Datacast Episode 14: Overcoming Impostor Syndrome with Conor Dewey

Datacast Episode 14: Overcoming Impostor Syndrome with Conor Dewey

Conor Dewey is a data scientist at Squarespace who spends his time thinking about growth and engagement. He frequently shares insights from his experience interviewing at top companies. More generally, he offers resources and advice on Medium and Github in the hopes of ‘open sourcing’ his journey to data science. Conor also manages a weekly data science newsletter with 1000+ subscribers.

Datacast Episode 13: Transition From Academia to Data Science with Martina Pugliese

Datacast Episode 13: Transition From Academia to Data Science with Martina Pugliese

Martina is a physicist and works as Data Science Lead at Mallzee, based in Edinburgh (Scotland). She loves looking at data regardless of the topic and area and believes the most enjoyable thing in Data Science is analyzing your data, finding the one you need for your question, and producing facts out of it. Throughout her education and job experience, she worked with data in epidemic dynamics, linguistics, and fashion. She also loves producing hand-crafted data visualizations and keeps studying and improving, whether it’s about Machine Learning or leadership topics.

An Introduction to Big Data: Distributed Data Processing

An Introduction to Big Data: Distributed Data Processing

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

An Introduction to Big Data: Decision Trees

An Introduction to Big Data: Decision Trees

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

An Introduction to Big Data: Clustering

An Introduction to Big Data: Clustering

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

An Introduction to Big Data: Itemset Mining

An Introduction to Big Data: Itemset Mining

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

An Introduction to Big Data: Data Cleaning

An Introduction to Big Data: Data Cleaning

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

Datacast Episode 12: Data Science in Consulting with Jim Leach

Datacast Episode 12: Data Science in Consulting with Jim Leach

Jim Leach is a data scientist, originally from the North of England, but now based in Atlanta, Georgia. After studying chemistry at university, Jim joined the consulting firm KPMG and began his career as a data analyst. He later returned to university, taking a sabbatical to study for a Master in Business Analytics at Imperial College, London. In his work, he is a passionate R user and developer and enjoys thinking about data visualization and how to communicate effectively using data. In his free time, he enjoys board games, music, cooking, and being outdoors.

An Introduction to Big Data: Data Integration

An Introduction to Big Data: Data Integration

This semester, I’m taking a graduate course called Introduction to Big Data. It provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. In an effort to open-source this knowledge to the wider data science community, I will recap the materials I will learn from the class in Medium. Having a solid understanding of the basic concepts, policies, and mechanisms for big data exploration and data mining is crucial if you want to build end-to-end data science projects.

Biologically-Inspired AI: Ant Colony Optimization, Bats, and Flower Pollination Algorithms

Biologically-Inspired AI: Ant Colony Optimization, Bats, and Flower Pollination Algorithms

There have been significant advances in recent years in the areas of neuroscience, cognitive science, and physiology related to how humans process information. This semester, I’m taking a graduate course called Bio-Inspired Intelligent Systems. It provides broad exposure to the current research in several disciplines that relate to computer science, including computational neuroscience, cognitive science, biology, and evolutionary-inspired computational methods.