Overview
The Level 3 Extended Diploma in IT and Data Science is a comprehensive qualification designed to provide learners with a strong foundation in information technology, data analysis, and digital technologies. The course equips students with the technical knowledge, practical skills, and problem-solving abilities needed to succeed in today’s fast-growing digital and data-driven industries.
This qualification introduces learners to essential areas such as computer systems, programming, database management, cybersecurity, networking, data analytics, and emerging technologies. Students also develop analytical thinking, communication, and project management skills that are highly valued by employers and universities alike.
The programme combines theoretical learning with practical assignments and real-world applications, enabling students to gain hands-on experience in solving IT and data-related challenges. It is ideal for school leavers, aspiring IT professionals, and individuals seeking to progress into higher education or entry-level careers in technology and data science. Equivalent to advanced secondary education qualifications, the diploma prepares learners for both academic progression and employment opportunities in the digital sector.
Benefits of Studying the Level 3 Extended Diploma in IT and Data Science Online
- Flexible Learning Environment
- The online study format allows learners to study at their own pace and schedule, making it easier to balance education with personal responsibilities or work commitments. Course materials are accessible anytime and from anywhere.
- Strong Foundation in IT and Data Skills
- Students gain practical knowledge in core IT subjects and data science concepts, helping them build industry-relevant technical skills required in the modern workplace.
- Affordable and Accessible Education
- Online learning eliminates additional costs associated with travelling, accommodation, and campus facilities, making quality education more affordable and convenient.
- Interactive Learning Resources
- Learners receive access to high-quality digital resources including recorded lectures, study materials, case studies, practical exercises, and assignment support through an online learning platform.
Course Delivery
The Level 3 Extended Diploma in IT and Data Science is delivered entirely online through a modern and user-friendly learning platform.
- Online Learning Platform: Students receive 24/7 access to study materials, learning resources, assignment briefs, and recorded sessions.
- Tutor Support: Dedicated tutors provide academic guidance, feedback, and support through email, discussion forums, and virtual communication channels.
- Self-Paced Study: Learners can complete their studies at a pace that suits their individual learning style while following a structured study plan.
- Assignment-Based Assessment: The qualification is assessed through assignments, projects, and practical tasks rather than traditional examinations, allowing learners to apply knowledge to real-world scenarios.
- Student Support Services: Students benefit from ongoing customer support through phone, email, and live chat during working hours.
Units you'll study
27 units · 180 credits
13 The Field of Data Science
Learning outcomes
- Understand the core issues of data science.
- Understand the core issues of data and big data.
- Understand the core issues of artificial intelligence.
- Understand the core issues of machine learning.
- Understand the core issues of deep learning.
14 Python for Data Science
Learning outcomes
- Understand the design philosophy and features of Python.
- Understand Python’s basic data types.
- Be able to create and manipulate lists and tuples.
- Be able to create and manipulate sets and dictionaries.
- Be able to write Python functions and flow statements.
15 Creating and Interpreting Visualisations in Data Science
Learning outcomes
- Understand the role and importance of visualising data.
- Understand basic plots and charts.
- Be able to create and interpret plots and charts.
16 Data and Descriptive Statistics in Data Science
Learning outcomes
- Understand the different types of data and their characteristics.
- Understand measures of centre.
- Understand measures of spread.
- Understand measures of symmetry and peakness.
- Understand measures of joint variability and linear relation.
17 Fundamentals of Data Analytics
Learning outcomes
- Understand the processes and types of data analytics.
- Understand the data analytics ecosystem.
- Understand the issues and methods for dealing with data quality issues.
- Understand the issues and methods of basic data transformations.
18 Data Analytics with Python
Learning outcomes
- Be able to load and save data
- Be able to perform basic data wrangling and exploratory analysis.
- Be able to perform basic data cleaning tasks.
- Be able to perform basic data transformation tasks.
19 Machine Learning Methods and Models in Data Science
Learning outcomes
- Understand the concepts of basic supervised machine learning models
- Understand the concepts of basic unsupervised machine learning models
- Understand the concepts of basic reinforcement learning.
20 The Machine Learning Process
Learning outcomes
- Understand the machine learning process.
- Understand the data preparation process for machine learning models.
- Understand how to evaluate machine learning models.
- Be able to evaluate classification models.
- Understand the issues of bias and variance in models.
21 Linear Regression in Data Science
Learning outcomes
- Understand the basic theory of linear regression.
- Understand regression metrics and how to evaluate a regression model.
- Be able to perform regression calculations and analysis.
- Be able to create linear regression models.
22 Logistic Regression in Data Science
Learning outcomes
- Understand the basic theory of logistic regression.
- Be able to perform logistic regression calculations.
- Be able to create logistic regression models.
23 Decision Trees in Data Science
Learning outcomes
- Understand what a decision tree is in data science.
- Understand how to construct a decision tree in data science.
- Be able to perform calculations using decision tree metrics in data science.
- Be able to build a decision tree model in data science.
24 K-means Clustering in Data Science
Learning outcomes
- Understand the theory of k means clustering.
- Understand how to evaluate k-means clusters
- Be able to create and evaluate a k-means model.
25 Synthetic Data for Privacy and Security in Data Science
Learning outcomes
- Understand the core issues of data privacy and security.
- Understand the basics of differential privacy.
- Understand the core issues of synthetic data.
