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Course Overview

Artificial Intelligence is one of the fastest growing areas in industry. Businesses are rushing to leverage AI to do things differently, faster, and more efficiently. We are seeing a rise in the use of autonomous vehicles. We are able to build houses in a week instead of a year. If you are an ITE graduate who is seeking to upgrade and upskill, this AI course is for you. You will learn to develop chatbots, leverage on natural language processing technologies, undertake object recognition and  use machine learning and deep learning algorithms to create solutions.

Application/Entry Requirement

 

‘O’ Levels

At least 3 ‘O’ Level passes in the following subjects: 

English Language (EL1 or EL2) Grade 1 – 7

Any mathematics subject Grade 1 – 6

Any science subject Grade 1 – 6

and 3 years of relevant working experience OR

Higher Nitec

GPA ≥ 2.0 OR

GPA ≥ 1.5 and 1 year of relevant working experience OR

Nitec

GPA ≥ 3.5 OR

GPA ≥ 3.0 and 1 year of relevant working experience OR

Higher Nitec in Technology/Services GPA ≥ 2.0 and 1 year of relevant working experience OR
Nitec in Technology/Services GPA ≥ 3.5 and 1 year of relevant working experience OR
WSQ Qualification Relevant WSQ Qualification with 3 years of relevant working experience and WSQ Workplace Literacy Statement of Attainment (SOA)(Level 6) AND Workplace Numeracy Statement of Attainment (SOA)(Level 6)

Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 5 years of relevant working experience or supporting evidence of competency readiness. Suitable applicants who are shortlisted may have to go through an interview and/or entrance test. The Polytechnic reserves the right to shortlist and admit applicants.

Who Should Attend

Individuals who want to upgrade their skills in the areas of applied artificial intelligence. It is suitable for ITE upgraders who have a technical certificate and wish to learn how to apply artificial intelligence across various areas.

What You'll Learn

To be awarded the Diploma in Infocomm and Digital Media (Applied Artificial Intelligence), participants are required to complete a total of 5 modular certificates (MCs). A certificate will be issued upon successful completion of each MC.

Subject Code Subject
CAA1C01 Computational Thinking

This subject introduces students to the fundamentals of computational thinking and their application in developing programming solutions to problems. Topics covered include programming concepts, simple data structures and programming techniques.

CAA1C02 Coding & Development Project

This subject introduces students to coding principles and practices using an object-oriented approach. The subject also introduces the development of an IT application using the latest technologies. Topics covered include object and classes, composition, simple data structures, application architecture, design and development.

CAA1C03 Database Application Development

This subject will introduce the fundamental concepts of relational database systems, the design methods specific to relational database, database manipulation using a database query language, and the techniques of implementing relational databases. It will also cover implementation of simple application to access relational database.

Subject Code Subject
CAA1C04 Data Visualisation & Analytics

This subject covers the data analytics lifecycle, including gathering, cleaning, processing and visualizing of data. Exploratory data analysis methods, descriptive and predictive analytics and the presentation of insights will also be covered.

CAA1C05 Data Science Essentials

This subject equips with knowledge and skills in the emerging field of data science. It covers the data science life-cycle, history and context, as well as its landscape.  Topics covered include data exploration and analysis techniques to discover new knowledge from data to aid data-driven decisions in an intelligent and informed way.

CAA1C06 Data Storytelling

The subject covers graphing fundamentals, graphing properties and building dashboard for storytelling and reporting purposes using relevant statistical modelling and analysis techniques. Topics covered include the preparation of reports on data analysis to support managerial decision-making and applying the data storytelling framework and principles of data visualisation to enable business users to effectively communicate and narrate findings and insights relevant to business contexts.

Subject Code Subject
CAA1C07 Machine Learning for Developers

This subject introduces the fundamentals of machine learning principles and practices. It covers the concepts of supervised and unsupervised learning, and how the trained model can be deployed in an application.

