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Everything You Need to Build Job-Ready Data & AI Skills
Build job-ready Data Science & AI skills through hands-on labs, real-life projects, and dedicated career support. You'll learn with industry professionals, complete practical coursework and a capstone project, graduate with industry certification, and receive Job Outcomes Program support to help refine your resume, strengthen your profile, and prepare for your next career opportunity.
Industry Credentials
Graduate with a UTS certificate of completion and CDSAIP™ industry certification from the Institute of Data.
Hands-on learning
Apply Python, SQL, machine learning, and AI through practical projects.
Real industry trainers
Learn from professionals who work with data and AI in the field.
Job-search support
Access 1:1 career coaching, interview prep, and support.
Job outcomes success within 180 days of completion*
Career support available for up to 12 months after course completion
Employers have hired our certified professionals
Industry Credentials
Graduate with a UTS certificate of completion and CDSAIP™ industry certification from the Institute of Data.
Hands-on learning
Apply Python, SQL, machine learning, and AI through practical projects.
Real industry trainers
Learn from professionals who work with data and AI in the field.
Job-search support
Access 1:1 career coaching, interview prep, and support.
*Read our full graduate outcomes report here
From your first line of Python to deploying generative AI in the cloud
Build the portfolio that gets you hired. You'll train machine learning models, work with LLMs, and deploy AI to production across three projects and a capstone.
Module 1:
Python, Math & Statistics
Start from the ground up: learn to code in Python and build the core maths and statistics every data scientist needs.
- Course Introduction and Overview
- Programming Fundamentals for Data Science
- Math & Statistics Fundamentals for Data Science
- Data Science Practice (ongoing)
Module 2:
Exploratory Data Analysis
Turn real, messy data into clear insights a business can act on, and learn the day-to-day practices of working data scientists.
- Data Cleaning and Quality Assessment
- Data Visualisation (Tableau)
- Statistical testing
- Succeeding as a Data Scientist in Industry
- Mini Project 1 – Data Science Practice
- Critical Thinking Training
Module 3:
Databases and APIs
Learn where real-world data lives and how to get it, using databases, SQL and APIs.
- Relational and Non-Relational Databases
- SQL
- Application Programming Interfaces (APIs)
- Data Science Practice (ongoing)
Module 4:
Machine Learning: Regression
Build your first predictive models: the techniques that forecast numbers like prices, demand and growth.
- Introduction to machine learning
- Feature modelling
- Evaluating Regression Models
- Overfitting and Regularisation
- Questioning Technique Training
Module 5:
Machine Learning: Classification
Train models to sort things into categories: the approach behind spam filters, fraud detection and risk scoring.
- Logistic Regression
- Evaluating Classification Models
- Support Vector Machines
- Bayesian Inference
- Data Science Practice (ongoing)
Module 6:
Machine Learning: Clustering & Patterns
Find hidden patterns and natural groupings in data that has no labels or right answers.
- K-means Clustering
- Principal Components Analysis
- Research and Documentation Training
- Mini Project 2 – Data Science Practice
Module 7:
Decision Trees & Ensembles
Combine many models into the powerful, high-accuracy systems used in industry today.
- Decision Trees
- Random Forests
- Bias and Variance
- Bagging
- Boosting
- Stacking
- Data Science Practice (ongoing)
Module 8:
NLP & Large Language Models
Work with human language and build the kind of technology behind tools like ChatGPT.
- Web Scraping
- Text Pre-processing
- Sentiment Analysis
- Large Language Models
- Presentation Skills Training
- Data Science Practice (ongoing)
Module 9:
AI & Deep Learning
Step into deep learning and the neural networks behind image recognition, voice assistants and modern AI.
- Introduction to Artificial Intelligence
- Reinforcement Learning
- Deep Feedforward Neural Networks
- Recurrent Neural Networks
- Convolutional Neural Networks
- Mini Project 3 – Data Science Practice
Module 10:
Generative AI & Deployment
Build generative AI applications and deploy machine learning models into real production environments.
- Generative AI Models
- Deployment of Machine Learning Models
- Cluster Computing
- Streaming Data
- Storytelling Training
- Capstone Project
Module 11:
Ongoing Content
Ongoing support that runs alongside the whole course, plus your capstone project. Extra topics are shaped by students and the lead trainer.
- Additional Topics: Determined by Students and Lead Trainer
- Job Outcomes Program
- Consultation and Presentation training
- Data Science Practice
- Capstone Project
Python Pre-work Included
30–40 hours of interactive Python prep sent immediately after enrolment — no prior coding experience needed.
Graduate Success Stories
Every graduate started where you are now: weighing up whether a career in data & AI was possible. These are the people who decided to find out, and what happened next.
Jack Sticklen
From zero IT experience to Deloitte data analyst
Jack had no IT background when he joined the UTS and Institute of Data program. Months later, he'd built the SQL, Python and machine learning skills that landed him a data analyst role at Deloitte.
"I could use my skills in a huge variety of industries and subject areas."
Chantanee Manonom
From 11 years in business consulting to data analyst
After more than a decade as a business consultant specialising in HRIS systems, Chantanee wanted to move into a field with stronger long-term prospects. The Institute of Data program gave her the technical foundation to make the switch.
"It was a career-changing course. Not just new skills, but a whole new mindset."
Supriya Maradana
From career break to data analyst at Infosys
After time away from the workforce to raise her family, Supriya wanted to return with future-proof skills. The part-time format let her study around motherhood, and she's now working as a Graduate Data Analyst at Infosys.
"I believe my decision to choose this industry is a great step in my career."
Simple, Clear Fees. Flexible Payment Options
Everything included — UTS certificate, industry certification, and career support
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Everything Included
- 400+ training and project hours
- Python pre-work modules (30–40 hrs)
- CDSAIP™ Industry Certification
- UTS Certificate of completion
- Job Outcomes Program (12m)
- 1:1 career coaching sessions
Employer-sponsored enrolment available.
Ask your employer to fund your study — we'll provide everything you need to make the business case. Speak to an advisor
Talk to a Career Advisor,
No Obligation
Prefer to speak with an advisor? Complete the form and we’ll call you back as soon as an advisor becomes available during business hours.
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Is Data Science & AI right for you? We'll be honest about whether your background is a good fit. -
Understand the real costs Get a clear picture of fees, payment plans, and ROI.
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Compare your options How does this stack up against a master's degree?
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Plan your career transition Discuss realistic timelines for changing roles after graduation.
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