Data Analysis for Health Food Competitive Positioning

The main goal for the project is to conduct a comprehensive analysis of open data from Health Canada to determine the competitive positioning for the launch of CaffeBerry's new health food product. This will involve several different steps for the learners, including: - Gathering and analyzing data on similar health food products in the market. - Conducting a comparative analysis of CaffeBerry's product with existing health food options.

Optimizing Event Networking with Data Science

PopIn aims to enhance networking opportunities for event hosts on platforms like Meetup.com, Eventbrite.com, and Lu.ma. The goal of this project is to determine the ideal event sizes and locations that maximize networking potential. To achieve this, learners will scrape event data from these platforms and apply data science and analytics techniques to identify patterns and insights. The project will involve data collection, cleaning, analysis, and visualization to provide actionable recommendations for event hosts. This will help PopIn tailor their tool to better serve their users and improve networking outcomes. Key tasks include: - Scraping event data from Meetup.com, Eventbrite.com, and Lu.ma. - Cleaning and preprocessing the collected data. - Applying data science techniques to analyze the data. - Visualizing the results to identify optimal event sizes and locations.