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AI for Life Science and Bioinformatics

Course Information

  • Sessions 4 days
  • Duration 32 hrs
  • Level Beginner
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Data and Statistical Analytics
TSC Code
HCE-DAT-4007-1.1

Funding Validity

Funding for this course is valid from 19 Oct 2024 to 18 Oct 2026. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

By end of the course, learners should be able to:

  • LO1: Recognize significant trends and aberrant results in bioinformatics data using statistical techniques.
  • LO2: Use statistical tests and data analytics tools to estimate uncertainties and determine data acceptability.
  • LO3: Review datasets to uncover trends or patterns and identify potential causes of unacceptable data.
  • LO4: Develop new methods for analyzing large, complex bioinformatics datasets using specialized modeling software.
  • LO5: Facilitate discussions on applying big data analytics to examine bioinformatics issues and derive insights.

Course Brochure

Download Course Brochure

Certification

  • Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - AI for Life Science and Bioinformatics

Course Code: TGS-2024049780
  • WSQ
  • SFC
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES

7 Review(s) | Add Your Review

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What's This Course About

This course equips participants with practical skills to apply artificial intelligence and computational methods to life science and bioinformatics data. Learners will explore how biological information can be collected, prepared, analysed, and interpreted to support research in genomics, transcriptomics, proteomics, drug discovery, and personalised healthcare.

Participants will learn the foundations of bioinformatics, including biological databases, sequence analysis, alignment, gene expression, genomic variation, and protein structure analysis. They will work with complex biological datasets to identify patterns, compare sequences, detect variants, and investigate relationships between genes, proteins, biological functions, and disease-related processes.

The course also introduces machine learning techniques for classifying biological data, predicting outcomes, detecting anomalies, clustering samples, and identifying important features. Learners will apply suitable evaluation methods to assess model performance and avoid issues such as overfitting, biased data, and incorrect biological interpretations.

Through hands-on activities, participants will use AI-assisted analytical workflows to explore datasets, visualise results, summarise scientific findings, and communicate evidence-based insights. Emphasis is placed on data quality, reproducibility, privacy, ethical use, model transparency, and the validation of AI-generated conclusions by qualified professionals.

By the end of the course, learners will be able to develop bioinformatics analysis workflows, apply AI techniques to life science data, evaluate analytical results, and present meaningful findings that support biological research and informed scientific decision-making.

WSQ Funding

Full Fee $2,000.00 Before GST
GST $180.00 9% of fee
Baseline Nett $1,180.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $780.00 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

View on SkillsFuture for Business

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used.

Direct Application on SkillsFuture Portal

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year.

Submit UTAP Claim

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

Check PSEA Eligibility

  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form, then submit the completed form to us:

PSEA Withdrawal FormSubmit PSEA Form

Course FeeBefore Funding

$2,000.00 (GST-exclusive)
$2,180.00 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

Topic 1: Bioinformatics Fundamentals and Biological Sequence Analysis

Topic 2: Protein Structure Analysis and Genomic Variant Detection

Topic 3: Transcriptomics, Genomics and Gene Expression Analysis

Topic 4: Machine Learning for Biological Pattern Discovery and Prediction

Topic 5: Bioinformatics Data Visualisation and Scientific Insight Communication

Assessment

  • Written Exam
  • Practical Exam

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 21-65 years old

Minimum Software/Hardware Requirement

Software: NIL

Hardware: Windows and Mac Laptops

SWDA (formerly SSG) Training Grant

SWDA TG is $15 per pax. Net fee after SWDA TG is $309.82. Absentee Payroll is not eligible.

Steps to Apply Skills Future Claim

  • The staff will send you an invoice with the fee breakdown.
  • Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
  • Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
  • Upload your invoice and click ‘Submit’

Get Additional Course Fee Support Up to $500 under UTAP

The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

Steps to Apply UTAP

  • Log in to your U Portal account to submit your UTAP application upon completion of the course.

Note

  • SWDA subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
  • All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
  • An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
  • UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
  • UTAP support amount will be paid to training provider first and claimed after end of class by learner.

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

Job Roles

Job Roles

  • Bioinformatics Analyst
  • Data Scientist (Bioinformatics)
  • Computational Biologist
  • Biostatistician
  • Genomics Data Scientist
  • Bioinformatics Research Scientist
  • Molecular Data Analyst
  • Proteomics Data Analyst
  • Genomic Data Analyst
  • Clinical Bioinformatics Specialist
  • Bioinformatics Software Developer
  • Machine Learning Engineer (Life Sciences)
  • Bioinformatics Consultant
  • Biotechnologist
  • Biomedical Data Scientist
  • AI Engineer (Life Sciences)
  • Big Data Analyst (Life Sciences)
  • Research Associate (Genomics)
  • Systems Biologist
  • Healthcare Data Scientist

Trainers

Trainers

Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.

Dr. Alfred Ang is a technology innovator, educator, and researcher with more than 25 years of experience in data analytics, computational systems, and applied engineering. He holds a PhD in Electrical Engineering from the National University of Singapore, an MEng from NTU, and an MBA from Universitas 21 Global. As Founder and Managing Director of Tertiary Infotech Pte. Ltd., Dr. Ang has led R&D initiatives and training programs in data science, AI, and bioinformatics applications, contributing to Singapore’s talent development in high-technology and research sectors. His academic and industry background uniquely positions him to bridge the gap between theoretical bioinformatics concepts and real-world implementation.
In this course, Dr. Ang provides learners with a deep understanding of AI-driven bioinformatics analysis. His sessions focus on data preprocessing, visualization, and predictive modeling for genomics and proteomics research. Learners gain a comprehensive view of how AI-assisted analytical workflows support precision medicine, biomarker discovery, and computational biology innovation. Through his structured and research-oriented instruction, participants build the capability to conduct reproducible and insightful biological data analysis using modern AI techniques.

Review

Customer Reviews (7)

Average Rating: 3.7/5 Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
N/A (Posted on 3/15/2026)
Average Rating: 4.3/5 Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
N/A (Posted on 3/15/2026)
Average Rating: 3.3/5 Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
N/A (Posted on 3/15/2026)
will recommend Review by Course Participant/Trainee
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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 2/2/2025)
will recommend Review by Course Participant/Trainee
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3. How do you find the training environment
. (Posted on 1/31/2025)

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