Academic Excellence

Comprehensive foundation in analytics using R programming. Mastered data wrangling, exploratory data analysis, statistical modeling, and advanced visualization techniques essential for biotech and healthcare research applications.

Real-world healthcare project with New Jersey clinic analyzing sleep health data. Applied advanced SQL techniques, database design principles, and data mining to explore correlations between sleep patterns and health outcomes.

Deep dive into statistical foundations including probability distributions, sampling theory, central limit theorem, hypothesis testing, and confidence intervals for robust biostatistical analysis and research design.

Advanced statistical modeling techniques including multiple regression, ANOVA, chi-square testing, and sophisticated model selection methods for data-driven decision making in research and clinical environments.

Team leadership analyzing Netflix streaming data. Created interactive dashboards and compelling visualizations using Tableau, Power BI, and Python to effectively communicate complex insights to diverse stakeholders.

Extensive Microsoft Excel training for business analytics. Mastered advanced techniques including pivot tables, scenario analysis, VBA automation, and sophisticated financial models for enterprise-level decision making.

Developed comprehensive machine learning classification models for healthcare applications. Built predictive model for diabetes diagnosis achieving 94% accuracy using advanced ML algorithms and feature engineering.

Large-scale big data analytics using Yelp dataset. Implemented advanced data mining techniques, real-time dashboards, AI-powered insights, and NLP for business intelligence and predictive analytics.

12-week industry collaboration with Wyman's (major US blueberry producer) on market analytics and product strategy for new protein blend launch. Applied comprehensive business analytics to agricultural biotechnology.

Advanced predictive modeling course with weekly hands-on projects. Mastered regression techniques, classification algorithms, ensemble methods, model selection, hyperparameter tuning, and performance optimization for biotech applications.

Comprehensive study of AI systems architecture and intelligent agent design. Explored multiple agent architectures including simple reflex, model-based, goal-based, utility-based, and learning agents. Covered search algorithms, knowledge representation, planning systems, and machine learning foundations.

Critical examination of ethical AI implementation, data privacy regulations, and governance frameworks. Studied GDPR, HIPAA compliance, bias detection and mitigation, fairness in ML models, explainable AI, and responsible data stewardship in healthcare and enterprise contexts.

Advanced big data technologies and distributed computing frameworks. Worked with Hadoop ecosystem, Spark for large-scale data processing, NoSQL databases, data lakes, cloud data warehousing, and scalable ETL pipelines for enterprise analytics.

Enterprise data warehousing architecture and advanced SQL for business intelligence. Dimensional modeling, star and snowflake schemas, OLAP operations, query optimization, indexing strategies, and building scalable data warehouse solutions.

Culminating project synthesizing all learned concepts. Will develop a comprehensive data science solution addressing a real-world healthcare or biotech challenge, demonstrating mastery of the end-to-end analytics pipeline from data acquisition to deployment.