This course will equip you with the knowledge and skills on the use of algorithms and their application in different domains. Participants will discover how to visualize the results of data analysis and present the results in a way that tells a story and explains concepts using non-technical language. The course will be delivered using a variety of hands-on learning activities that provides participants with practice scenarios in data mining and machine learning.
Professionals working with data from various sectors in healthcare, finance, insurance and marketing, data science and data analytics professionals.
Upon successful completion of the course, students will be able to:
- Examine cases of descriptive and predictive problems.
- Apply clustering approaches such as K-means and hierarchical clustering.
- Investigate data classification using statistical methods such as logistic regression, naïve Bayes.
- Demonstrate machine learning with Support Vector Machines, decision trees and random forest.
- Explain the Deep Learning concept and methodologies and apply Neural Network methods to data sets.
- Describe model evaluation methods.
- Discover how to visualize the results of data analysis and present results in non-technical language.
- Program using advanced R language.
Admission to the program requires an Undergraduate degree or College Diploma plus the completion of a Basic Statistics course.
Applies Towards the Following Certificates
- Data Science Certificate : Required Courses