Group coursework

1 - Written assignment (including essay) - 100

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Topic 1: Introduction to Shipping Data &amp; Analytics 
Data sources in shipping and algorithms 
  
Topic 2: Commercial Tools and Case studies 
Introduction to The Signal Ocean Platform 
Chartering tools 
Case studies on market monitoring, TCE calculation, vessels selection and analytics 
  
Topic 3: Chartering, Pools and Derivatives 
Vessel ﬁxing, cargo selection, pooling 
Freight Forward Agreements 
Case studies on voyage and cargo comparison, competition and supply monitoring 
  
Topic 4: Case Studies on Market Research 
Oil and Dry Bulk ﬂows 
Market fundamentals focusing on Supply and Demand 
Case studies on the Suez, Panama canals 
  
Topic 5: Energy Performance and Decarbonisation 
From consumptions to emissions 
Energy performance and decarbonisation initiatives 
Case studies on emission indices 
  
Topic 6: Investments in the Shipping/Trading space 
Shipping tech Ecosystem 
Investments, VCs and growth 
Case study on investment assessment and decision

Feedback is provided in a number of ways throughout your module. This includes feedback you receive during teaching from both peers and lecturers and that provided for formative assessment. Following an assessment, you will be given your marks and feedback in line with the assessment regulations and policy. More information on the timing and type of feedback that will be provided for each assessment will be available from the module leader. <a href='https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations'>https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations</a>

This module will support the development of all the graduate attributes. Your module leader will provide you with information about how your learning, teaching and assessment activities support your development of these attributes. The graduate attributes are: - Always learning - Engaged in the world - Technical and digital - Connected Professional - Creating Impact

In-Person - 

Directed Asynchronous - 

Self-directed - 

Maritime Economics 

Shipping Derivatives and Risk Management 

The Handbook of Maritime Economics and Business

SMM395 - Big Data in Commercial Shipping and Trading

SMM395-PRD3-PER-ALV1

The module is based on a series of lectures.

Contact hours are designed to be flexible and are delivered using a variety of methods to help you learn in the most effective way. A proportion of the core content may be delivered online and additional support materials and content will also be made available through Moodle.

Big Data in Commercial Shipping and Trading

Appreciate the intricacy of the shipping market, the various relationships between parties and how these impact commercial performance. 

Values and attitudes

Assess how technology and data science can produce quantitative data to influence trading decisions. 

Knowledge

Use technology, data and analytics to make commercial ship management decisions which produce efficient performance. 

Skills

Evaluate the processes and strategies of commercial ship management including decision making, negotiation and operations. 

Recognise the relationship between technology, data and traditional shipping practises. 

Evaluate how Data science and technology tools can help analyse the market and improve commercial decision making. 

Analyse the market structure within Shipping, the various parties and the roles that they play. 

Analyse market performance, trends and use data tools to make trading decisions for the shipping and oil industries. 

Analyse the Signal Ocean Platform and its application in the shipping industry. 