AI and Data Science Projects
Welcome to my portfolio! Here, you’ll find a showcase of the topics I teach and the projects I guide my students through — from Python programming, Data Science, and Machine Learning to Deep Learning and Generative AI. Each project reflects a hands-on approach to applying cutting-edge technologies for solving real-world problems and developing strong analytical and AI-driven thinking skills.
Project 1: Power BI Dashboard Development
My Role: Adjunct Faculty Data Scientist
I guided students through the complete process of developing interactive dashboards using Power BI. The project focused on teaching data visualization principles, data modeling, DAX functions, and storytelling with data. I mentored learners in connecting multiple data sources, transforming raw data into actionable insights, and designing professional dashboards aligned with industry standards. Through this project, students gained hands-on experience in translating business problems into analytical visual solutions.
Project 2: Generative AI using Microsoft Copilot
My Role: Adjunct Faculty Data Scientist
I led students in exploring the practical applications of Generative AI through Microsoft Copilot. The project focused on integrating AI-assisted tools to enhance productivity, automate tasks, and generate intelligent content across platforms like Excel, Word, and PowerPoint. I guided learners in understanding prompt engineering, ethical AI use, and workflow automation with Copilot. Through this hands-on project, students developed a strong foundation in leveraging generative AI technologies to solve real-world business and data challenges.
Project 3: Python for Data Science
My Role: Adjunct Faculty Data Scientist
I trained students in applying Python for real-world data science workflows, covering essential libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn. The project emphasized data collection, cleaning, exploration, and visualization, enabling learners to transform raw data into meaningful insights. I guided students through end-to-end problem-solving using Python-based analytics, including building predictive models and interpreting outputs. This project helped students strengthen their programming logic, analytical thinking, and ability to use Python as a core tool in data-driven decision-making.
Project 4 : Azure Cloud for Data Science Certification
My Role: Adjunct Faculty Data Scientist
I guided students in leveraging Microsoft Azure Cloud to prepare for Data Science certifications covering key domains such as Machine Learning, Natural Language Processing (NLP), and Computer Vision. The project focused on teaching students how to utilize Azure Machine Learning Studio, manage datasets, build and deploy models. I mentored learners in applying cloud-based tools to design scalable data science solutions, helping them gain both practical experience and the technical knowledge required to achieve industry-recognized certifications.
