OTHM Level 7 Diploma in Data Science

Develop advanced expertise in data science, statistical analysis, predictive modelling, data visualisation, machine learning and artificial intelligence through...

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Course Overview

The OTHM Level 7 Diploma in Data Science is a postgraduate-level qualification designed to develop advanced knowledge and practical skills in data analysis, statistical methods, predictive modelling, machine learning and artificial intelligence.


The programme focuses on extracting meaningful insights from complex datasets and using evidence to support business decisions, identify opportunities and solve organisational problems.


Learners explore the foundations of data science, probability and statistics, predictive analytics, data visualisation, data mining, machine learning, artificial intelligence and advanced computing research methods.


Through analytical assignments and research-based activities, learners develop the ability to evaluate data, select appropriate analytical techniques, interpret results and communicate findings to technical and non-technical audiences.


Qualification at a Glance


  • Awarding Organisation: OTHM
  • Qualification: Level 7 Diploma in Data Science
  • Qualification Level: Level 7
  • Total Units: 6 mandatory units
  • Total Credits: 120
  • Guided Learning Hours: 480
  • Total Qualification Time: 1,200 hours
  • Recommended Duration: One academic year for full-time study
  • Assessment: Coursework and assignments
  • Grading: Pass or Fail
  • Language of Assessment: English


Assessment Method


The qualification is assessed through coursework and assignments. Learners must provide evidence that they have achieved the specified learning outcomes and met the assessment criteria for each mandatory unit.


Units are internally assessed by the approved centre and externally verified by OTHM. Learners must satisfy all relevant assessment criteria to achieve a pass.


Assessment tasks, report requirements and marking criteria must follow the current OTHM assignment briefs issued for the applicable registration period.


Entry Requirements


Applicants must meet the current OTHM entry requirements. The published entry profile includes:


  • An honours degree in a related subject, a UK Level 6 Diploma, or an equivalent overseas qualification.
  • Mature applicants with relevant management experience may be considered, subject to confirmation by the delivery centre.
  • Applicants must be at least 21 years old at the beginning of the course.
  • Applicants who are not from a majority English-speaking country must provide evidence of English-language competency in accordance with OTHM requirements.
  • The delivery centre must check qualifications, experience and English-language evidence before confirming eligibility.


Who Should Apply?


This qualification may be suitable for:


  • Graduates in computing, information technology, mathematics, statistics or related subjects.
  • IT professionals seeking to develop advanced data science skills.
  • Analysts who want to strengthen their statistical and predictive modelling knowledge.
  • Professionals interested in machine learning and artificial intelligence applications.
  • Individuals seeking to use data analytics to support organisational decisions.
  • Learners planning further postgraduate study in data science or related fields.


Progression Opportunities


Successful learners may progress to further study, including eligible master's top-up programmes at universities that accept the qualification.


OTHM Level 7 Diplomas are positioned at the same RQF level as master's degrees but are shorter qualifications. A full master's degree normally requires an additional dissertation or other requirements specified by the university.


Admission, credit transfer and advanced entry are not automatic. Learners should confirm eligibility and progression arrangements directly with the receiving institution.


Career Development


The qualification may support career development towards roles such as:


  • Data analyst
  • Junior data scientist
  • Business intelligence analyst
  • Predictive analytics analyst
  • Machine learning analyst
  • Data visualisation specialist
  • Research analyst
  • Data-driven business analyst


Specific roles may require practical programming experience, a portfolio of projects, additional technical skills or relevant professional experience.


Study with Versa Institute London


Versa Institute London aims to support learners in developing their analytical knowledge, research skills and professional confidence.


Contact our team to confirm course availability, tuition fees, admission requirements and current study arrangements.


Website: www.versainstitute.org.uk

Email: info@versainstitute.org.uk

Telephone: +44 0808 136 0001

Location: London, United Kingdom


Important information: The current OTHM specification and assignment briefs take precedence over this general course description. Progression and employment opportunities depend on the requirements of the relevant university or employer.

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Course curriculum

Requirment

  • Applicants should hold an honours degree in a related subject, a UK Level 6 Diploma or an equivalent overseas qualification.

  • Applicants must be at least 21 years old at the beginning of the course.

  • Mature applicants with relevant management experience may be considered by the delivery centre.

  • Applicants must provide evidence of English-language competency where required by OTHM.

  • A background in computing, IT, mathematics, statistics or a related subject is recommended.

  • Basic programming and quantitative reasoning skills are beneficial for advanced data science study.

  • Learners should be prepared for independent research, analytical assignments and academic report writing.

  • Admission is subject to verification of qualifications, experience and the current OTHM entry requirements.

Outcomes

  • Demonstrate advanced understanding of data science concepts and applications.

  • Evaluate data quality, data sources and governance requirements.

  • Apply probability and statistical methods to data analysis.

  • Select and evaluate predictive modelling and forecasting techniques.

  • Prepare, analyse and visualise complex datasets.

  • Apply appropriate data mining, machine learning and artificial intelligence techniques.

  • Interpret analytical results and communicate data-driven insights.

  • Evaluate model performance and recognise limitations or potential bias.

  • Consider ethical, privacy and responsible-data requirements.

  • Formulate research questions and select appropriate research methods.

  • Analyse evidence and present defensible research conclusions.

  • Communicate findings and recommendations to technical and business audiences.

  • Identify opportunities for further postgraduate study and professional development.

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VERSA INSTITUTE LONDON

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