This course offers an in-depth introduction to least squares regression, approached from a linear algebraic and mathematical perspective. It is designed for students with a foundational knowledge of linear algebra, multivariate calculus, statistics, regression models, and basic proof-based mathematics, along with some familiarity with the R programming language.
By the end of the course, students will gain a solid understanding of the linear algebra concepts underlying regression modeling, enhancing their overall comprehension of applied data science and regression analysis.
🆓 Free to Audit
🕒 Approx. 8 Hours
✏️ Advanced Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by Johns Hopkins University via Coursera
