This course is centered on using Python for data science, providing a foundational understanding of machine learning (ML) models and concepts in ML and Artificial Intelligence (AI). By the end of the course, students will have learned to work with regression models and classification models using popular libraries like sklearn, Pandas, matplotlib, and numPy.
Key topics include selecting model complexity, preventing overfitting, regularization, assessing uncertainty, weighing trade-offs, and evaluating models. This course will increase your confidence in using Python and prepare you for more advanced studies in ML and AI and career advancement in the field.
🆓 Free to Audit
🕒 Approx. 8 weeks
📈 Intermediate Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by Harvard University via Edx
