The CBIT Associate Extended Diploma in Data Science (Level 5) is a comprehensive, industry-aligned course designed to equip you with the theoretical understanding and practical skills needed to thrive in the fast-evolving field of data science.
This course covers a wide range of topics, including data literacy, statistical foundations, programming, artificial intelligence, machine learning, deep learning, big data, and data mining.
The CBIT Associate Extended Diploma in Data Science Management is a comprehensive course comprising twelve modules that can typically be completed in twelve to eighteen months.
The curriculum is designed around real-world applications and current industry trends, ensuring that you are well-prepared to handle complex datasets, extract insights, and make informed, data-driven decisions across various sectors.
Designed for aspiring data scientists and analysts looking to start a career in data science, IT professionals aiming to upskill or transition into data-driven roles, business analysts and decision-makers seeking to leverage data for strategic insights, students and recent graduates in computer science, mathematics, or related fields, and career changers from non-technical backgrounds who are passionate about working with data.
Course fees cover all costs.
High-quality learning resources and study guides developed by subject-matter expert tutors approved by CBIT.
12 - 18 months
You will receive comprehensive formative assessment feedback from your tutor before your final submission, which will help you understand flaws, increase your knowledge, and elevate your grade.
Schedule online personal tutor meetings whenever you want, which will help you get the most out of your studies and provide guidance, support and encouragement.
Curriculum designed and developed by tutors with extensive industry experience in the in the Data Science discipline.
All assessment materials are readily available on the user-friendly online learning platform, 'MyLearnDirect', ensuring you have everything you need at your fingertips.
Study from anywhere at your own pace, 100% online.
24 months
Online or blended
You'll receive unlimited support from our expert tutors, ensuring you have all the help you need to succeed.
You can raise queries, request tutor support and ask for a call back whenever you need guidance and assistance.
If you choose blended learning, you can schedule live online classes for each module at your convenience.
Upon successfully completing the programme, learners will be awarded a certification from CBIT, enhancing their credentials and professional value.
Designed for aspiring data scientists and analysts looking to start a career in data science, IT professionals aiming to upskill or transition into data-driven roles, business analysts and decision-makers seeking to leverage data for strategic insights, students and recent graduates in computer science, mathematics, or related fields, and career changers from non-technical backgrounds who are passionate about working with data.
Study from anywhere at your own pace, 100% online.
12 - 18 months
Course fees cover all costs.
You'll receive unlimited support from our expert tutors, ensuring you have all the help you need to succeed.
Online or blended
You can raise queries, request tutor support and ask for a call back whenever you need guidance and assistance.
You will receive comprehensive formative assessment feedback from your tutor before your final submission, which will help you understand flaws, increase your knowledge, and elevate your grade.
This coursee offers a cohesive, end-to-end data science curriculum that blends foundational theory with hands-on practice, ensuring you graduate ready to extract actionable insights from complex datasets. You will study critical domains, including data collection and cleaning, statistical inference, machine learning, deep learning, big-data architectures, and data visualisation alongside essential ethical and governance considerations, completed over a period of 8 to 12 months.
Ideal for aspiring data scientists, IT professionals expanding into analytics, and business leaders seeking to make data-driven decisions, this Extended Diploma combines academic rigour with real-world problem-solving. Through case studies, and lab exercises, you’ll learn not just how algorithms work, but when and why to apply them, and how to communicate results to stakeholders.
The CBIT Advanced Award in Data Science (Level 7) with Integrated Real-world Experience is designed for senior data professionals looking to strengthen their strategic data science expertise through hands-on, industry-relevant project work.
The Centre for Business and Information Technology (CBIT) is dedicated to creating high-quality programmes and providing exceptional learning experiences that enhance the skills and knowledge of business and IT professionals. CBIT inspires and improves performance through innovative business and IT programmes, enabling professionals to reach their full potential.
CBIT's business programmes have received prestigious recognition from the Chartered Management Institute (CMI), signifying our commitment to excellence. These programmes align with the CMI Quality Benchmark and adhere to the high professional standards set by the CMI. Additionally, CBIT has earned BCS Tech10 Accreditation from BCS - The Chartered Institute for IT for select IT programmes, establishing a benchmark for quality in the technology field. This accreditation demonstrates that CBIT programmes meet rigorous standards.
