If you are aspiring to break into the field of data science and are looking for resources and wisdom to guide your learning, then this is the place for you! Welcome to HoyAlytics’ Medium publication. Whether you want to improve your programming skills, learn statistical concepts, or understand the high-level basics and use cases for data science, we’ve got you covered!
As a group of undergraduate students at Georgetown University, we’re here to inspire you to join us in our journey of learning data science together. In our experiences, we’ve found it difficult to discover accessible data science resources at the undergraduate level, as topics are either reserved within graduate programs or are gatekept by their requirements of intense programming and mathematics. But don’t panic — we aim to build a passionate learning community while staying true to our mission of welcoming all levels of technical ability. We want to help kickstart your learning journey, so you can emerge with a foundational understanding of data science and prepare to enter the field!
Why is data science so important to learn?
We believe this growing discipline has a great chance to be socially impactful, and we hope we can inspire you to solve our future’s problems through application of your newfound skills. Self-driving cars, early and rare disease detection, and optimal natural resource allocation are just a few examples of what can be achieved from the intersection of mathematics, computer science, and creative problem-solving. Banking, media, healthcare, government, sports — every industry requires intelligence from information, and we’re excited about data science as its revolutionary tool. No matter your interest, there’s always a problem that can be solved using data. We are optimistic about what our field can contribute, and you should be too!
So what can you expect from us? Here are the types of content you will see from our publication…
In the News: Our Friday newsletter, containing a curated list of industry news with our personal commentary. We want to keep you informed of industry trends, and we encourage you to think critically to measure both the current practicality and future potential of new advances in data science.
Conceptual Articles: We aim to introduce and explain fundamental data science concepts at their most basic level, with corresponding resources to guide your learning from “ground-zero.”
How To Articles: Our guides on essential skills, tools, and procedures to build a deeper understanding of data science. Whether it is best practices for selecting a proper model, establishing a professional code style, or interpreting results, we aim to draw upon our experiences and knowledge base to help you gain practical skills needed to become confident in your work.
Personal Projects: We hope to introduce you to the data science workflow by taking real-world data sets and walking you through our thought process in both code and prose. We hope our work inspires you to pursue your own data science projects, where you can use your coding skills to rethink your way through a problem, or deeply explore something you’ve always had a hunch about.
Op-Ed Pieces: There’s a common misconception that technical people are not active participants beyond their specialized skills. Given the growing ambitions of industry-leading firms, it is imperative that the next wave of technical professionals develop strong ethical principles about the implications of industry practices. We want to call to your attention key developments in the field that may go largely unnoticed.
…with so much more to come in the future!
Ready to get started?
The best way to stay active in our community is to subscribe to our publication, set up email notifications to receive our content in your inbox, and give us a clap to support our work!
We invite you to follow us on Twitter (@HoyAlytics). DM us with a question or comment to let us know what you think!
You can also contact us at email@example.com for more professional requests or inquiries.
We hope our publication motivates you to develop your passion in data science. Learning data science is hard enough. Let’s do this together!
Will Calandra is a senior at Georgetown University majoring in Operations and Information Management with dual minors in Statistics and Computer Science. He is the Chief Analytics Officer at HoyAlytics after previously serving as the club’s VP of Technology. In his free time, he can be found religiously following his sports teams, searching for new puppy friends, or expanding his palate at D.C.’s restaurants.
Spencer Karp is a Junior at Georgetown University majoring in Operations and Analytics, with minors in Mathematics and Computer Science. He previously worked as a Project Manager at HoyAlytics before becoming VP of Analytics. Spencer is an avid sports fan, and enjoys watching the Mets and Tottenham Hotspur. He also enjoys crosswords (you’ll have to ask him for his Times Mini leaderboard link).
Annika Lin is a junior at Georgetown University majoring in Computer Science and Economics, with a minor in Mathematics. She became VP of Analytics at HoyAlytics after serving as Director of Curriculum. In her free time, she enjoys playing tennis, karaoke, and exploring French culture.
Sameer Tirumala is a sophomore at Georgetown majoring in Operations and Analytics, with minors in Statistics and Computer Science. He became VP of Analytics for HoyAlytics after serving as VP of Curriculum. He enjoys running, chess, soccer (Brazil and Chelsea), video games, and anime.