Beginner's Guide to Data Science

It’s predicted that demand for data scientists will grow 36% from 2021 to 2031, according to the Bureau of Labor Statistics. If you’ve been considering a career in data science, that’s a pretty promising stat.

Join us for a free, 2-hour class, to get hands-on practice with the basics and see if you’ve got what it takes to transition into the field of Data Science.

You’ll learn the fundamentals of data science and how different industries are applying its predictive power to improve their bottom line. Then, get hands-on practice with predictive models using a real-world dataset. Bonus: there will be time at the end for live Q&A with the instructor.

We’ll see you in class.

You’ll leave this class with:

• An understanding of what data science is and some of its broader industry applications
• Basic knowledge of the differences between supervised and unsupervised machine learning algorithms.
• Practice with quantitative, data-driven analysis
• Confidence to continue learning data science

• This is an entry level class, so no prior knowledge is necessary.
• We’ll send a Zoom link to your email the day of class.
• Note: your mic and camera will be off for the duration of the class.
• A recording will be shared via email after filling out our in-class survey.

Charis Loveland works at AWS as a business development manager on the cloud intelligence team specializing in artificial intelligence and machine learning. She has a decade and a half of experience in product management, AI, data analytics, new product introduction, file and hardware storage, and software development. After launching a crowdsourcing platform for Azure ML at Microsoft, Charis founded Rue La La's data science team, creating and executing a roadmap and strategy for personalization and customer sub-segmentation. Charis co-founded an ML startup and has taught several business courses at General Assembly as well as online courses about data science at MIT, Dartmouth, and Columbia. Charis serves as a coding instructor, mentor, and advocate for early STEM education and volunteers for several nonprofits that help promote greater diversity in the technology industry.