If you're interested in exploring other courses within the CBIT Associate in Data Science suite, please find them listed below. Selecting a course that aligns with your career goals and aspirations can help you achieve your desired progression
This course is ideal for aspiring data scientists and analysts looking to start a career in data science, IT professionals aiming to upskill or transition into data-driven roles, business analysts and decision-makers seeking to leverage data for strategic insights, students and recent graduates in computer science, mathematics, or related fields, and career changers from non-technical backgrounds who are passionate about working with data.
There are no formal entry requirements to enrol in the CBIT Associate Extended Diploma in Data Science. However, CBIT expect you to meet the following criteria.
Our friendly admissions advisors will provide the best advice, considering your needs and goals.
For each module you study, you will complete a written assignment of 2,000–2,500 words and submit it online via your MyLearnDirect learning portal. Your submitted assignments will be assessed by a dedicated tutor who will provide feedback to support your progress.
Upon completing the CBIT Associate Extended Diploma in Data Science (Level 5) may pursue various career paths, including but not limited to:
You must complete all 12 modules, with a maximum of 960 hours of Total Programme Time (TPT).
Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable.
Learners are not allowed to make any request to interchange unit(s) once enrolment is complete.
Reference No : CBIT- ADM -501
Credit : N/A || TQT : Maximum of 960 hours
This Module provides learners with a foundational understanding of data science, focusing on core concepts, methods, and tools essential for working with data. The aim is to introduce learners to the data science pipeline, from data collection and processing to basic statistical analysis and visualisation. It also emphasises the importance of data quality and understanding how data can be interpreted to drive insights. By the end of the module, learners will be equipped with the theoretical knowledge necessary to understand how data science is applied in different industries.
Reference No : CBIT- ADM -502
Credit : N/A || TQT : Maximum of 960 hours
This module provides learners with a strong theoretical foundation in statistics and probability, essential for understanding data science applications. The aim is to introduce key statistical concepts, methods, and frameworks that underpin data analysis in a wide range of real-world contexts. Learners will develop the ability to apply theoretical concepts to statistical problems and interpret the results in the context of data science.
Reference No : CBIT- ADM -503
Credit : N/A || TQT : Maximum of 960 hours
This module aims to provide learners with an understanding of the fundamental principles of machine learning and neural networks, focusing on the theoretical concepts and methodologies used to extract patterns and predictions from data. Learners will explore key machine learning techniques, the mathematical foundations underlying these methods, and how neural networks are modeled based on biological learning systems. The module will enable learners to gain the knowledge necessary to apply machine learning theories to real-world data challenges in various industries.
Reference No : CBIT- ADM -504
Credit : N/A || TQT : Maximum of 960 hours
The aim of this module is to provide learners with a comprehensive understanding of the fundamental concepts, tools, and techniques in data science. This module will introduce learners to the core data science pipeline, from data collection to processing, analysis, and visualisation, enabling them to apply statistical methods to real-world data. Learners will gain insights into the theoretical underpinnings of data science while exploring how these principles are applied across different sectors.
Reference No : CBIT- ADM -505
Credit : N/A || TQT : Maximum of 960 hours
This module aims to introduce learners to the core principles of Artificial Intelligence (AI) and Big Data, focusing on the theoretical understanding of machine learning and data analysis techniques. Learners will explore how AI and Big Data technologies are applied in various sectors and gain knowledge of the challenges involved in handling and analysing large datasets.
Reference No : CBIT- ADM -506
Credit : N/A || TQT : Maximum of 960 hours
This module aims to introduce learners to the fundamental concepts of Artificial Intelligence (AI) and Deep Learning (DL). Learners will explore the theoretical underpinnings of AI models and deep learning architectures, focusing on how these models are structured, trained, and applied to solve real-world problems. The module will also examine ethical considerations in AI and deep learning.
Reference No : CBIT- ADM -507
Credit : N/A || TQT : Maximum of 960 hours
This module introduces students to core programming concepts, data structures, and database management techniques, with a focus on developing secure and efficient software solutions. It also explores key concepts of database management systems (DBMS), data modeling, and the essential security considerations required when handling data in an organisational context.
