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18–55 yearsPythonStatisticsSQLMachine learningDeep learningDocker

Data Science

Data scientists analyse large datasets, build models and use machine learning to make predictions and find patterns. This 9-month programme covers the full toolkit — and teaches the maths through Python, not dry theory.

From Python basics to deep learning with PyTorch and deploying models with Docker.

What you'll build

Exploratory data analyses

Clean, transform and visualise real datasets.

Machine learning models

Regression, decision trees, random forests, clustering.

A neural network project

Computer vision or NLP with PyTorch.

A deployed model

Packaged and served with Docker.

Curriculum

  1. 1Python for dataJupyter, data types, loops, functions, files, OOP, algorithms and unit tests — plus Git and GitHub.
  2. 2Maths with PythonLinear algebra with NumPy, data tables with Pandas, charts with Matplotlib, statistics, calculus and probability.
  3. 3SQLSyntax, table joins, window and ranking functions, and PostgreSQL.
  4. 4Machine learningEDA, feature scaling and encoding, linear and logistic regression, decision trees, random forests, k-NN, clustering and PCA.
  5. 5Data extractionWeb scraping with Scrapy, BeautifulSoup and Requests; CSV, Excel and PDF files; images with Pillow and OpenCV.
  6. 6Deep learning & deploymentNeural networks with PyTorch, computer vision and NLP examples, and deploying models with Docker.

NOVA certificate

Confirms completed training, practical tasks and project work — not just attendance.

Where it can lead

The course builds skills and a portfolio; it is not a job placement programme.

Typical monthly salary in Malaysia, from JobStreet Malaysia (October 2026).

Data Analyst

Python, SQL, Pandas

RM 3,500 – 5,000

per month

Data Scientist

ML, statistics, EDA

RM 6,800 – 7,800

per month

Data Engineer

SQL, pipelines, Docker

RM 5,750 – 8,250

per month

Questions about this course

Do I need strong maths?

The maths you need — linear algebra, statistics, calculus and probability — is taught inside the course using Python packages.

Who is it for?

Adults aged 18–55 who want to move into data roles, including career switchers.

What a lesson looks like

up to 12 students

per group — the teacher sees everyone

238 academic hours

total study hours

Computers provided

no laptop needed

Free replacement classes

if you miss a lesson

Free consultation

Book a free consultation

Tell us what you'd like to learn — we'll confirm a consultation time over WhatsApp.

Data Science

18–55 years · 9 months

Preferred time
WhatsApp