CS-301: Advanced Honors Seminar: Data Science & Machine Learning 78607 CompSci - BWK

78607 Grade Level: 11th - 12th Prerequisite: CS-201: AP Computer Science Principles or CS-202 AP Computer Science A. Departmental approval required.

One of the hottest fields in tech, Data Science has virtually limitless potential, spanning across industries, roles, and functions. Data science provides a set of methods and tools for assembling, scrubbing, analyzing and extracting insights from big data sets that may be highly structured or unstructured.

This course provides a comprehensive introduction to Data Science and Machine Learning using tools such as Jupyter Notebook, NumPy, and Pandas to analyze real-world datasets, to identify patterns and relationships in data with statistical modeling techniques such as linear & logistic regression, decision trees, and random forests. The curriculum is designed to enhance computational and inferential thinking while emphasizing collaborative teamwork for building projects that are based on real-life Data Science problems. The class will explore Data Science and Machine Learning, its diverse applications; common terminologies; core, descriptive and inferential statistics; correlation; hypothesis testing; confidence intervals & margin of error; pattern recognition via supervised and unsupervised learning, and much more!

Students will build their own portfolio of open-source GitHub projects using both built-in and custom-built data types to create expressive and computationally robust Data Science projects and predictive machine learning models using Python and Scikit-learn.