OBJECTIVE
The program provides students with a broad knowledge in two main areas of Machine Learning: supervised and unsupervised. The program introduces to systems that learn from experience and outline the problems based on classification, clustering, and regression.
LERANING OBJECTIVES
Machine Learning students will understand the foundations of Linear Regression, Linear and Logistic regression, Support Vector Machines, and other models in machine learning. The course will expose to the fundamental’s concepts of regression and classification with practical implementation with different Python packages like Numpy, Scipy and Scikit-Learn.
Student will be able to build models for prediction using machine learning concepts, use classification methods for building prediction models, apply learning algorithms to improve predictive performance, outline the required instances using representation learning, build an anomaly detection system by separating outliers, apply clustering algorithms for observations based on similarity and construct predictor’s models using machine learning techniques.
The project work will build your technical skills by providing a methodological approach towards problem-solving using models in Machine Learning.
COURSE DURATION: 20 Weeks
COURSE FEE: CAD $ 2500