Machine Learning (CS467)

COURSE DESCRIPTION

This is a comprehensive course on ‘Machine Learning‘ prepared for the Engineering students of KTU to introduce the prominent methods for machine learning, to study the basics of supervised and unsupervised learning, to study the basics of connectionist and other architectures. This course will also helps them to prepare for their university examination. The course content covers the essential  fundamentals as per the curriculum assigned by APJ Abdul Kalam Technological University (KTU). The student can attempt the optional assignment questions and MCQ test to strengthen their knowledge on the topic. The assessment algorithm of our LMS will help the students evaluate their performance till they get a certification of completion.

COURSE OUTCOME

• Differentiate various learning approaches, and to interpret the concepts of supervised learning.
• Compare the different dimensionality reduction techniques.
• Apply theoretical foundations of decision trees to identify best split and Bayesian classifier to label data points.
• Illustrate the working of classifier models like SVM, Neural Networks and identify classifier model for typical machine learning applications.
• Identify the state sequence and evaluate a sequence emission probability from a given HMM.
• Illustrate and apply clustering algorithms and identify its applicability in real life problems.

COURSE FEATURES

• Over 100+ lectures covering all the modules from the syllabus.
• Learn Machine Learning from a professional trainer from your own desk.
• Suitable for beginners to advance level users.
• Personalized training for easy understanding.
• Covers each and every aspects of the content.
• Clear all your doubts online.
• MCQ test for practice after each Module.
• Practice assignment questions after each session.
• Assessment algorithm for self-evaluation.
• Pass certification after completing the minimum-criteria with unlimited attempts at hand.

CERTIFICATION

Once you pass the course, you attain a certification of completion from Pace Lab. It will have a unique identifier and will be emblazoned by licensed institution logo. Authenticity of the certificate can be verified by scanning the QR code provided on the certificate.

(First few modules of this course are now available online. Other modules will be uploaded at the earliest, latest by March 2021)