TGS code · TGS-2024042276
AI101TECHNICAL FOUNDATION
Data Analytics and AI with Python
Turn financial-services data into actionable insights with Python
Start with the data. Learn to prepare it, ask better questions of it and explain what you find with Python. Build the foundations before reaching for more complex tools.
- Audience
- Finance professionals
- Duration
- 15 hours
- Format
- 3 days · In person
- Level
- Beginner
- Coding
- Python, taught from the fundamentals
- Prerequisite
- Tertiary education; Python is taught from the fundamentals
- Fee after funding
- from S$25S$1,750 full fee
01What you’ll build
Python, taught from the fundamentals · 3 days · In person
What you’ll build: A Python capstone that collects, cleans, analyses and visualises a financial-services dataset.
A clean, analysis-ready dataset
Collect, assess, impute and organise financial-services data with Python.
A Python analysis notebook
Use NumPy and pandas to explore the data, calculate statistics and derive business insights.
A visual data story
Create charts with Matplotlib and Seaborn and explain what the patterns mean for the business.
02Curriculum
15 hours
Curriculum
Day 01
- Understand big data, its characteristics and economic value, and distinguish analytics from data science.
- Review common analytics use cases, tools and the reasons Python is widely used for data work.
- Navigate Jupyter Notebook, write a first program and work with Python data types and variables.
- Apply arithmetic, equality, comparison and logical operators in short code-along exercises.
- Retrieve, slice, concatenate and search strings and lists.
- Use for and while loops to repeat operations across collections.
- Combine sequence operations and iteration to transform small workplace datasets.
Day 02
- Write if, else-if, else and match/case branches for data-processing decisions.
- Combine nested conditions and iterations without losing track of program flow.
- Retrieve, update and search dictionary data.
- Define reusable functions and apply systematic debugging techniques.
- Create and manipulate NumPy arrays for numerical data.
- Use vectorisation and Boolean techniques instead of repetitive manual calculations.
- Calculate descriptive statistics and prepare NumPy results for exploration in pandas.
Day 03
- Create and configure pandas tables, then inspect and manipulate dataframe values.
- Run frequency analysis and apply string operations to clean categorical data.
- Handle null values, apply row-wise functions and merge multiple dataframes.
- Produce an analysis-ready dataset for the final visualisation workflow.
- Build bar charts, histograms, box plots and kernel-density plots with Matplotlib and Seaborn.
- Edit axes, labels, titles, colours, legends and styles so charts communicate clearly.
- Create multiple, conditional and overlaid plots to compare patterns in a dataset.
- Interpret the resulting visual evidence and explain its relevance to a financial-services question.
03Your instructor
Metacamp trainer
Your instructor: Vincent Leow
Tech Lead, Neutral Trade.
He has built production data pipelines and machine-learning systems and previously co-founded the Singapore Data Science Academy, where he served as lead instructor.
04Course fee and subsidies
AI101 · Full fee S$1,750
What you pay, and what funding covers.
Fee note
IBF-STS support is available to eligible Singapore Citizens or Permanent Residents who are physically based in Singapore and successfully complete the course, subject to prevailing eligibility, quantum and caps. Eligible Singapore Citizens may use up to S$500 from their Opening SkillsFuture Credit; SkillsFuture Mid-Career Credit cannot be used.
| Learner profile | Subsidies | Final course fee |
|---|---|---|
| Singaporeans aged 40 years and above | 70% IBF subsidy | S$525 |
| 70% IBF subsidy + up to S$500 Opening SkillsFuture Credit | from S$25 | |
| Singaporeans aged below 40 years | 50% IBF subsidy | S$875 |
| 50% IBF subsidy + up to S$500 Opening SkillsFuture Credit | from S$375 | |
| Permanent Residents (PRs) | 50% IBF subsidy | S$875 |
| Others (non-Singaporeans and non-PRs) | N/A | S$1,750 |
70% IBF subsidy + up to S$500 Opening SkillsFuture Credit → from S$25
05Course FAQ
A few things worth knowing before you choose.
Still unsure? Write to team@metacamp.sgIndicative after funding
from S$25S$1,750 full fee
Subject to eligibility · confirmed at enrolment
Start with GAI101 if you are new to applied generative AI. Choose GAI101F to build within a financial-services context, AI101 to analyse financial data with Python, or GAI201 after GAI101 or equivalent experience to orchestrate multi-agent systems.
GAI101 and GAI101F require no prior AI or coding experience. AI101 teaches Python from the fundamentals and requires tertiary education. GAI201 requires GAI101, GAI101F or equivalent working generative-AI fluency, but no coding experience.
Funding is course-specific. Eligible Singapore Citizens may use up to S$500 from their Opening SkillsFuture Credit toward the remaining fee. SkillsFuture Mid-Career Credit cannot be used. Available subsidies and final fees depend on the approved course run and your eligibility; confirm the prevailing amount before enrolment.
Something you built and know how to use. Depending on the course, this may be a custom assistant and automation, a financial-services AI workflow, a Python data-analysis capstone or a tested multi-agent system.
Yes. We offer private programmes for organisations and functional teams. Examples and exercises can be shaped around relevant roles, workflows and business goals.
AI will continue changing after your course. We teach principles and ways of thinking that remain useful as tools evolve. Graduates can also continue learning with the Metacamp community as new sessions and programmes are announced.