Super Data Science: ML & AI Podcast with Jon Krohn 477: How to Thrive as an Early-Career Data Scientist
Jun 8, 2021
Sidney Arcidiacono, a computer science student at Make School and an intern at Greenlight Biosciences, shares her passion for utilizing AI in healthcare. She reveals her insights into graph theory and graph convolutional networks, diving into how they can revolutionize data science. Sidney offers practical advice for beginners, emphasizing the importance of discipline and networking in building a data science career. Her journey showcases the blend of technical skills and personal growth needed to thrive in the evolving landscape of AI and healthcare.
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Choosing Make School
- Sydney chose Make School for its applied, project-based computer science program, focusing on practical skills.
- The accelerated two-year bachelor's degree and data science specialization aligned with her career goals.
From Phlebotomy to AI
- Sydney Archidiakono, initially pursuing a medical career, became disillusioned with traditional healthcare's limitations.
- Working as a phlebotomist exposed her to patient accessibility gaps, inspiring her to explore AI's potential in healthcare.
Graph Theory's Importance
- Graph theory, describing nodes and edges, helps understand data relationships and networks like molecules or maps.
- It's crucial for analyzing non-Euclidean data, which traditional convolutional neural networks struggle with.
