IBF - Financial Data Mining and Modeling with R

Topic 1: Data Preprocessing

• Overview of Data Mining
• Data Pipeline
• Data Ingestion
• Data Quality
• Introducing R
• Data Processing

Topic 2: Data Analysis and Modelling

• Financial Analysis
• Statistical Summaries
• Data manipulation
• Descriptive statistics
• Variable relationships
• Cluster Analysis
• Anomaly Detection
• Forecasting

Topic 3: Business Case Studies

• Cluster Stock Investment
• Forecast Stock Time Series

Final Assessment

• MCQ
• Case Studies

Promotion Code

Promo or discount cannot be applied to IBF-STS courses

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

Softtware: Windows / Mac

Hardware: Laptop

Self-Sponsored Individuals

• Up to 70% subsidy is available for Singapore Citizens and Permanent Residents of Singapore, physically based in Singapore. GST funding support will no longer be applicable for all courses.

Company-Sponsored Individuals

• Up to 70% subsidy is available for Singapore Citizens and Permanent Residents of Singapore, physically based in Singapore. Please note:
• The company must be a Financial Institution regulated by MAS or a FinTech firm certified by Singapore FinTech Association (SFA)
• To register, please email your company name and your name to reachus@knowledgehut.com.sg.
• For more information on the IBF subsidies and eligibility, please visit:  https://www.ibf.org.sg/programmes/Pages/IBF-STS.aspx

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

• SSG 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.

• SME Business Owner
• Financial Analyst
• Business Development Manager
• Financial Consultant
• SME Accountant
• Finance Manager
• SME Credit Analyst
• Investment Banker focusing on SMEs
• Venture Capitalist
• SME Loan Officer
• Business Strategy Consultant
• Start-up Founder
• Economic Development Specialist
• Chief Financial Officer (CFO) for SMEs
• Financial Planner specializing in SMEs

Dr. Alvin Ang: Dr. Alvin Ang is a data science and AI specialist with a PhD in Operations Research from Nanyang Technological University and over 15 years of experience in teaching, research, and consulting. He has taught data science, statistics, R programming, machine learning, and financial analytics at institutions including SUSS, Curtin University, and SP Jain School of Global Management. As a dedicated trainer with IBM and Tertiary Infotech, he has delivered courses on R, Python, big data, and deep learning, equipping professionals with the skills to apply data-driven methods in real-world contexts.

Dr. Ang’s extensive professional certifications, including IBM credentials in R for Data Science, Data Visualization with R, and Deep Learning, reinforce his technical expertise. His teaching approach emphasizes practical application, ensuring learners master financial data mining, predictive modeling, and advanced R programming techniques. With a proven record of integrating theory with case-based learning, he empowers financial professionals to harness R for effective decision-making and strategic business insights.

Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is the Head of Data Science at Plano Pte. Ltd. and a seasoned trainer with extensive expertise in R programming, machine learning, and predictive modeling. He has developed advanced analytics solutions in R, Keras, H2O.ai, and RShiny, applying them to healthcare, finance, and customer analytics. As an adjunct lecturer at LSBF and associate trainer with Tertiary Courses, Dwight has delivered a wide range of R-focused courses, including R Data Mining, R Shiny App Development, Time Series Forecasting, and Deep Learning with R.

With an ACLP certification and strong applied experience in big data analytics using Spark, Impala, and AWS cloud platforms, Dwight bridges technical knowledge with practical industry applications. His training emphasizes hands-on learning, guiding participants through R-based data mining workflows, statistical modeling, and visualization techniques tailored to financial datasets. By combining advanced technical expertise with real-world use cases, Dwight equips learners with the skills to extract insights, build predictive models, and apply R effectively in financial services.

Dr. Alfred Ang: Dr. Alfred Ang is a distinguished technology and data science educator with over 20 years of experience in artificial intelligence, financial analytics, and digital transformation. As CTO and Chief Instructional Designer at Tertiary Infotech, he has spearheaded the development of over 500 accredited technology and analytics programs across domains such as AI, cloud computing, and machine learning. His expertise includes quantitative modeling, predictive analytics, and data-driven decision systems, with a focus on applying statistical programming in R and Python to real-world business and financial contexts.

In “Financial Data Mining and Modeling with R,” Dr. Ang equips learners with the analytical and programming skills to uncover insights from complex financial datasets. His training emphasizes statistical modeling, time series forecasting, and machine learning techniques tailored for financial applications such as risk analysis, portfolio optimization, and market trend prediction. Combining academic rigor with practical relevance, he guides participants in using R for end-to-end financial data workflows—transforming raw data into actionable intelligence that supports strategic financial decision-making.