TECH 07 — Breaking Into Data Science
Quarter: Spring
Instructor(s): Grace Tang
Date(s): Apr 7—Jun 2
Class Recording Available: Yes
Class Meeting Day: Mondays
Class Meeting Time: 7:00—8:50 pm (PT)
Please Note: No class on May 26
Tuition: $500
Refund Deadline: Apr 9
Unit(s): 1
Status: Open
Quarter: Spring
Day: Mondays
Duration: 8 weeks
Time: 7:00—8:50 pm (PT)
Date(s): Apr 7—Jun 2
Unit(s): 1
Tuition: $500
Refund Deadline: Apr 9
Instructor(s): Grace Tang
Recording Available: Yes
Status: Open
Please Note: No class on May 26
This unique course will provide a gentle introduction to the vast data science landscape to help students determine if it suits them and discover which data science roles might be most fitting. Using real-world open data sets and open source tools, students will practice foundational data science skills, such as sourcing open data sets; ingesting, cleaning, and processing data; troubleshooting; and finally, telling a compelling story through the interpretation of data. They'll also explore case studies on topics such as data visualization, predictive modeling, and A/B testing. Students will build a starter portfolio to showcase their work, using free online resources such as GitHub, W3Schools, Kaggle, and data.gov.
Prior programming experience in Python or R is recommended but not required. Supplementary resources will be provided to students without programming experience for self-study.
GRACE TANG
Data Scientist
Grace Tang received a PhD in neuroscience from Stanford, where she studied how personality traits, emotions, and external stimuli affect decision-making. Since graduating in 2014, she has been a data scientist at various companies, including a 10-person startup, Uber, Grab, and Netflix. She is passionate about helping newcomers break into data science, especially from nontraditional fields like the social sciences. Textbooks for this course:
There are no required textbooks; however, some fee-based online readings may be assigned.