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4 programs, 9 subject areas, 5 career directions
Data Science
From first analyses to rigorous statistics, data engineering and the dashboards leaders act on.
Inside a clustering model
Structure, found in the data.
K-means puts every point with its nearest centre, then moves each centre to the middle of its points, and repeats until nothing changes. Click to generate new data.
An illustration for learning, not a live model.
What this domain covers
Every subject area below is taught inside a full program, not as a thin standalone course. Each area links to the programs that teach it in depth.
Data science foundations
The programming and statistics underneath every analysis.
Introduction to data science, Python for data science, R programming, Mathematics for data science, Probability and statistics, Data literacy, Data analysis fundamentals
Taught in Applied Data Science
Data analytics
Answering business questions with data.
Professional data analytics, Exploratory data analysis, Data cleaning and preparation, Statistical analysis, Business analytics, Product analytics, Marketing analytics, Financial data analytics, Customer analytics
Taught in Applied Data Science and Business Intelligence & Analytics
SQL and databases
Querying and modelling the data everything else depends on.
SQL fundamentals, Advanced SQL, Relational database design, NoSQL fundamentals, Analytical databases, Data modelling, Query optimisation
Taught in Data Engineering and Business Intelligence & Analytics
Business intelligence
Dashboards and metrics that guide decisions.
BI foundations, Power BI, Tableau, Data visualisation, Dashboard engineering, KPI design, Executive analytics, Data storytelling
Taught in Business Intelligence & Analytics
Advanced data science
Rigorous methods for high-stakes questions.
Applied statistical modelling, Predictive analytics, Time series forecasting, Experimental design, A/B testing, Causal inference, Bayesian data analysis, Optimisation, Recommendation systems
Taught in Data Science & Analytics
Data engineering
Pipelines and platforms that move and shape data.
Data engineering foundations, ETL and ELT pipelines, Apache Spark, Data warehousing, Lakes and lakehouses, Pipeline orchestration, Streaming data, Cloud data engineering, Data quality engineering, DataOps
Taught in Data Engineering
Big data and cloud
Processing at scale on modern cloud platforms.
Big data analytics, Distributed processing, AWS data engineering, Azure data engineering, Google Cloud data engineering, Cloud analytics architecture, Scalable data systems
Taught in Data Engineering and Data Science & Analytics
Data governance
Quality, privacy and responsible data practice.
Data governance fundamentals, Data privacy, Data security, Data quality management, Catalogs and metadata, Data compliance, Responsible data practices
Taught in Data Science & Analytics and Data Engineering
Specialised data science
Industry applications, taught as electives.
Finance, Healthcare, Retail, Sports analytics, Supply chain, Geospatial analytics, Customer intelligence, Risk analytics, Operations research, Applied research methods
Taught in Data Science & Analytics and Applied Data Science
Pathways that cross domains
Programs are designed to stack. These sequences are common routes; PathFinder will suggest one for your situation.
Data to AI engineering
All data science programs
4 programs
Professional Certificate, Data science
Applied Data ScienceTurn raw data into decisions people act on.
- Length
- 6 or 12 months
- Level
- Foundational
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort, Hybrid, Self-paced
Professional Certificate, Data science
Data EngineeringBuild the pipelines every data and AI team depends on.
- Length
- 6 or 12 months
- Level
- Intermediate
- Weekly time
- 8 to 12 h/week
- Formats
- Live cohort, Hybrid, Self-paced
Advanced Program, Data science
Business Intelligence & AnalyticsDashboards and analysis that leaders actually use.
- Length
- 3 or 6 months
- Level
- Foundational
- Weekly time
- 6 to 10 h/week
- Formats
- Live cohort, Self-paced
Advanced Program, Data science
Data Science & AnalyticsStatistical depth for decisions with real stakes.
- Length
- 12 or 18 months
- Level
- Advanced
- Weekly time
- 10 to 14 h/week
- Formats
- Live cohort, Hybrid
Where this leads
Roles these programs prepare you to work toward. We describe the work; we don't promise jobs or salaries.
Data Scientist
Answers questions and informs decisions with statistics and models.
Explore this roleData Analyst
Turns business data into reports, dashboards and recommendations.
Explore this roleData Engineer
Builds the pipelines and platforms data teams rely on.
Explore this roleAI Solutions Architect
Designs how AI capabilities fit into an organisation's systems.
Explore this roleAI Product or Engineering Leader
Sets direction for AI products, platforms and teams.
Explore this role