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MSc Artificial Intelligence in Finance

University of Essex

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Course options

  • Qualification

    MSc - Master of Science

  • Location

    Colchester Campus

  • Study mode

    Full time

  • Start date

    01-SEP-25

  • Duration

    1 year

Course summary

Our MSc Artificial Intelligence in Finance course offers a dynamic blend of financial theory and cutting-edge AI technologies. You will study topics such as algorithmic trading, risk management, and financial modelling, all enhanced by AI techniques like machine learning and natural language processing.

This course equips you with the skills to revolutionise traditional finance practices, driving innovation in areas like automated trading strategies and fraud detection. With a strong foundation in both finance and AI, you will be poised to excel in roles at investment firms, banks, fintech startups, and beyond, shaping the future of finance through data-driven insights and intelligent decision-making.

In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas, such as:

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Statistical and computational methods

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Machine learning models for finance

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Modelling trading strategies and predictive services that are deployed by hedge funds

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Algorithmic trading groups

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Analysis of derivatives

Risk management

Tuition fees

Students living in Hong Kong
(International fees)

£ 22,400per year

Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.

University information

University of Essex

  • University League Table

    30th

  • Campus address

    University of Essex, Wivenhoe Park, Colchester, Essex, CO4 3SQ, United Kingdom

The careers team offer dedicated international careers advice and support throughout studies and after graduation.
Central London is easily accessible from all of the university's campuses.
Gain access to the curriculum from nine European universities through the YUFE (Young Universities for the Future of Europe) virtual campus.

Subject rankings

  • Subject ranking

    55th out of 103 1

    41st out of 117 5

  • Entry standards

    / Max 227
    116 51%

    62nd

  • Graduate prospects

    / Max 100
    62.0 62%

    59th

    11
  • Student satisfaction

    / Max 4
    3.03 76%

    75th

    3
  • Entry standards

    / Max 227
    134 59%

    49th

  • Graduate prospects

    / Max 100
    90.0 90%

    28th

    15
  • Student satisfaction

    / Max 4
    3.00 75%

    63rd

    32

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