Advanced Data Science Course - Stanza Academy

Stanza Academy

Advanced Data Science Course

Data is everywhere around us. We generate more data every 40 minutes than all of the data generated since the dawn of civilization until 2003. The ability to work with data, understand what it tells us, and use it in your communication has become an essential life and career skill.

Decisions that used to be straightforward are increasingly more complex and driven by data. Individuals across all disciplines need to constantly separate fact from friction. The need to analyze and interpret data has permeated every discipline — across engineering, business, finance, social sciences, humanities, and even journalism. Several leading academics now agree that the mathematics we teach in high school is rooted in the 1950s space race and needs to be updated to reflect the realities of the digital and information age of today.

2Sigma School takes an interactive approach to data exploration, rather than a lecture based approach. Our classes are hands-on and use several tools that are used by leading data scientists as well as higher education universities, as illustrated by the following video clip of a live session in a small cohort.

The Advanced Data Science online course is equivalent to a 1-semester college level course, adapted for high school. It combines three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand the phenomenon and draw conclusions? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design.

Data science is more than just a combination of programming and statistics. Effective data science requires understanding problem domains and correctly interpreting domain-specific approaches. The examples in this course are largely drawn from real-world data sets, and one of the main goals of this course is to develop the ability to apply analysis and prediction techniques to real-world scenarios.

This is an advanced course meant for students who have experience with Python programming or who have previously taken the AP Computer Science A class. At the end of the course, students will have a portfolio of their data science work to showcase their newly developed knowledge and understanding.

In order to maximize our time together during the live sessions, we use a flipped classroom model that includes pre-work for every class. This allows students to program with the support of an instructor during the class. The pre-work includes pre-recorded videos, online reading, and some programming practice.