- Understand the synthetic data ecosystem.
- Be able to create anonymised or fake data.
26 Graphs and Graph Data Science
Learning outcomes
- Understand different types of graphs and their properties.
- Understand the core types of graph data models.
- Understand the graph ecosystem.
- Understand the types of graph data science and graph algorithms.
27 Learning Outcomes
Learning outcomes
- The ability to read and use appropriate literature with a full and critical understanding
- The ability to think independently and solve problems.
- Apply subject knowledge and understanding to address familiar and unfamiliar problems.
- Recognise the moral and ethical issues of business practice and research, appreciating the need for ethical standards and professional codes of conduct.
- An appreciation of the interdisciplinary nature of business and service provision.
- Capacity to give a clear and accurate account of a subject, in a mature way and engage in debate and dialogue both with specialists and non-specialists
- Transferable skills and knowledge that will enable individuals to meet changes in business.
- To motivate individuals to progress to further professional development through future study or as part of their chosen career.
Tap a unit to see what you'll learn.
Entry requirements
- The qualifications have been designed to be accessible without artificial barriers that restrict access, for this qualification applicants must be aged 18 or over.
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Study & assessment
- 24/7 access to the online learning portal
- Tutor support: academic questions answered within 48 hours
- Assignments marked with feedback in 5 to 7 working days
- No exams: you are assessed through written assignments
- 18 months of portal access from enrolment
- Learner support team, Mon–Fri, 09:00–17:30 (UK time)
How you're assessed
- Assessment is via assignment submission only.
- No Exams
Qualification
- Course level
- Level 3
- Same level as A levels
- Awarding body
- QUALIFI Qualifications
- Regulated by Ofqual (610/5600/5)
- Credits
- 180
- on the RQF
Qualifi is an awarding organisation recognised by Ofqual, the regulator of qualifications in England. This course leads to the Qualifi Level 3 Extended Diploma in IT and Data Science (Ofqual qualification number 610/5600/5), at Level 3 on the Regulated Qualifications Framework (RQF). It carries 180 credits and 1800 hours of total qualification time. Your certificate is issued by Qualifi when you complete the qualification.
Careers & progression
Successful completion of the qualification provides learners with opportunities for further study and career development.
1. Higher Education Opportunities
Learners may progress to:
- Level 4 and Level 5 IT qualifications
- Foundation Degrees in Computing or Data Science
- Higher National Diplomas (HNDs)
- Undergraduate degree programmes in:
- Computer Science
- Information Technology
- Data Science
- Cybersecurity
- Software Engineering
- Business Information Systems
2. Employment Opportunities
The qualification helps prepare learners for entry-level roles within the IT and digital technology industries, such as:
- IT Support Assistant
- Junior Data Analyst
- Helpdesk Technician
- Junior Software Developer
- Database Assistant
- Web Support Assistant
- Digital Operations Assistant
- Technical Support Executive
These roles are in demand across sectors including technology, finance, healthcare, retail, education, logistics, and telecommunications.
Fees & payment plans
Questions about this course
How do I enrol on this course?
You can enrol on Level 3 Extended Diploma in IT and Data Science (QUALIFI) directly from this course page. Choose your preferred payment option, complete the enrolment form, and follow the secure checkout steps. The Inspire College admissions team can also help if you want to ask a question before enrolling.
Can I start this course immediately?
Yes. Once your enrolment for Level 3 Extended Diploma in IT and Data Science (QUALIFI) is processed, you will receive access details for the online learning platform so you can begin your studies without waiting for a fixed intake date.
How long will I have access to the learning platform?
Your access period for Level 3 Extended Diploma in IT and Data Science (QUALIFI) is designed to give you enough time to work through the course at a flexible pace. The expected study duration is 6-9 months, and your enrolment information will confirm the exact access period available for this course.
Are there any exams for this course?
Level 3 Extended Diploma in IT and Data Science (QUALIFI) is normally assessed through coursework and assignments rather than traditional exams. If a specific exam or practical assessment applies, it will be explained in the assessment section of this page.
How are assignments submitted?
Assignments for Level 3 Extended Diploma in IT and Data Science (QUALIFI) are completed and submitted online through the learning platform. Your tutor will review your work and provide feedback so you can make progress through each required unit.
Is tutor support included?
Yes. Tutor support is included with Level 3 Extended Diploma in IT and Data Science (QUALIFI). You can use this support for guidance on course content, assignment preparation, and feedback during your studies.
What payment options are available?
The available payment options for Level 3 Extended Diploma in IT and Data Science (QUALIFI) are shown on this page. Depending on the current course setup, you may be able to pay in full or use a deposit with monthly instalments.
Will I receive a certificate after completing this course?
Once you have successfully completed all required modules and assignments for Level 3 Extended Diploma in IT and Data Science (QUALIFI), your work will be assessed and processed for certification through QUALIFI Qualifications, where applicable.
Is this qualification recognised?
Level 3 Extended Diploma in IT and Data Science (QUALIFI) follows the qualification details shown on this course page. Where the course is linked to an awarding body or regulated qualification, those details are displayed so you can check recognition before enrolling.
Can I study this course while working full-time?
Yes. Level 3 Extended Diploma in IT and Data Science (QUALIFI) is delivered online with flexible access, making it suitable for learners balancing study with work, family, or other commitments.
