Qualifi Level 07

Diploma in Data Science

  • Duration :
    01 Year
  • Delivery :
    Part Time
    Full Time
    Distance Learning
  • Intakes :
  • Fee :

    GBP 4,000.00

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Overview

With the emergence of cloud computing, big data and artificial intelligence, data science has become a key fourth generation profession. The Level 7 Postgraduate Diploma in Data Science has been developed to prepare aspiring Data Scientists, Data Analysts and Artificial Intelligence specialists to take advantage of the growing business and employment opportunities in these fields.

The Diploma is designed to enable learners to gain skills in maths, statistics and programming in R, Python and SQL. The Diploma also provides a sound basis for a progression to Masters Degrees in a number of relevant disciplines.

Entry requirements

  • A minimum of a Level 6 qualification in a related sector or;
  • Bachelors degree or;
  • A minimum of 3 years’ work experience which demonstrates current and relevant industry knowledge.

Mandatory Units

Exploratory Data Analysis
Statistical Inference
Fundamentals of Predictive Modelling
Advanced Predictive Modelling
Time Series Analysis
Unsupervised Multivariate Methods
Machine Learning
Further Topics in Data Science
Contemporary Themes in Business Strategy

  • 8 Credits

    Exploratory Data Analysis

  • 12 Credits

    Statistical Inference

  • 15 Credits

    Fundamentals of Predictive Modelling

  • 15 Credits

    Advanced Predictive Modelling

  • 15 Credits

    Time Series Analysis

  • 15 Credits

    Unsupervised Multivariate Methods

  • 15 Credits

    Machine Learning

  • 15 Credits

    Further Topics in Data Science

  • 10 Credits

    Contemporary Themes in Business Strategy

Learning Outcomes

  • Gain the mathematical and statistical knowledge and understanding required to carry out basic and advanced data analysis.
  • Develop sufficient skill in the R, Python and SQL programming languages to use them to successfully carry out data analysis to an advanced level.
  • Develop a strong understanding of data management, including evaluation, structuring and cleaning of data for analysis.
  • Become familiar with and use the tools and techniques used in data visualisation
  • Develop a comprehensive knowledge of classical data analytics, including statistical inference,
    predictive modelling, time series analysis and data reduction.
  • Become familiar with and apply common machine learning techniques to business and other problems
    in order to uncover options and solutions for them.
  • Develop an understanding of essential concepts from contemporary themes in business.
  • Understand, evaluate and apply data science and analytics within business and organisational contexts.