CES Resolution: RPC-SO-03-No. 094-2021

Admission Profile:

Hold a degree in:

• Computer Engineering.
• Systems Engineering.
• Information Technology Engineering.
• Telematics Engineering.
• Telecommunications Engineering.
• Information and Communication Technology (ICT) Engineering.
• Statistical Computing.

Graduation Profile:

The Professional Master"s in Data Science will be capable of:

Knowledge:

• Integrating the interrelationship of Data Science-environment-society-economy into their worldview within a context of knowledge generation based on the ancestral knowledge of Ecuadorian culture and technologies.

Skills:

• Establishing correct information security schemes.
• Utilising services for the efficient storage of information in the cloud.
• Proposing information analysis models based on historical data to make inferences about the studied population.
• Inferring properties of a statistical population from a sample using methods and procedures of statistical inference.
• Identifying information and data issues within organisations related to the volume of information.
• Recognising the characteristics of data to establish evaluation metrics for the quality of data to be processed within the context of the business problem to be solved.
• Applying computerised statistical methods in systems or processes related to the field of Data Science.
• Establishing effective communication with specialists from other fields of knowledge, as well as with social and governmental actors, to undertake research, technological development, and consultancy actions.

Comprehension:

• Applying knowledge of data science to develop algorithms using soft computing techniques to achieve the best productivity.
• Developing processes that facilitate the proper management of Data Science systems in relation to the socio-economic conditions of the environment.
• Implementing development projects in the community context with the application of Data Science.
• Applying managerial skills to create and lead companies related to the areas of Data Science.
• Analysing the conceptual, methodological aspects and tools for the characterisation of Data Science systems.

Ethics and Responsibility:

• Creating useful knowledge for their environment by employing responsible behaviour from an ethical dimension.
• Disciplinedly acquiring knowledge for the proper and supportive management of resources in Data Science.

Objectives

To train human talent in fields related to Data Science through a formative process that promotes the theoretical-practical learning of a set of techniques and theories of data retrieval, security, analysis, processing, and management, predictive models, programming, statistical learning, pattern recognition, and data mining, for the generation of knowledge that contributes to the timely strategic business decision-making in public and private companies.

Class times:

Saturdays: 08:00 - 17:00
Sundays: 08:00 - 17:00

Modules:

• Scientific Research Methodology
• Statistical Inference and Modelling
• Data Mining
• Fundamentals of Machine Learning
• IT Infrastructure and Architecture
• Advanced Data Mining
• Data Privacy and Security
• Big Data
• Information Visualisation
• Thesis Workshop I
• Web Mining
• Cybersecurity
• Cloud Processing
• Thesis Workshop II

Research Line