Modular Certificate in Data & AI Applications (part of Diploma in Engineering (Electronic & Digital Engineering))

Training Provider: Nanyang Polytechnic
Course Reference: TGS-2022015029
S$5,094

About This Course

Modular Certificate in Data & AI Applications (MC4 of Diploma in Engineering (Electronic & Digital Engineering)) will prepare the learners to:

1. learn to perform basic analysis on data collected to solve engineering related problems.
2. apply data analytics to gain insights from data and pre-process data for machine learning applications.
3. apply machine learning algorithms, including both supervised and unsupervised learning for AI modelling, using industry standard libraries/framework.
4. apply algorithms to conduct hyperparameters tuning to solve engineering problems.
5. acquire knowledge and skills in domain-specific applications and latest emerging technologies for solving real-world problems.

What You'll Learn

Modular Certificate in Data & AI Applications (part of Diploma in Engineering (Electronic & Digital Engineering)) covers 6 modules (as listed below).  Each module has 30 hours of training.

• Data Acquisition
• Data Management
• Data Analytics
• Machine Learning
• Deep Learning Networks
• AI Applications

Entry Requirements

The admission requirements are:

• GCE 'O' level with minimum of 3 relevant passes and at least 1 year of relevant working experience; or
• Nitec with GPA ≥ 3.5; or
• Nitec GPA ≥ 3.0 and at least 1 year of relevant working experience; or
• Higher Nitec with GPA ≥ 2.0, or
• Higher Nitec GPA ≥ 1.5 and at least with 1 year of relevant work experience; or
• Nitec in Technology with GPA ≥ 3.5 and at least 1 year of relevant working experience; or
• Higher Nitec in Technology with GPA ≥ 2.0 and at least 1 year of relevant working experience; or
• Relevant WSQ Advanced Certificate (or higher), and at least 1 year of relevant working experience and Workplace Literary & Numeracy (WPLN) at Level ≥ 6; or
• At least 2 years relevant working experience (subject to interview/assessment).

Recognition of Prior Learning (RPL):
Applicants who do not meet the entry requirements may be considered for admission to the course based on supporting evidence of competency readiness. Suitable ap

Course Details

Duration 180 hours
Language English
Training Commitment Part Time
Total Enrolled 15 students
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Note: To apply for this course, visit the SkillsFuture website or contact the training provider directly.

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