CS 495 - Data Science Project Practicum

5 CR

This course focuses on applying technological methodologies and theories to real-world scenarios within the realm of Data Science. Emphasizing hands-on experience, problem-solving, critical analysis, and the application of industry standard practices, alongside collaborative teamwork within the context of Data Science applications. Additionally, students have the option to apply for course credit equivalent to an internship, offering practical industry exposure.

Prerequisite(s): CS 410 with a C (2.0) or better and admission to the Computer Science, BS program, and permission of the program.

Course Outcomes

Apply technological methodologies specifically within the realm of data analysis, machine learning, and statistical modeling.
Apply knowledge and comprehension to assess data quality effectively, enabling dependable data-driven decision-making.
Design and implement solutions to address Data Science real-world challenges by evaluating and selecting appropriate technological applications for specific contexts.
Apply industry-standard practices for scaling Data Science solutions
Perform independent learning of new technologies and concepts relevant to Data Science, demonstrating adaptability and continuous skill development.
Work productively in a team environment, communicating appropriately with all team members.
Communicate findings effectively through reports and presentations.

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