects.