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QUALIFI Level 7 Diploma in Data Science

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What you'll learn

The Level 7 Diploma in Data Science is tailored to equip future Data Scientists, Data Analysts, and Artificial Intelligence specialists with the necessary skills to leverage the expanding business and employment prospects in this dynamic field. This program acknowledges the evolution of data science into a pivotal fourth-generation profession fueled by the rise of cloud computing, big data, and artificial intelligence.

  • QUALIFI Level 7 Diploma in Data Science: Advanced program.
  • Focus on data analysis, machine learning, and big data.
  • Skills in math, stats, Python, and SQL.
  • Prepares for roles in Data Science AI.
  • Foundation for further studies.

The curriculum is structured to empower learners in mathematics, statistics, and programming languages like R, Python, and SQL. Additionally, the Diploma lays a robust foundation for potential advancement towards Master's Degrees in various disciplines.


Key Benefits

  • Assess the notion of transformation and the pivotal technologies propelling it forward.
  • Utilise decision tree and random forest algorithms for both classification and regression tasks.
  • Effectively handle and oversee multiple datasets within both R and Python environments.
  • Construct models utilising binary logistic regression and evaluate their effectiveness.
  • Evaluate the principles and applications of time series analysis and conduct tests for stationarity in time series data.
  • Evaluate the strategic significance of implementing Big Data and Artificial Intelligence within business organisations.
  • Authenticate models through data partitioning, out-of-sample testing, and cross-validation.
  • Examine the concept of variance through Analysis of Variance (ANOVA) and select a suitable ANOVA or ANCOVA model accordingly.
  • Assess the ethical practices implemented within organisations and their relevance to ethical concerns in Data Science.
  • Conduct text analysis on data sourced from social media platforms.
  • Utilise the Hadoop framework for Big Data Analytics.
  • Use SQL programming for data analysis.
  • Evaluate classification techniques such as the Naïve Bayes method and the support vector machine algorithm.
  • Comprehend both hierarchical and non-hierarchical cluster analysis and evaluate the outcomes they yield.
  • Validate ARIMA (Auto Regressive Integrated Moving Average) models and use estimation.
  • Construct generalised linear models and conduct survival analysis, including Cox regression.


About Awarding Body

Qualifi is a UK Government (Ofqual.gov.uk) regulated awarding organisation and has developed a reputation for supporting relevant skills in a range of job roles and industries, including Leadership, Enterprise and Management, Hospitality and catering, Health and Social Care, Business Process Outsourcing and Public Services. Qualifi is also a signatory to BIS international commitments of quality. The following are the key facts about Qualifi.

  • Regulated by Ofqual.gov.uk
  • World Education Services (WES) Recognised

What is Included?

  • Outstanding Tutor Support: EDVORO provides consistent and helpful guidance throughout the course. Learners can seek assistance through the EDVORO Support Desk Portal.
  • Cutting-Edge Learning Management Platform: Access to a modern platform that contains essential learning resources and facilitates communication with the support desk team.
  • Quality Learning Materials include well-structured lecture notes, study guides, and practical applications. Real-world examples and case studies are integrated to help learners apply their knowledge effectively. These materials are available in well-structured pathway books, letter notes, PDF, PowerPoint, or Interactive Text Content formats on the learning portal.
  • Formative Assessment Feedback: Tutors provide feedback on formative assessments, helping learners improve their achievements throughout the program.
  • Summative Assessment feedback: Tutors provide feedback on summative assessments; this kind of feedback can be instrumental in helping students achieve their academic goals.  
  • Accessible Assessment Materials: All assessment materials are conveniently accessible through the online learning platform.
  • Supervision for All Modules: This suggests that oversight and guidance are provided for every module of the course.
  • Multiplatform Accessibility: Learners can access course materials through various devices such as smartphones, laptops, tablets, or desktops. This flexibility allows students to study at their convenience.
  • Limitless Learning Opportunities: EDVORO offers a range of innovative online and blended learning experiences to help learners expand their knowledge.
  • Convenience, Flexibility, Support, and User-Friendliness: Core principles of online learning at EDVORO.


  • Assignment based Assessment
  • No exam


Entry Requirements

  •  Accessible qualification without unnecessary barriers.
  • Entry through centre interview.
  • Expected qualifications:
  • Level 6 in related sector OR
  • Bachelor's degree OR
  • 3 years' relevant work experience.
  • Experience without formal qualifications may be considered based on interview and ability demonstration.


Upon completing the QUALIFI Level 7 Diploma in Data Science, learners can advance to:

  • QUALIFI Level 7 and/or 8 Diploma programs.
  • Immediate entry into related professions.
  • Pursue a dissertation-only Master's Degree through our University partnerships

Why gain Qualification

  • QUALIFI diplomas provide industry-recognised certification, showcasing expertise.
  • They facilitate career growth, enabling access to higher-level positions and increased earnings.
  • Specialised knowledge is a hallmark of QUALIFI diplomas, valued in niche industries.
  • Practical training ensures hands-on skill development for immediate workplace application.
  • Flexible learning options, including part-time and online courses, accommodate diverse schedules.
  • QUALIFI qualifications are globally recognised, facilitating international work and education opportunities.
  • Business-focused diplomas are beneficial for aspiring entrepreneurs and those starting ventures.
  • Networking, regulatory compliance, staying updated with industry trends, and enhanced confidence are additional benefits of a QUALIFI diploma.

