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Diploma · 800 h · 8 modules
Diploma in Data Science for Ports and Shipping
The Diploma in Data Science for Ports and Shipping Prepares you to apply data science to the challenges of shipping and port operations. You will work with AIS data, port call records, fuel consumption reports, met-ocean data and
Duration800 h
FormatOnline
Starts14 December
Places20 / 20
Prior knowledge
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Programme overview
What is the Diploma in Data Science for Ports and Shipping?
The Diploma in Data Science for Ports and Shipping
Prepares you to apply data science to the challenges of shipping and port operations. You will work with AIS data, port call records, fuel consumption reports, met-ocean data and terminal data, and learn to clean, analyse and model them to optimise routes and berthing, predict arrival times, monitor fuel use and emissions, and build dashboards that improve decision-making in ports, terminals and shipping companies of every size.
Key advantages
- Sector data: Case studies using AIS, port calls, fuel consumption and terminal operations.
- Applied focus: Real problems faced by ports, terminals and shipping lines.
- Professional tools: Python, SQL and visualisation tools.
- Decarbonisation: Analysing fuel use and emissions with recognised indicators.
- Your own case study: An analytics project for a port or a fleet.
Programme type
Diploma
Study mode
Online
Duration
800 hours
Modules
8
Programme highlights
- Master maritime data: Work with AIS and operational data from ships and ports.
- Optimise operations: Improve berthing, port calls and routes with data.
- Forecast: Apply predictive models for arrivals and demand.
- Measure emissions: Analyse fleet fuel use and energy efficiency.
- Boost your career: Open doors to port authorities, terminals and shipping companies.
- Train to make data the driver of more efficient, sustainable ports and fleets.
Curriculum
Programme Structure
The programme is structured in 8 modules, listed below in order of study.
01
Data in the Maritime and Port Sector
- Digitalisation of shipping
- Players in the port ecosystem
- Port community systems
- The maritime single window
- Vessel and port call data
- Terminal data
- Met-ocean data
- Data governance and sharing
02
Data Science Tools
- Python for analysis
- Pandas and tabular data
- SQL and databases
- Geospatial analysis
- Data visualisation
- Reproducible notebooks
- Business intelligence tools
- Good project practice
03
AIS Data and Traffic Analysis
- How AIS works
- AIS messages and fields
- Cleaning vessel tracks
- Detecting port calls and anchorages
- Traffic density
- Route analysis
- AIS limitations and data quality
- Enrichment with ship registers
04
Port Operations Analytics
- Port productivity indicators
- Waiting and port call times
- Berth planning
- Congestion and queues
- Container terminal productivity
- Bulk operations
- Hinterland transport and connections
- Benchmarking between ports
05
Predictive Models for Ports and Fleets
- Forecasting estimated time of arrival
- Forecasting traffic demand
- Terminal operating times
- Predictive maintenance
- Time series models
- Machine learning models
- Model evaluation
- Putting models into production
06
Energy Efficiency and Emissions
- Fuel consumption and performance
- Effects of weather and load
- Speed optimisation
- IMO carbon intensity indicators
- Monitoring emissions in port
- Shore power
- Port emissions inventories
- Sustainability reporting
07
Dashboards and Decision-Making
- Designing key indicators
- Operational dashboards
- Strategic dashboards
- Geospatial visualisation
- Alerts and monitoring
- Storytelling with data
- User adoption
- Data ethics and privacy
08
Case Study: An Analytics Project for a Port or Fleet
- Defining the problem
- Identifying data sources
- Data preparation
- Exploratory analysis
- Model development
- Evaluating results
- Dashboard
- Presentation to management
Workload
Study Time and Workload
800 hours of study, online and at your own pace. Move the slider to the hours a week you can really put in.
Hours a week8
Weeks to finish—
You finish around—
Who it is for
Port, terminal and shipping professionals: who want to make the most of their data Graduates in nautical studies, engineering, economics or logistics: looking for an analytical profile Data analysts: who want to specialise in the maritime sector Sustainability officers: who manage fleet fuel use and emissions Logistics consultants: working with maritime supply chains
Faculty
Academic direction and faculty
The teaching team at Navalis: working professionals who deliver and oversee the institute's programmes.
Eng. Diego Cifuentes
Cap. Javier Abaroa (MCA)
Dr. Pau Ferrer
Dr. Nuria Llobregat
Eng. Javier Bañuls
Eng. Sofía Marquina
Eng. Tomás Riera
Verified reviews
Student Reviews
Reviews collected and verified by Opynio, not written by us.
Outcomes
Learning Outcomes
- 01Understand maritime data
- 02Prepare data
- 03Analyse operations
- 04Build predictive models
- 05Assess efficiency and emissions
- 06Communicate results
Careers
Career Opportunities
01Port data analyst: Indicators and analytics at port authorities.
02Maritime data scientist: Predictive models for shipping lines and terminals.
03Fleet performance analyst: Vessel fuel use, efficiency and emissions.
04Business intelligence specialist: Dashboards for the maritime sector.
05Port digital transformation consultant: Data projects in ports.
06Maritime traffic analyst: Route and demand studies.
Questions
Entry Requirements
It is not essential; the diploma includes an introduction to Python and SQL applied to sector case studies.
From open sources and sample datasets; the limitations and quality of this data are also explained.
Yes. You analyse fuel use and the carbon intensity indicators defined under the IMO framework.
Yes. The methods apply to fleets and ports of any size.
A complete analytics project for a port or a fleet, with a model and a dashboard.
100% online, with a virtual campus available 24/7, live sessions that are recorded, and tutorials with the teaching staff.
The programme involves 800 hours of study. You can work at your own pace within the timetable we give you when you enrol.
Each programme has its own start date, shown on this page and confirmed by our admissions team when you enquire.
On completing the programme you receive the Diploma in Data Science for Ports and Shipping qualification awarded by Navalis Magna Institute.
Online admissions
Admissions Process
No waiting for a phone call. If your documents are complete, you can pay in the same session.
Entry requirements
Entry profile: A degree in nautical studies, engineering, economics, logistics, statistics, computer science or a related field; or professional experience in the maritime and port sector. Language: A good working level of English to follow classes and materials. Technical requirements: A computer with a stable internet connection, an up-to-date browser and a webcam for live sessions and project presentations. Admissions process: Online application, profile review and a short interview with the academic team. We confirm your start date when you enquire.
Questions?
Frequently Asked Questions
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