IS 2320 Principles of Data Analysis 3.0 Credits
Applications of data science require an effective understanding of quantitative foundations, including linear algebra, calculus, probability, and statistical methods. This course will provide students with a gentle introduction to such foundations alongside essential computational techniques for exploring, summarizing and analyzing data. The course also discusses how to install and configure software necessary for a statistical programming environment, covers practical issues in statistical computing, and introduces computational applications for data analysis through a variety of analytic libraries.
Repeat Status: Not repeatable for credit
Prerequisites: MATH 1201 [Min Grade: D], MATH 1002 [Min Grade: D], MATH 2401 [Min Grade: D], MATH 2901 [Min Grade: D] (Can be taken Concurrently) or (IS 1310 [Min Grade: D] or BMES 1610 [Min Grade: D] or INFO 212 [Min Grade: D] or BMES 201 [Min Grade: D]) or MATH 121 [Min Grade: D] or MATH 102 [Min Grade: D]) or MATH 201 [Min Grade: D] or MATH 261 [Min Grade: D])