Reference No : CBIT- ADM -508
Credit : N/A || TQT : Maximum of 960 hours
This module aims to provide learners with a strong foundational knowledge of data analysis and visualisation techniques. Students will understand the role of data analysis in industry and research, learn to handle data preprocessing, and apply visualisation techniques to interpret data insights. Emphasis will be on theoretical applications and the conceptual underpinnings of data-driven decision-making.
Reference No : CBIT- ADM -509
Credit : N/A || TQT : Maximum of 960 hours
This module aims to equip learners with a foundational understanding of data structures and algorithms, focusing on theoretical aspects, complexity analysis, and the application of various algorithmic strategies. Through studying these topics, learners will gain insights into selecting appropriate data structures and algorithms for problem-solving, as well as analysing their efficiency and scalability.
Reference No : CBIT- ADM -510
Credit : N/A || TQT : Maximum of 960 hours
This module provides learners with foundational knowledge in probability and statistics, essential for understanding data analysis, inferential statistics, and decision-making under uncertainty. It aims to equip learners with the skills to analyse and interpret probabilistic data, understand statistical models, and apply various sampling and estimation methods in a theoretical context.
Reference No : CBIT- ADM -511
Credit : N/A || TQT : Maximum of 960 hours
This module aims to provide learners with a foundational understanding of data wrangling and exploration processes, emphasising theoretical knowledge and techniques essential for transforming raw data into structured formats suitable for analysis. Learners will develop insight into the key stages of data acquisition, cleaning, structuring, and preliminary analysis, preparing them to understand the complexities of handling diverse data types and sources.
Reference No : CBIT- ADM -512
Credit : N/A || TQT : Maximum of 960 hours
This module provides learners with a deep understanding of the theoretical foundations, concepts, and techniques involved in data and text mining. Learners will explore approaches to transform unstructured and semi-structured data into actionable insights. The module focuses on building knowledge of data-mining methodologies, natural language processing (NLP), feature extraction, and data indexing, while introducing learners to contemporary techniques for analysing complex datasets.
Reference No : CBIT- ADM -513
Credit : N/A || TQT : Maximum of 960 hours
This module provides learners with a theoretical foundation in machine learning concepts and methodologies. It focuses on understanding core algorithms, their applications, and the critical considerations involved in selecting and evaluating machine learning models. Learners will gain insights into supervised and unsupervised learning, key application areas, and the broader context of machine learning in data science.
Learners need to complete any combination of units to a minimum of 15 credits. The minimum Total Qualification Time is 150 hours, including 50 Guided Learning Hours
Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable.
Learners are not allowed to make any request to interchange unit(s) once enrolment is complete.
Reference No : Unit 2001V1
Credit : 6 || TQT : 60
Personal development as a team leader unit is all about the event of talents,responsibilities and knowledge of the team leader for team welfare. Inorder to understand the team leader’s responsibilities in reference to discrimination, harassment, and diversity.Learners will be also able to implement and review the development plan to meet work objectives.
Reference No : Unit 2003V1
Credit : 5 || TQT : 50
This unit helps the learner the understand the aspects of understanding and monitoring team performance using smart technique.
Reference No : Unit 2007V1
Credit : 5 || TQT : 50
The unit describes about the teams internal and external customers. Learners will be able to identifying the customer, providing the extent of service, and resolving customer issues.
Reference No : Unit 2002V1
Credit : 5 || TQT : 50
Communicating with a team unit is about organising and leading a team briefing to communicate within the team. Learners can understand the structure of team briefing, it also describes methods of involving team members within the team briefing and evaluate the result of the team briefing against its objectives.
Reference No : Unit 2004V1
Credit : 6 || TQT : 60
Controlling resources unit is about identifying, sourcing, managing, and maximising resources to realise team objectives. Discuss the consequences of resource wastage,explains methods of identifying resource wastage and actions to be taken to scale back resource wastage whilst meeting team objectives.
Reference No : Unit 2005V1
Credit : 5 || TQT : 50
"Building work relationships unit is about understanding the way to communicate and develop work relationships with the manager, team, and people outside the team. Learners can understand the need to maintain confidentiality while communicating with individuals within the team. "
Reference No : Unit 2006V1
Credit : 6 || TQT : 60
Developing team needs unit is about inducting a team member, identifying, planning,and implementing team training.This unit trains a team member to hold out a task, ensuring that training provided meets legal and organisational requirements.
