This is the micro degree program of the course series "Introduction to Machine Learning", comprising three courses that cover different supervised machine learning topics. Starting from basic machine learning concepts learners will get to know the full cycle of developing machine learning models. Micro degree certificate is issued after concluding all three courses. After clicking on the "Enrol/to course" button, the certificate can be found in the course section "Micro Degree Certificate." 

The three online courses from this micro degree program will cover:

• Basic supervised matching learning concepts include regression, classification and loss functions.
• Classification and regression algorithms for building machine learning models such as k-nearest neighbours, decision trees and random forests.
• Evaluation and improvement aspects in machine learning, focusing on AUC-ROC metrics and hyperparameter tuning.

Upon conclusion of this micro degree program, you will

• understand regression and classification tasks in machine learning.
• explain the ideas behind those machine learning algorithms.
• evaluate regression and classification machine learning models and fine-tune model hyperparameters.
• build Python or R machine learning models and apply different evaluation and fine-tuning methods. 

To receive the micro degree, learners must have completed the three online courses of "Introduction to Machine Learning", i.e., Foundation, Algorithms, Evaluation and Tuning. The Transcript of Records is available to those who have achieved at least 60% of the total grade in all courses by completing the graded activities.