SITizens Learning Credits

Overview

Most AI Deep Learning and data science projects fail, despite promising test results and clear problem statements at the start. This is because many users may start off with unrealistic expectations due to an inadequate understanding of AI; what it can and cannot do, and IT managers may fail to understand the privacy, ethics, cyber security and governance issues related to this new disruptive science. Additionally, there may not be enough high-quality data available, and users do not understand the importance of garbage in, garbage out.

Therefore, the aim of this module is to provide a business deployment perspective of foundational Deep Learning AI capabilities, ranging from Natural Language Processing to Machine Vision; in a manner that requires little or no coding. Neural networks and how Deep Learning works, the data input requirements, project lifecycle and the development framework would be introduced. What problems that each specific AI algorithm can solve would be illustrated in an interactive workshop session and the enterprise benefits would be highlighted via case studies, e.g. enhanced productivity for corporate decision making, process automation or difficult unattended problem solving.

The focus is on rapid prototyping and to guide the users and the relevant project team members to validate project viability using the data and requirements that are available. Importantly, the student will gain the skills to highlight missing gaps, failure scenarios and to discuss AI compliance, privacy and cyber security requirements at the design phase, avoiding misunderstanding of the project’s complexity and hence be able to protect the project from failure.

Finally, modern challenges such as ensuring man-in-the-loop AI oversight, cyber security hardening against adversarial AI attacks and privacy obligations would be covered as new requirements for an upgraded corporate IT risk management framework that will be instrumental in protecting the company’s digitalisation efforts.

The future of AI continues to shine brightly, and we aim to highlight major high value factory automation future possibilities as AI and Big Data systems converge pervasively, and 5G and IoT AI at the edge become commodity. With these insights, the student will master key leadership skills to manage and plan AI projects successfully and hence, deliver strategic benefits to the corporation.

Teaching Team

What You’ll Learn

1. The architecture, applications and operations of popular AI Deep Learning systems and how they would benefit the digital entereprise via enhanced productivity in corporate decision making, process automation and problem-solving. Overview of software development using AI frameworks.
2. Overview of Natural Language Processing (NLP) AI systems and key applications.
3. Overview of AI vision processing systems for object recognition, segmentation, pose, biometrics, and action recognition.
4. Overview of AI Ethics, governance, AI cyber security vulnerabilities such as Adversarial Attacks, data security, privacy, and common implementation weaknesses. Understand privacy and cyber security best practices for AIOps and the need for ethics, transparency, and fairness for Trustworthy AI.
5. Overview of AI Project Management and leadership roles.
6. State-of-the-art in AI, future trends and developments; new pending problems that can be solved with better algorithms, and the cost reduction expected as the technology advances.
7. Analyse the feasibility of user requirements, data input requirements, AI project life cycle, and deployment suitability for Digitalisation and Enterprises.

Who Should Attend

  • Engineers, IT developers and Project Managers of enterprises.
  • Professionals with work exposure to manage automation projects or are managing enterprise innovation deployments, capabilities upgrading and associated risks.


SITizens Learning Credits (SLC) - Eligible Course

This course is SITizens Learning Credits (SLC) eligible. Please refer to the user guide how to register for courses utilising your SLC.

Find out more about SITizens Learning Credits (SLC).


Certificate and Assessment

A Certificate of Participation will be issued to participants who:
  • Attend 75% of the course
  • Undertake non-credit bearing assessment (during course)

A Certificate of Attainment for each module will be issued to participants who:

  • Attend at least 75% of each respective module; and
  • Participants who pass the Continuous Assessment

Schedule

Date Time Mode Topic
7 Feb 2023 9 am - 1 pm Physical class 1. Introduction to AI (Deep Learning) and Applications
8 Feb 2023 9 am - 1 pm Online Asynchronous e-learning + Lab1 2. Deep Learning Explained
9 Feb 2023 9 am - 1 pm Online Asynchronous e-learning + Lab2 3. Natural Language Processing (NLP) Use Cases
14 Feb 2023 9 am - 11 am
2 pm - 3 pm
Online (Zoom) Session 1
Xsite MCQ
Quiz 1: Open Book (30 Qns)
15 Feb 2023 9 am - 12 pm Online Asynchronous e-learning 4. AI Vision Applications
16 Feb 2023 9 am - 12 pm Online Asynchronous e-learning 5. IoT, Robots, and Drones
21 Feb 2023 9 am - 11 am Online (Zoom) Session 2
22 Feb 2023 9 am - 12 pm
2 pm - 5 pm
5 pm - 6 pm
Online Asynchronous e-learning + Lab3
Online Asynchronous e-learning
Xsite MCQ Respondus
6. AI Vision Embedded Systems
7. AI Project Management and Leadership
Quiz 2: Closed Book (30 Qns)
23 Feb 2023 9 am - 12 pm
1 pm - 5 pm
Online Asynchronous e-learning
Online Asynchronous e-learning + Lab4
8. AI Governance and Compliance 
9. AI and Cyber Security
24 Feb 2023 9 am - 12 pm
1 pm - 4 pm
4 pm - 6 pm
Online Asynchronous e-learning
Online Asynchronous e-learning
Xsite MCQ Respondus
10. AI Ethics, Economics, and Politics
11. The Future of AI
Exam/MCQ

Fees

Category Full Fee After SF Funding
Singapore Citizen (Below 40) $5,778.00 $1,733.40
Singapore Citizen (40 & above) $5,778.00 $653.40
Singapore PR/LTVP+ Holder $5,832.00 $1,749.60
Non-Singaporeans $5,832.00 Not Eligible

Note:
  • All figures include GST. GST applies to individuals and Singapore-registered companies.
  • You can opt for either SkillsFuture Funding or Mid-Career Enhanced Subsidy. Both cannot be combined.

» Learn more about funding types available

Terms & Conditions:

SkillsFuture Course Funding

To be eligible for the 70% training grant awarded, applicants (and/or their sponsoring organisations where applicable) must:

1.    Be a Singaporean Citizen or Singapore Permanent Resident or LTVP+ Holder
2.    Not receive any other funding from government sources in respect of the actual grant disbursed for the programme

SkillsFuture Mid-Career Enhanced Subsidy

To be eligible for the 90% enhanced subsidy awarded, applicants (and/or their sponsoring organisations where applicable) must:

1.    Be a Singaporean Citizen
2.    Be at least 40 years old
3.    Not receive any other funding from government sources in respect of the actual grant disbursed for the programme

SIT reserves the right to collect the balance of the course fees (i.e. the SSG course fee grant amount) directly from the trainees and/or their sponsoring organisations, where applicable, should the above requirements not be fulfilled by the trainee.

SIT reserves the right to make changes to published course information, including dates, times, venues, fees and instructors without prior notice.

Course Series

Postgraduate Certificate in Frontier Technologies in Infocomm Technology

Modules

  • FTI6001 Managing and Leading Enterprise Artificial Intelligence Projects
  • FTI6002 Internet of Things for a Connected World
  • FTI6003 5G for Digital Transformation
  • FTI6004 Cybersecurity in the New Economy

Each module carries 6 credits. Candidates who pass all 4 modules (totalling 24 credits) with a CGPA of 2.5 or more will be awarded the Postgraduate Certificate in Frontier Technologies by SIT. 

SITizens Learning Credits

Key Info

Venue SIT@NYP, 172A Ang Mo Kio Avenue 8, S567739
Time 09:00 AM to 06:00 PM
Date 07 Feb 2023 (Tue) to
24 Feb 2023 (Fri)
Registration is Closed.

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