Course Overview
Domain
Infocomm Technology
Business, Communication and Design
Format
SkillsFuture Career Transition Programme (SCTP)
Duration
4+ months
Fee Subsidy
Up to 95% SF Funding
As organisations increasingly rely on data-driven insights to enhance decision-making and gain a competitive edge, the demand for skilled analysts to interpret and apply these insights remains high.
Despite the growing need for data expertise, there is a skills gap to find qualified data professionals such as data analysts and Business Intelligence (BI) specialists. As a result, there is a focus on equipping employees with data analytics skills for both career growth and organisational success.
This programme provides learners with key skills to extract actionable insights from large datasets, covering statistical analysis, data mining, and database management. It includes training in data visualisation techniques and emphasises critical thinking and problem-solving to identify patterns and trends.
Learners will gain hands-on experience with industry-standard tools like SQL, Python, Tableau, and Power BI for data cleaning, transformation, and analysis. Real-world case studies and projects will allow them to apply their knowledge to business challenges. It will also cover business intelligence concepts, showing how data-driven insights can enhance strategic decision-making and organisational performance.
Learners will put their skills into practice with a Capstone Project, which aims to cultivate data-literate professionals adept at driving business growth and innovation. The programme prepares them to tackle business problems, develop data-driven solutions, and effectively communicate their findings. This comprehensive training equips them for successful careers across industries such as finance, marketing, healthcare, and e-commerce.
Who Should Attend
- Market research professionals
- Technical professionals
- Engineers
- Individuals with STEM-related work experience looking to pivot into a career in data analytics for roles such as:
- Data analyst
- Market data researcher/analyst
- Data specialist/engineer
Prerequisites
Individuals should possess a relevant background, which may include:
- A minimum of a STEM-related diploma; or
- Completion of a STEM-related BootCamp programme within the past three years; or
- Relevant work experience in the Infocomm sector or related job roles; or
- Prior or current work experience in a STEM-related field.
What You Will Learn
Module 1: Data Fundamentals, Database Management (SQL), Data Wrangling and Cleaning (OpenRefine, Trifacta Wrangler)
- Differentiate important data concepts including between data, information, and knowledge, and identify the various types of data and data quality issues
- Explain the fundamentals of relational databases and the importance of database normalisation
- Use SQL syntax query to manipulate and manage data within databases effectively
- Utilise tools such as OpenRefine and Trifacta Wrangler for cleaning, transforming, and enriching data
Module 2: Python for Data Analysis
- Develop a comprehensive understanding of Python syntax including data types, control flow, and functions
- Produce well-structured, maintainable Python code
- Master numerical computations and array operations using the NumPy library
Module 3: Statistics and Data Visualisation with libraries like Matplotlib and Seaborn
- Grasp fundamental statistical concepts such as descriptive statistics, probability distributions, hypothesis testing, and regression analysis
- Apply appropriate statistical techniques to data analysis
- Create effective visualisations, tailored to specific audiences using Matplotlib and Seaborn
- Communicate data insights through effective storytelling
Module 4: Machine Learning
- Define machine learning and its various applications, including supervised, unsupervised, and reinforcement learning
- Build and evaluate predictive models using algorithms such as linear regression, decision trees, and neural networks, addressing business problems like customer churn and fraud detection
- Implement data preprocessing, feature engineering, and hyperparameter tuning to optimise model performance
- Leverage machine learning within data analytics and business intelligence workflows, while considering ethical implications and decision-making processes
Module 5: Business Intelligence Concepts and Tools
- Explain the fundamental components of Business Intelligence (BI) and define its role in organisations
- Apply popular BI tools, such as Power BI and Qlik, to extract, transform, and load (ETL) data, solving real-world business challenges
- Evaluate how BI techniques support data-driven decision-making and enhance organisational performance
- Assess the effectiveness of BI implementations and their contribution to overall business performance
Module 6: Capstone Project on Data Analytics and Business Intelligence Programme
- Synthesise and apply data mining, statistical analysis, machine learning, and data visualisation methods to solve complex business problems encountered in the Capstone Project
- Perform the entire data analysis process, including data acquisition, cleaning, exploration, modelling, visualisation, and utilising skills acquired in the previous five modules
- Develop interactive dashboards and reports using business intelligence tools, effectively communicating insights to stakeholders
- Identify and address data-related challenges, and present findings to varied audiences, including business executives, technical teams, and potential employers
Teaching Team
Vinol Joy D’Souza
Head of Data, Aspire
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Ilia Tivin
Managing Director, Locked Jar
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Schedule
| Course Run | Dates | Topics and Delivery |
|---|---|---|
| TBA | TBA | Facilitated classroom training Classes are held once a week from 9:00 am – 1:00 pm over four+ months |
| In-person assessment (MCQ test) Five tests over four+ months |
||
| Synchronous e-Learning Classes are held online once a week from 6:00 pm – 9:00 pm over four+ months |
||
| Assignments and project works, self-learning | ||
| Asynchronous e-Learning with research and reading materials | ||
| Capstone project, self-learning with project consultation and final project presentation |
Certificate and Assessment
A Certificate of Participation will be issued to participants who:
- Attend at least 75% of the course
- Undertake and pass non-credit bearing assessment during the course
Fee Structure
The full fee for this course is S$16,350.00.
| Category | After SF Funding |
|---|---|
| Singapore Citizen (Below 40) | S$4,905.00 |
| Singapore Citizen (40 & Above) | S$1,905.00 |
| Singapore Citizen who meets the additional course fee funding support criteria | S$1,155.00 |
| Singapore PR / LTVP+ Holder | S$4,905.00 |
| Non-Singapore Citizen | Not Eligible |
Note:
- All fees above include GST. GST applies to individuals and Singapore-registered companies.
Additional Course Fee Funding Support Criteria
To be eligible for 95% additional course fee funding support, applicants must be a Singapore Citizen and meet one of the following criteria:
- Long-term unemployed individual (unemployed for six months or more); or
- Person with disabilities; or
- Individual in need of financial assistance – ComCare Short-to-Medium Term Assistance (SMTA) recipient or Workfare Income Supplement (WIS) recipient. Additionally, they should not have received any other funding from government sources in respect of the actual grant disbursed for the programme.
Speak to Our Career Coach
If you have further questions regarding the SkillsFuture Career Transition Programme, do get in touch with our career coach Joe Leong via email, or make an appointment today.
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