School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments.
We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish.
The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations.
School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently.
Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal.
As part of the program, you will get access to CMI Management Direct, which provides a rich foundation of management and resource for students. The Management Direct is packed with content, including:
We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue a smart learning approach where the traditional regular classroom-based learning is replaced by web-based learning and the support level is incredibly high. Learners enrolled at SBTL are allocated a dedicated tutor whether it is online or blended learning, who provide learners with comprehensive guidance and support from start to finish of the course.
The significant difference between blended and online learning at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions which can be booked in advance on their convenience most of the time. In addition to the Online Live Sessions, students will also receive all the standard benefits offered to Online Learning students.
SBTL strategically and conveniently employ Blended Learning, where web-based learning using hybrid-teaching technology coupled with a block delivery of live workshops (classes) replaces the traditional regular classroom-based learning. The live sessions are provided online using Apps like GoToMeeting, Zoom or Skype. In addition to the live sessions, blended learning students will receive comprehensive tutor support through our support desk portal like online learning students.
This mode of study is treated as a Full-time study, not as Online learning. School of Business & Technology London understands that choosing the right education institution is as important as the qualifications you gain. Thus, SBTL always takes a genuine interest in the needs of our students and believe that we can drive positive change for their future.
Total Qualification Time (TQT) denotes the minimum timeframe a learner takes or requires to complete their qualification.It comprises of the GL (Hours) plus all other time taken in preparation,study or research or any other form of participation in education or training, however no direct supervision of a lecturer or tutor is required. TQT is a terminology mostly used within the qualifications regulated by Ofqual as part of the Regulated Qualification Framework (RQF). When calculating TQT, Awarding bodies take into account similar qualifications to ensure that both the quality and the requirement is met. We also consider the views and expectations of the learners of our qualifications during the development process leading to the attainment of qualification. Our learners will see TQT expressed in two ways within the qualification specifications.
Guided Learning hours are designed in a way that the learner need to complete the activities/ presentations under the instruction, guidance or supervision of a lecturer, tutor or supervisor either by physical presence or electronic means such as prepared lecture slides or learning material. Where a qualification follows a unitised structure, each unit will be allocated a GL(hours) value but where a qualification does not follow a unitised structure, GL (hours) will be allocated to the qualification as a whole. We at School of Business & Technology London provide well precise and detailed learning materials, prepared by qualified and approved tutors in line with the specifications detailed by the awarding body. Besides, learners are given constructive formative feedback for each unit emphasising for learning and development.
We at SBTL offer comprehensive learning materials to the learners made by qualified and approved tutors. In order to accomplish the qualification, learners are needed to undertake further research and readings to achieve the learning outcomes. Thus for further research and readings learners may need to access a number of books and/or journals ,articles from external sources such as libraries or online libraries when and where required. . If you are studying a CMI qualification, you will be provided with access to CMI Management Direct portal where you will have access to several eBooks, Journals and videos etc.
The course fee for online learning and blended learning are different. The fee details provided in the ‘fees and funding section’ of each course is meant for online learning only. If you want to know the fee details for a blended learning program, please speak to our admission team or email at admission@sbusinesslondon.ac.uk.
SBTL continuously innovates and provides high-quality education to transform the skills, knowledge and understanding of our students to enhance their employability and enable them to compete successfully in the dynamic and ever-changing business world. Blended Learning students at SBTL will receive the following benefits.
The number of hours of live sessions offered for blended learning students varies according to the course level they enrolled. Please see the illustrative examples below.
At School of Business & Technology London, we deploy a cutting-edge learning management system where the learners are enabled to pursue accredited online education with a simplified process. We focus on conferring utmost flexibility on you for schedules and accessibility and learner decide when and how to study. We offer advanced and proficient course portfolio, which meets the current global professional needs. Learners can accomplish their qualification at their own pace, and they don't need to put their life on hold to get qualified.
Quality learning materials made by industry experts is a significant competitive edge of School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal.