Career Pathways

The Qualifi Level 7 Diploma in Data Science can open many career pathways including, but not limited to:

  • Data Analyst
  • Associate data scientist
  • Data Scientist (senior-level)
  • Product Manager
  • Lead data scientist
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Course Content

Reference No : L/618/4971

This unit imparts a thorough comprehension of statistical distribution and hypothesis testing. It encompasses distributions like Binomial, Poisson, Normal, Log Normal, Exponential, t, F, and Chi-Square. Both parametric and non-parametric tests relevant to research are included. The unit guides learners in formulating research hypotheses, choosing suitable hypothesis tests, primarily utilising R programs for testing, and drawing inferences from the generated output. Additionally, planned experiments are part of the curriculum.

Credit : 12 || TQT : 120

Reference No : J/618/4970

This unit offers a comprehensive grasp of R and Python programming alongside fundamental statistics. It encompasses writing commands in R and Python for data handling and basic statistical analysis. The unit enables learners to execute descriptive statistics and present data using suitable graphs/diagrams and is a stepping stone for advanced analytics. Exploratory Data Analysis forms the basis of many industry analyses, and a thorough study of this equips learners to conduct data health assessments and offer initial business insights.

Credit : 8 || TQT : 80

Reference No : R/618/4972

This unit establishes a robust groundwork for predictive modelling. It aims to outline the entire modelling process through real-life case studies. Since numerous concepts in predictive modelling methods are widely applicable, this unit delves into them in depth. Proficiency in predictive modelling is crucial for a discerning data scientist, as many business challenges hinge on accurately forecasting future outcomes.

Credit : 15 || TQT : 150

Reference No : Y/618/4973

This unit introduces learners to developing models for categorical dependent variables. It focuses on the intricacies of constructing models for binary dependent variables, prevalent in domains like risk management, marketing, and clinical research. Additionally, the unit will delve into multinomial models and ordinal scaled variables.

Credit : 15 || TQT : 150

Reference No : D/618/4974

This unit aims to explore time series forecasting techniques. Learners will engage in the analysis and prediction of macroeconomic variables like GDP and inflation. Additionally, the unit will cover panel data regression methods.

Credit : 15 || TQT : 150

Reference No : H/618/4975

Data reduction is a pivotal step in business analytics endeavours. This unit instructs learners on techniques like PCA, factor analysis, and MDS for data reduction. Additionally, they will learn to create segments using cluster analysis methods. This process of segmenting and analysing is crucial for handling large datasets, as it unveils detailed insights once the segmentation is done thoughtfully.

Credit : 15 || TQT : 150

Reference No : K/618/4976

In this unit, learners will explore the applications of various machine learning algorithms and the next-generation techniques used alongside traditional predictive modelling methods. The focus will be on their use in solving classification problems.

Credit : 15 || TQT : 150

Reference No : M/618/4977

This module will instruct learners to analyse unstructured data through text mining. The emphasis will be on sentiment analysis of text data, including content from social media platforms. Additionally, learners will be introduced to the "SHINY" package for creating interactive web applications directly from R. The unit will also cover Big Data concepts and artificial intelligence, along with an introduction to SQL programming and its application in data management.

Credit : 15 || TQT : 150

Reference No : T/618/4978

Integrating Cloud computing, Big Data, Artificial Intelligence, and The Internet of Things is reshaping organisations worldwide. It's a make-or-break moment: they must adapt to thrive or risk becoming obsolete. This unit familiarises learners with the strategic and managerial hurdles posed by the digital technology revolution in business and organisations. This transformation affects operational and strategic norms, organisational structures, work dynamics, and employment paradigms on a global scale.

Credit : 10 || TQT : 100

Delivery Methods

The program is delivered by Edvoro, a flagship of the School of Business and Technology London, and awarded by QUALIFI; Edvoro offers a range of flexible delivery methods to cater to the diverse needs of its learners. These options include online and blended learning, allowing learners to select the mode of study that best suits their preferences and schedules. The program is designed to be self-paced and is facilitated through Edvoro's state-of-the-art Learning Management System.

Edvoro ensures learners can engage with their tutors through the Edvoro Support Desk Portal System. This platform enables learners to discuss course materials, seek guidance and assistance, and request feedback on their assignments, fostering a dynamic and interactive learning experience.

Edvoro stands out by providing exceptional support and infrastructure for online and blended learning formats. We have adopted an innovative approach to learning, replacing traditional classroom-based instruction with web-based learning while maintaining an exceptionally high level of support. Learners who enrol at Edvoro benefit from the dedicated guidance of a tutor throughout their learning journey, ensuring comprehensive support from beginning to end, whether they choose the online or blended learning option.

Resources and Support

Edvoro is committed to providing unwavering support throughout your educational journey. Our dedicated support team is a crucial link between tutors and learners, ensuring that guidance, assessment feedback, and additional study assistance are delivered promptly and effectively. When a learner submits a support request via the support desk portal for advice, assessment feedback, or any other service, one of the support team members assigns the request to an appropriate tutor. Once the support team receives a response from the allocated tutor, the information is promptly made accessible to the learner through the portal. This structured support system is designed to assist learners and streamline support processes efficiently.

Edvoro's competitive edge is enhanced by the high-quality learning materials crafted by industry experts. The learning materials encompass well-structured pathway books, letter notes, practical applications with real-world examples, and case studies that empower learners to apply their knowledge effectively. Learning materials are conveniently accessible in one of three formats, PDF, PowerPoint, or Interactive Text Content, through the learning portal, providing learners with versatile options for accessing and engaging with the content.

Study Options
  • Duration 12 Months
  • Credits 120
  • Accreditation Ofqual.Gov.UK
  • Intake Every Month
  • Study Mode Online / Blended
  • Course Materials: Well Structured
  • All Inclusive Cost Yes
  • Tutor Desk Yes
  • Support Desk Yes
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