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MSc Artificial Intelligence & Data Science

  • DeadlineStudy Details:

    21 months part-time

Course Description

Please note this course is subject to approval

Our MSc Artificial Intelligence & Data Science offers a programme of study that has been designed to support the career development of AI and data science professionals by providing graduates with the in-depth knowledge, skills and experience that are required by businesses and organisations in the technology sector.

By studying this programme, learners will gain an in-depth understanding of the statistical and mathematical foundations of AI and achieve advanced practical knowledge of AI and machine learning methodologies applied to complex datasets to meet business objectives.

Suitable for recent graduates and for those looking to retrain or restart careers, the MSc Artificial Intelligence & Data Science provides an ideal pathway for those aspiring to further their career in the advanced application of artificial intelligence (AI) and data specialisms. Learners will have the opportunity to further their career from day one of the programme by gaining professional skills, status and accreditation as they progress.

We welcome learners from all backgrounds, and are committed to lifelong learning, pastoral support and to providing routes into digital careers for all graduates, especially those from groups that are currently underrepresented in the technology sector. Employers need to build teams with a diversity of thought and experience because this is both a critical factor in innovative thinking within teams and will facilitate the delivery of solutions applicable to an inclusive society.

Entry Requirements

Offers are typically made to applicants holding a minimum of lower second-class honours undergraduate degree (or equivalent) in a STEM discipline.

Please note that GCSE Grades 4 or C in English and Mathematics, or the equivalent, are required for the MSc Artificial Intelligence & Data Science.

Applicants should be confident in Python in a data setting and have an awareness of machine learning (i.e. logistic or linear regression).

Knowledge of the following packages is also required:

  • IDE’s – PyCharm, Eclipse
  • Jupyter Notebook
  • pandas
  • Matplotlib
  • NumPy
  • seaborn
  • unittest
  • Databases
  • sklearn

Fees

Please see our website for fees and funding

Student Destinations

In their daily work, an employee in this occupation interacts with a broad spectrum of people and collaborates with, and provides technical authority and insight to, a diverse business community of Senior Leaders, Data Scientists, Data Engineers, Statisticians, Analysts, Research and Development Scientists and Academics. Their interactions extend to working externally alongside other organisations, such as local and international governments, businesses, policy regulators, academic research scientists and non-technical audiences. They will work independently and collaboratively as required, reporting to Heads of Data, Chief Architects, Company Directors, Product Managers and senior decision makers within any organisation.

Module Details

Programming for Data Science
Data Driven Analytics
Advanced Statistical and Mathematical Methods
Applied Machine Intelligence
Stakeholders, Negotiation and Project Management
Communication in Business
Data Engineering
The Social Context of Artificial Intelligence and Data Science
Artificial Intelligence Capstone Project

Northeastern University London Campus

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