Data Science Foundations

Leverage your Python skills to learn about data science and how to identify, solve and answer problems using data! Our BUILD program will introduce learners to the basics of data science within a python programming environment. Builders will use Python libraries such as Numpy, Pandas, Jupyter Notebook, Matplotlib, and Scikit-Learn to perform structured data operations, visualize data, and even create simple machine learning algorithms. Our curriculum focuses on teaching these skills while also being mindful of data activism.

Data activism is when data skills are used to raise awareness or help address social justice issues. Through our socio-technical curriculum, builders will be exposed to many examples of technologists and activists who have gathered, analyzed or amplified data to address a topic of community concern. Learners will be exposed to some of the technologies that have been strategically used to disadvantage communities of color. They will deconstruct these technologies from both a social and technical perspective, then collaborate on ways to address some of the shortcomings of current technology.

Technical Content

Builders will use Python coding skills to introduce themselves to data science concept. They will combine these skills to understand, define, and demonstrate data analytics processes and algorithms.

Social Justice / Community

Learners will have weekly socio-technical dialogue that explores and discusses ethics in technology design. This program will focus on data activism and Jim Code.

Intersectional Tech Identity Development

Participants will hear from minorities working in tech during weekly career panels. They will develop relationships and professional skills through various career workshops and mentorship sessions.

Practical Skill Demonstration

Members will begin developing a portfolio of coding algorithms and data analytics samples through weekly assignments hosted on Replit and Google Classroom.

DISCLAIMER: This program introduces builders to concepts that would be found at various levels of a data science curriculum within college. However, we only aim to expose learners to various topics. We are not expecting them to gain mastery of the more complicated data science concepts such as supervised and unsupervised learning. We want our learners to grow their interest and they can expect to be equipped to further their knowledge in data science. However, our programs will not immediately make participants qualified for a data scientist job.

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