• 10/28 Essay: To give you a better idea of what data science is and how is compares to other areas in the world of work read this 10-15 min article . Taxonomically, in academia, data science is a subfield of computer science. Personally, I see data science as a tool or a set of tools and methods that a researcher or practitioner of data science applies to data in a particular domain. This combination is their “craft”, in essence. I, for example, apply data science to geography in the context of international development. This means I use tools such as machine learning on data such as satellite imagery to help solve problems in the international development community. Data science is a domain that can be surprisingly hard to define given its broad applications and newness. I don’t necessarily think there’s one correct definition and, whatever it is, the field will continue to evolve with new technologies, new industries, and/or new issues. There’s also a question of skill ranges. Should the title of “data scientist” be reserved for those with doctoral degrees in the same way it is in physics, for example, and anyone below that is basically something else (like an analyst)?
• Notes on article
  • Data science projects have one of three purposes
    • Provide insight
    • Establish causality
    • Make predictions
  • These purposes align with the three major domains of data science
    • Data analysis
    • Statistics
    • Machine learning
  • “It’s possible to be solely a data analyst, statistician, or machine learning engineer. However, a data scientist is a person who can do all three.”
• Think about an area of study or field you care about (outside of your formal assignment topic), maybe the major you intend to choose. Based on what you read and know about data science and its related areas (data analysis, stats, and ML), briefly (1-2 paragraphs) write about how you think these disciplines could possibly be used in your field (it’s okay to think ambitiously). If methods are already being used, what are they and to what extent (if you know)? If you are a prospective data science major, what ideas do you have for how data science could be used in ways you believe they are currently not?

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• The topic I am looking at is biology, and specifically the human brain. The application of data science to studying the human brain can improve our understanding of people and how our minds work. Data analysis in studying the brain could mean recording brain signals and finding trends in those signals. Statistics can help to figure out the causes of trends, and machine learning models can be used to model the brain and predict what will happen when different stimuli are introduced. Data science can be used to model the entire human brain and be able to accurately predict what will happen or simulate a human mind.
• If we could map out the brain, we could learn more about what causes certain responses or even diseases in the brain, similar to how we use mappings of the human genome. Being able to predict how the brain would react, or mapping out the human brain to see exactly what would happen, would be a huge advancement for many reasons. It would help to create prosthetics for people with disabilities if the prosthetic could read the signals that the brain would normally send to that part of the body. It could also help doctors diagnose patients if their brain signals were a more accurate communication of pain than the patient’s own description. And Google would surely use this science to put ads in places where you’re sure to click on them.
• Of course, simulating the human brain is likely a feat that won’t be possible at any time in the near future. But we can use today’s technology to read signals from the brain. The application of data science, and more specifically, machine learning, can still help us predict how the brain works and maybe simulate it on a crude level.