Applied Machine Learning in Data Science

Catalog description

3 hours. This course immerses students in learning essential techniques in data acquisition, cleaning, transforming, and exploratory data analysis (EDA) with a focus on practical applications. Through interactive case studies, students will gain proficiency in programming for data acquisition and analysis, explore various data sources and acquire a wide variety of data, and apply cleaning and transforming techniques to prepare data for analysis. Students will engage in data wrangling activities to ensure data quality and readiness for analysis. The includes comprehensive coverage of effective data visualization methods, and best practices and ethical considerations in data handling to ensure accurate and responsible data analysis.