Data Science
and Machine Learning

Learning Outcome
Review programming languages to select the best option for data processing.

Topics:

• Comparative analysis of programming languages for financial data analysis
• Evaluation criteria for selecting optimal languages based on business requirements
• Characteristics and applications of different programming paradigms in finance
• Decision frameworks for language selection in financial data science projects

Learning Outcome
Assess business objectives to determine coding requirements.

Topics:

• Identifying business objectives and their impact on software solutions
• Evaluating business constraints and compliance requirements in coding decisions
• Mapping coding requirements to business needs through structured analysis
• Case studies on aligning software solutions with business goals

Learning Outcome
Develop functional code solutions that meets business requirements.

Topics:

• Requirement decomposition techniques for financial applications
• Translating financial processes and business logic into programmatic functions
• Ensuring business compliance and accuracy in coding financial solutions 

Learning Outcome
Utilise scripting and algorithmic techniques to develop efficient financial data solutions.

Topics:

• Selecting and applying algorithms for efficient financial data processing Developing automation scripts for repetitive financial data tasks
• Integrating scripting with structured coding solutions for scalable applications
• Optimizing data structures for performance and scalability
• Ensuring code efficiency and maintainability in data processing solutions

Learning Outcome
Use error handling techniques to resolve coding errors.

Topics:

• Systematic error identification and debugging methodologies
• Error handling patterns for financial applications 
• Analytical approaches to code review and optimization in financial models 

Learning Outcome
Apply structured testing methods to improve code performance and reliability.

Topics:

• Techniques for identifying performance bottlenecks in code execution
• Applying structured testing methods (unit testing, integration testing, performance testing)
• Refactoring techniques to enhance code efficiency 
• Optimizing algorithms and data structures for improved execution speed 
• Measuring and analyzing code performance using profiling

Learning Outcome
Develop coding frameworks to ensure consistency and maintainability.

Topics:

• Developing structured coding frameworks for better documentation practices
• Standardizing coding structures to improve maintainability and system integration
• Applying coding conventions to ensure consistency across documentation
• Versioning strategies for tracking code changes in integrated systems
• Aligning coding frameworks with API documentation and system workflows 

Learning Outcome
Prepare documentation for coding processes and system integration.

Topics:

• Best practices for documenting coding workflows and system architecture
• Maintaining clear and concise technical documentation for developers
• Documenting API specifications and software integration processes
• Writing structured reports for system updates and modifications
• Communicating technical documentation to non-technical stakeholders

Data Science is the field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines various disciplines like statistics, computer science, and domain expertise to analyze and interpret complex data, helping businesses and organizations make informed decisions, predict trends, and solve problems.

Data Science is essential because it enables organizations to harness the power of data to make informed decisions, optimize processes, and predict future trends. In today’s data-driven world, it helps businesses uncover hidden insights, drive innovation, and gain a competitive edge. Whether in finance, healthcare, or technology, data science plays a critical role in solving complex problems and shaping strategies.

This course has been accredited as a WSQ course and is eligible for funding under the SkillsFuture funding, subject to all eligibility criteria being met. Participants are advised to assess the suitability of the course and its relevance to his/her business activities or job roles. The SkillsFuture Funding provides 50% - 70% course fee subsidy support for direct training costs subject to all eligibility criteria being met.

Find out more on https://www.skillsfuture.gov.sg/funding-individuals

Yes. For self-sponsored Singaporeans aged 25 years old and above, you can use your SkillsFuture Credit to offset the remaining course fees after WSQ funding.

To check your SkillsFuture credit balance, please follow these steps:

1. Go to https://myskillsfuture.gov.sg
2. Click on ‘Submit SkillsFuture Credit Claims’
3. Login with your SingPass
4. Click on the arrow (>) at the top right hand corner. You will be able to see a drop-down list of your Available SkillsFuture Credits.

After you have registered for a course, an Aventis representative will reach out to guide you with the SkillsFuture Credits

Yes, all our courses are eligible for Union Training Assistance Programme (UTAP) Funding. NTUC Union members can use UTAP to offset 50% of unfunded course fees (capped at $500 per year).

This claim must be done after completion of the course. Please refer to the UTAP FAQ for more information.

Yes, both can be utilized concurrently. UTAP claims are processed after SkillsFuture Credits have been applied.

Illustrative Example:

• Total Course Fee: $1,000
• IBF Subsidy (70%): $700
• Remaining Fee: $300
• SkillsFuture Credit Applied: $200
• Out-of-Pocket Expense: $100
• UTAP Reimbursement (50% of $100): $50
• Final Cost After Reimbursements: $50

A laptop is required for this course. No special software or other hardware is required for this course participation.

Upon successful completion of this WSQ-accredited course, you'll receive a Data Science and Machine Learning certification to showcase your knowledge and expertise in this field.

Our programmes are highly respected by leading companies, who actively shape our curriculum and utilize our courses for employee training.