Hana Kafri

Conducted in-depth analysis on diverse operational datasets using SQL and Python to generate actionable insights that informed strategic logistics decisions. Developed a Power BI dashboard analysing carrier performance, integrating Python-based analyses and predictive ML model pipelines (using scikit-learn) to forecast logistics costs, enabling identification of optimal cost-saving opportunities. Designed and implemented model prediction pipelines combining preprocessing (scaling, encoding) and Random Forest regression to deliver cost forecasts directly in the dashboard for management use. Collaborating in developing AI agents by performing web scraping, data cleaning, and model training to build intelligent systems that enhance operational decision-making and automation.

Completed the Programming for Data Science Nanodegree including: - Mastered essential SQL functions and queries - Learned Python programming, including libraries such as Pandas and NumPy. - Gained comprehensive training to tackle real-world data challenges - Developed high-demand tech skills - Enhanced proficiency in terminal and Git

- Learned ASP.NET and programming with C# - Developed skills in creating MVC applications using ASP.NET - Developed efficient backend APIs. - Utilized CSS and HTML to display data returned from the APIs. - Worked with SQL databases for data storage and retrieval.

-- Implemented a shopping cart API using Django and the REST framework - Developed comprehensive CRUD functionality, enabling users to save, search, update, and delete items. -- Learned fundamental backend development concepts: - RESTful API design - Database management - Server-side scripting -- Gained hands-on experience in designing and implementing database schemas - Utilised SQL and ORM frameworks like SQLAlchemy