CAA1C08 Deep Learning & Object Recognition

This subject introduces students to the fundamental principles of deep learning and how it is applied to a collection of computer vision tasks to implement object recognition. It covers the concepts and architecture of convolutional neural networks such as the various layers within, and the hyperparameters involved, using available tools and libraries.

CAA1C09 AI & Ethics

This subject provides students with insights on the usage and implications of AI in daily life. It touches on the risks of applying AI without a certain set of moral and ethical principles, and discusses issues brought about by machine learning, such as the four types of bias: sample bias, prejudice bias, measurement bias, and algorithm bias.

Subject Code Subject
CAA1C10 IoT Application Development

This subject covers the concepts of Distributed System Architecture like Service-Oriented Architecture, Representational State Transfer (REST) and Web Services, identification of technology and design principles for connected devices as well as prototyping techniques for developing web services.

CAA1C11 Cloud Technologies

This subject equips students with the skillsets for developing and deploying machine learning applications to a cloud platform maintained by cloud computing providers such as Amazon, Google, etc. It covers the storage of data and the use of application programme interfaces (APIs) and tools provided by the cloud platform.

CAA1C12 Robotic Process Automation

This subject introduces students to the techniques of using an automation tool to automate tasks within a business process. It touches on the various use cases of robotic process automation (RPA) and provides a platform for students to creatively apply the concepts to different scenarios. It also discusses the challenges and limitations of RPA such as integration with unsupported third-party tools, security and governance, etc.

Subject Code Subject
CAA1C13 Virtual Assistant Development

This subject equips students with the knowledge and skills to apply the concepts of natural language processing to chatbot development using available tools and libraries.

CAA1C14 Text Classification

This subject equips students with the knowledge and skills to apply the concepts of natural language processing to text classification using available tools and libraries. It also explores the use of text classification in applications such as sentiment analysis and spam detection.

CAA1C15 Speech Recognition

This subject equips students with the knowledge and skills to apply the concepts of natural language processing to speech recognition using available tools and libraries.

Modes of Assessment

 

You will be assessed by coursework. There is no examination for this course.

Career Opportunities

At the entry level, the job positions are AI/Machine Learning Engineers and Software Engineer. Upon completing the course, graduates can look forward to role expansion in their work scope. They can also look forward to upgrading their knowledge and skills through further CET and executive programmes offered by local Institutes of Higher Learning.

Course Schedule

Intake Info Application Period Course Duration

19 April 2021

02 November 2020 - 11 January 2021

2.5 Years

APPLY

Course Fees

Course Fees per Modular Certificate

Fee Type Course Fees
(w GST) 
SME-sponsored Singapore Citizens & Permanent Residents S$337.50
Singapore Citizens aged 40 & above S$327.42
Singapore Citizens aged below 40 S$481.50
Singapore Permanent Residents S$1,290.42
Others & Repeat Students S$3,235.68

SkillsFuture Credit Approved. For more details, please click here

Course fees payable is based on per MC.

Course fees will be reviewed by MOE on an annual basis and adjusted accordingly.

MOE subsidy will not be applicable for students who repeat a module or semester.

With effect from 1 Jul 2020, the Workforce Training Scheme (WTS) will be replaced by Work Support Scheme (WSS), for more information, please visit:

https://www.wsg.gov.sg/programmes-and-initiatives/workfare-skills-support-scheme-individuals.html

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Course Contact

  • 67881212
  • 8.30 am to 6.00 pm (Mon to Thu)

    8.30 am to 5.30 pm (Fri)

    Closed on Sat, Sun & Public Holidays

  • Website: https://www.tp.edu.sg/tsa
  • Temasek SkillsFuture Academy
    Temasek Polytechnic
    East Wing Block 1A, 
    Level 3, Unit 81
    21 Tampines Ave 1
    Singapore 529757

  • Temasek Polytechnic reserves the right to alter the course, modify the scale of fee, amend any other information or cancel course with low enrolment.

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