Assessments are conducted through assignments and exams. Most of the courses offered at SBTL do to come with exams but only assignments. To find out whether your course requires exams, please visit the relevant course details page on our website and check the assessment section.
Being an approved centre, School of Business & Technology London reserve the right to preselect units to deliver each qualification. For every course, SBTL has preselected units (modules) as per the criteria among the various units listed in the course specification provided by the awarding body. The preselected units are shown in the details page of every course on our website.
Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable.
Learners are not allowed to make any request to interchange unit(s) once enrolment is complete.
The fee can be paid in either of the following methods:
As it is a purely online program you have the flexibility to complete the learning at your ease. However, there is a course expiry date for each awarding body. Learner(s) is required to complete their course within the duration specified for each course. If the learner(s) would require additional time, they should inform the admissions manager during the enrollment process. The course duration for all the (a) award programs are 6 months, (b) certificate programs are 10 months, (c) diploma programs are 12 months and (d) extended diploma programs are 18 months. The course duration for the degree top-up programs are subject to the relevant university where the learner(s) is enrolled. This course duration is applicable for all the programs delivered by SBTL, irrespective of the awarding bodies. Suppose, for any reason, you exceed the maximum course duration, and additional time was not agreed upon during enrolment. In that case, you must request a course extension in writing within 14 days of the course expiry date. If your request is approved, a course extension fee is applicable. The applicable course extension fee is £150.00 plus VAT, which acts towards the administration charges for the course extension. You may also need to pay any awarding body re-registration fee if applicable, which will be subject to the policy of the respective awarding body .
The fee can be paid in two ways; either it can be made with a single payment or monthly instalments as specified in the course details page. Students who make a single amount will get an extra discount.
Both monthly and single payment details for online learning are given on our site. However, if you want to have a customised payment plan, please speak to our admission team or email at admission@sbusinesslondon.ac.uk
Select your course
You choose the course that you decide to pursue but ensure you meet the entry requirements.
Enrol
Once the course is selected, you make an application via our website and contact us via email admission@sbusinesslondon.ac.uk. You can make the payment online or bank transfer- either a single payment or easily monthly instalments.
Access to Learning Portal
You will be provided with the login credentials to access the learning portal, which will have all sorts of pathway learning materials to complete your programs successfully. The simplified materials are easy to understand and would help you to work on your assignments.
Dedicated Tutor
You will be allocated to a tutor and supported by our academic support team who will assist, and advice about your course and assignments. Once you accomplish your assignment, your allocated tutor will assess your work and provides you with formative feedback which will help you to improve your assignment prior to the final submission.
Assessment of Assignments.
Feedback is provided to you regularly when you improve your work. Once the final submission is made, marks and grades are published via the learning portal.
Certification
You will get your certificate once you completed the course successfully. You can then move on to your desired career with the help of the accredited certificate. You can enrol for a different course with us; if you want to study more, Decision is yours.
Our online learning gives you the flexibility to study when and where you want, with rich online learning resources and study guides developed by our expert tutors to provide structure, keep you motivated, and strengthen your understanding of the subject.
If you want a high level of structured guidance and support but can't attend scheduled live classes, then online learning is the perfect study method. You study at your own pace and set your own flexible schedule. We are dedicated to offering extensive learning support to simplify your learning journey, so we provide the option to schedule online personal meetings with your tutor at your convenience.
Our simplified online learning facilitates you to achieve high career growth without stress and dilemmas.
What's included in our online learning?
We offer our learners limitless learning experience opportunities to develop knowledge and skills with our innovative blended learning approach. Our blended learning combines self-paced online learning with scheduled online live classes. With our blended learning, you can schedule online live classes for each module you study at your convenience. Join scheduled, interactive live lectures online, talk to tutors during the class for live feedback, and get guidance and support for your studies.
What's included in our blended learning?
We are 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. At the Support Desk area in the MyLearnDirect learning portal, you can raise queries, request tutor support, and ask for a call back whenever you need guidance and assistance.
We devised a structured support system and procedures to assist learners and streamline support processes efficiently.
Our extensive support includes:
We focus on providing a sophisticated, flexible learning experience. Our courses are designed to fit into your full-time work schedule.
You will have access to unlimited dedicated tutor support. You can also schedule personal tutor meetings.
