Modular Certificate in AI Algorithms & Deep Learning

Training Provider: SINGAPORE POLYTECHNIC
Course Reference: TGS-2026063523
S$5,598

About This Course

This is a certificate under the Diploma in Infocomm & Digital Media (Applied Artificial Intelligence & Analytics).

What You'll Learn

The Modular Certificate in AI Algorithms & Deep Learning provides participants with knowledge and skills in data structures, algorithms, and deep learning. It covers advanced object-oriented concepts and the implementation of data structures such as stacks, queues, linked lists, and dictionaries, as well as algorithms for problem solving, code efficiency, and searching using Python. Participants will also learn deep neural network architectures and their applications, including preparing datasets and training models using frameworks such as TensorFlow, Keras, and PyTorch, with applications in image recognition, natural language processing, generative AI, and reinforcement learning.

Entry Requirements

GCE ‘O’ Levels
3 relevant passes & 1 year relevant working experience:
Subjects/Min. Grade:
1. English: 7
2. Mathematics (E-Maths or A-Maths): 6
3. Any one other subject (excluding CCA): 6

FT Nitec
GPA > 3.5 OR
GPA > 3.0 and 1 year of relevant working experience

PT Nitec in Technology/Services
GPA > 3.5 and 1 year of relevant working experience

FT Higher Nitec
GPA > 2.0 OR
GPA > 1.5 and 1 year of relevant working experience

PT Higher Nitec in Technology/Services
GPA > 2.0 and 1 year of relevant working experience

WSQ Diploma
Relevant WSQ Advanced Cert (or higher) with 1 year of relevant working experience and Level 6 for both WSQ Workplace Literacy SOA & Workplace Numeracy SOA.

Without any of the relevant academic qualifications
At least 2 years of relevant working experience.

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

Course Details

Duration 180 hours
Language English
Training Commitment Part Time
Total Enrolled New course
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