Data Analyst → Data Scientist Bridge Program: From Business Analytics to Applied Machine Learning & Predictive Intelligence

1. Course Overview The Data Analyst → Data Scientist Bridge Program is designed for experienced Data Analysts who want to transition into Data Science roles. This program focuses on closing the skill gap between: - Reporting & dashboarding AND - Machine learning, modeling, and advanced analytics You will move from descriptive and diagnostic analytics to predictive and prescriptive modeling using industry-standard tools and real-world datasets. This is a practical, applied, business-focused data science program — not purely theoretical. 2. Who This Course Is For - Intermediate or Senior Data Analysts - BI Analysts with strong Python skills - Analytics professionals transitioning into Data Science - Professionals preparing for ML Engineer (entry-level) roles - AI-driven analytics professionals expanding into modeling 3. Course Outcomes (What You Will Gain) By the end of this program, participants will be able to: ✅ Build supervised and unsupervised ML models ✅ Perform feature engineering ✅ Conduct model evaluation & tuning ✅ Apply advanced statistical techniques ✅ Work with large datasets ✅ Deploy simple ML models ✅ Perform end-to-end data science workflows ✅ Understand model governance & monitoring ✅ Present technical findings to business stakeholders ✅ Build a portfolio-ready data science project 4. Skills You Will Develop - Advanced Python for data science - Machine learning modeling - Feature engineering - Model validation & tuning - Exploratory data analysis (advanced) - Probability & statistics for ML - Model deployment basics - Version control for ML projects - Data storytelling for technical audiences - Responsible AI & model governance 5. Course Structure & Duration - Total Duration: 14 Weeks - Total Learning Hours: ~130–150 hours - Format: Live + Coding Labs + ML Workshops + Capstone - Weekly Commitment: 8–12 hours