COURSE PROGRAMME

INTRODUCTION MEETING

BIP PRACTICAL SESSIONS

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

Time and Activity will be updated soon

TIME TABLE

Introduction to Marine Data

LECTURE 1, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • Why do we need marine data?
  • How do we measure and model the sea?
  • Different types of marine data: physical, biogeochemical, ecological; models; observations (in situ + remote)
  • What is operational oceanography?
  • Technologies used to produce marine data
  • Temporal and spatial constraints in data collection and interpretation; how to measure and interpret data avoiding pitfalls
  • The value addition chain of data; downstream services and data product delivery

Reliable oceanographic data sources.

Met-ocean data sets: climate, reanalysis, forecast and in situ data

LECTURE 2, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • Met-ocean data: types and characteristics
  • Types of products PHYS CMEMS
  • Types of products INSITU CMEMS
  • “Data lexicon”: Quality information document and product user man

Online Data Portals

LECTURE 3, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • What oceanographic data is freely available? How can this be accessed?
  • Demonstration of professional online data interfaces to visualise in near-real-time ocean data products
  • Portals from where numeric data derived from in-situ measurements, remote sensing, and forecasting models, can be downloaded
  • Demonstration of visualisation software including Panoply, the Sentinel Application Toolbox (SNAP), and QGIS, that can be used to process downloaded data
  • Simple data processing techniques to added-value products (such as colour composites, vegetation and water quality indices, etc…)

Introduction to Operational Modelling

LECTURE 4, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • What is a model?
  • Transport of a property: Eulerian vs Lagrangian
  • Discretization in space and time
  • Model limitations
  • Initial and boundary conditions
  • Downscaling
  • Types of models
  • Operational modelling cycle
  • Data assimilation, analysis and reanalysis
  • Model validation

Introduction to EMODnet
Ocean Decade’s Data and Information Strategy

LECTURE 5, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • Data management tools, principles and technologies deployed by EMODnet
  • DCO Data Sharing, Decade’s Data and Information Strategy and related initiatives

Accessing and transforming data

LECTURE 6, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • Brief introduction to web scraping and API
  • Brief introduction to data wrangling
  • Interacting with data servers part 1 (openDAP)
  • Introduction to cloud storage and cloud computing

Fundamentals and examples of marine data analysis

LECTURE 7, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • Statistical methods
  • Time series analysis
  • Spatial analysis of data fields
  • Climatological assessments

Applying AI to Oceanography

LECTURE 8, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • Introduction
  • What is Artificial Intelligence? Demystifying the hype surrounding AI
  • AI needs huge amounts of data to operate, and oceanographic data is readily available
  • Overview of different AI applications used in oceanography

Managing and Processing (Big) Scientific Data

LECTURE 9, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

Managing (Big) Scientific Data

  • IT tools and systems
  • Relational Database Management Systems
    • Data model
    • Basic properties of transactions in RDMS
  • Geo-Information systems
    • Spatial, temporal, and spatio-temporal data models
    • NoSQL Databases
    • Data models
    • Cap-theorem (consistency and availability)

Processing (Big) Scientific Data

  • Data Preprocessing
  • Overview on Distributed Data Processing
    • Hadoop, map-reduce
    • Spark
    • Flink

Introduction to learning algorithms, neural networks and clustering

LECTURE 10a, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

  • What is unsupervised learning?
  • Distinction between clustering and classification
  • Cluster properties and basic approaches to cluster analysis
  • Examples of some algorithm and applications
  • What is supervised learning?
  • Distinction between classification and regression problem
  • Learning algorithms and why are the introduced
  • Learning as an optimization problem. Gradient descent. Local optimum
  • Linear separability and complexity of neural network architecture
  • Simple (shallow) neural network implementation

Applying AI to Oceanography: case studies

LECTURE 10b Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

Case studies and demonstration of the different AI/ML models used in Oceanography

Introduction to Python

INTRO TO PHYTON, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

Part 1 is designed for beginners and those looking to refresh their Python knowledge.

  • Syntax
  • Variables
  • Data types
  • Basic operations
  • Loops
  • Conditional statements

Introduction to Python

INTRO TO PHYTON 2, Time and date will be updated soon

(Date, University, Duration)

Key points of the lecture

Part 2 builds upon the knowledge gained in Part 1 of the Introduction to Python module.

  • Functions
  • Modules
  • Libraries

Introduction to Physical Mobility in Split

INTRO TO PRACTICAL SESSIONS, Time and date will be updated soon

(Date, University, Duration)

Any more questions? Feel free to write us a mail!

For more info on the course please follow the details in the course website  or contact us through mdl@sea-eu.org