CZ4041: Machine Learning
Course Type: Certification | Study Mode: Part-Time
Keywords: Undergraduate | IT | Machine Learning
Course Detail
Introduction
The course is to introduce the principles of various fundamental machine learning techniques and their applications in data mining, computer vision and other fields. It covers areas ranging from unsupervised learning to supervised learning as well as the various applications of machine learning that may be encountered in industry.
Curriculum Overview
Successful completion of the course will enable students to:
a. Deeply understand the principles of the classical machine learning methods.
b. Apply the machine learning methods to solve classification, regression and clustering problems.
c. Understand challenges in machine learning.
d. Understand machine learning techniques for specific applications.
e. Use the available machine learning tools and packages.
Entry Requirements
Working professionals with prior knowledge of:
Pre-requisite: CZ1007 Data Structures, CZ1011 Engineering Mathematics I
- At least 21 years of age
- Have 2 years of full-time work experience, or have fully discharged full-time NS liability, or are currently employed on a full-time basis.
- Degree in Engineering/Science or
- Polytechnic Diploma with relevant working experience
Other Information
Funding
- SkillsFuture Series / SSG
- SkillsFuture Credit
- NTUC-UTAP
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