1871 Courses

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

What is this workshop about? One of the key principles of Cognitive Behavioural Therapy (CBT) is that it is crucial to help clients see the impact of thinking on emotions. Biased thinking patterns can lead to low mood, high anxiety, low self esteem, anger or a range of other psychological challenges. These cognitive patterns are also crucial in maintaining psychological disorders such as depression or GAD. Key to many CBT interventions is to help the client challenge their own thought processes and break the vicious circle of biased thinking and negative affect. This workshop will look in detail at the practical techniques which can help clients overcome these patterns of thinking which drive emotional reactions and behavioural avoidance or overreaction. Key skills to help clients replace dysfunctional thought structures with more effective, balanced perspectives will be at the heart of the workshop. The workshop will include live demonstrations by Prof McGhee of some of the most crucial techniques. There will also be a case study for participants to review and discuss. Ticket price includes all slides and handouts. Key Topics (indicative) KEY CONCEPTS The role of beliefs in maintaining psychological distress Negative Automatic Thoughts Unhelpful Thinking Styles Unhelpful Rules Unhelpful Assumptions Core Beliefs KEY SKILLS AND TECHNIQUES Challenging Thought Structures Common Errors to avoid Behavioural Experiments in Cognitive Restructuring Mindfulness and Cognitive Restructuring Imagery and Cognitive Restructuring Metaphor and Cognitive Restructuring SUMMARY and NEXT STEPS What have previous delegates said about similar workshops? "Excellent overview. Great Case Studies" "Very Informative"Learned a lot of new techniques - thank you! Excellent, I’ve learnt a great deal today .... thank you! This was very clear and practical l. The techniques simple to understand. Excellent session Interesting Patrick - helps me to get my thoughts in order. Enjoy some of the links and will find overall very useful" "Informative and educational""Thought provoking""grounded in research""good resources provided" "Very interesting Good knowledge and excellent research" Who is leading this webinar? Professor Patrick McGhee is a CBT therapist, psychologist and UK National Teaching Fellow. Educated at the universities of Glasgow and Oxford, he has completed CPD programmes at Harvard Business School and Ashridge. In 2017 he was a Visiting Fellow/Scholar at the universities of Cornell, Yale and MIT in the USA. He has taught, researched or practised in psychology and therapy for 30 years. His first post was a Research Fellow in Psychiatry and Psychology at St George's Hospital Medical School, University of London. He is the author of Thinking Psychologically (Palgrave) and co-editor of Accounting for Relationships (Methuen). He is an occasional columnist for the Guardian, the BBC and the Times Higher. He currently works in private practice in Greater Manchester. He has full accreditation from the British Association for Behavioural and Cognitive Psychotherapies. Image Credit Dana Tentis

Thinking about a job as a Digital Product Manager? The BCS Practitioner Certificate in Digital Product Management encourages individuals in both technical and non-technical product-related roles to develop the practical behaviours required to succeed in leading a product project or team.

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

This Digital Functional Skills Level 1 Course will set you up with the relevant digital skills and knowledge and provide you with a competitive advantage in your career, making you stand out from all other applicants and employees. Course Highlights Course Type: Self-Paced Online Learning Accreditation: NCFE Qualification: Nationally Recognised Qualification Study Materials: High-Quality E-Learning Study Materials Assessment: Externally Graded and Verified | Center-Based Online or Online Remote Exam Guided Learning: 55 hours Access: 1 Year Access Certificate: Certificate upon completion of the official exam (hard copy) Tutor Support: Paid Tutor Support Customer Support: 24/7 live chat available Digital Functional Skills Level 1 - Online Course This Digital Functional Skills Level 1 Course is governed by Ofqual, and accredited by NCFE, making it a nationally recognised credential that will improve your CV while helping you stand out from the rest of the applicants.  Subject content of this course is based on the National Standards for Digital Functional Skills to increase comparability across awarding organisations. This course will increase your confidence and fluency in using digital tools and help you develop a positive attitude towards them. The course will introduce you to new areas of life and work that you might encounter in the future, providing you with the knowledge and skills to complete tasks and activities. Upon successful completion of this course, you will be equipped with the necessary digital skills to function independently, effectively, and with confidence in everyday life, professional, and academic settings. EXAM Booking & Results Details You can decide the exam date and place according to your convenience. Awarding Body On Screen Exam in Centre Remote Online Exam – From Home Results NCFE Book within 24 Hours Book within 2 working days Get results in only 7 days *Offline examinations will be held at our Swindon and London centres. Please contact us for more information. The new assessment and result dates by NCFE is: (Only applicable if you are attending the exam in between the following assessment date). Delivery mode: On-screen and RI Assessment date to and from: 23/09/2024 – 1/11/2024 Results release: 8/11/2024 (Note that this only applies to the mentioned exam type and if you book the exam during the dates mentioned above. Also, this will not affect the schedule of the other exam types and results.) How This Course will work for you? Initial Assessment: Determines levels Diagnostic Assessment: Identifies skill gaps and produces an individual learning plan Learning Resources: Develop underpinning knowledge and fill skill gaps identified Progress Check: Assesses progress at the end of the module You will get useful resources that are designed to improve your essential skills, knowledge and understanding of the digital knowledge required to pass the assessments.  Our online learning portal is fully compatible with desktop, tablet and mobile devices and can be accessed from anywhere. Aims & Outcomes This course will enable you to: Increase your confidence and fluency in the use of digital Gain knowledge and skills, and develop a positive attitude towards the use of digital skills; Demonstrate knowledge and skills by applying these to complete tasks and activities; Introduce you to areas of life and work which may be new or unfamiliar, and tasks and activities that they may encounter in future; Develop an appreciation of the importance of digital skills in the workplace and in life generally; Provide a basis for further study, work and life. Why is this course right for you? This course can be taken by: Anyone willing to enhance their practical digital functional skills Anyone looking to meet the entry requirement of your desired university Anyone looking to secure an apprenticeship Anyone looking to improve their job outlook with an added expertise Entry Requirements Students or professionals of any age group hailing from any academic background can take this Digital Functional Skills Level 1 Course to acquire practical skills in ICT; no prior knowledge, skills or qualifications are required to enrol.  About Official Exam, Assessment Students are required to undergo an initial assessment to determine the level and a diagnostic assessment to identify skill gaps and produce an individual learning plan. These interactive assessment sessions measure the knowledge you are absorbing and evaluate your potential to demonstrate these digital skills practically. You can also keep track of your score and progress at the end of the module. Towards the end of the Digital Functional Skills Level 1 Course, you will be required to undergo an onscreen/online exam that is externally set and graded. You can take the online exam at the designated exam center or remotely. Some assessment components for the skills and knowledge to be evaluated under the Content Document must be conducted online and on screens utilising digital devices. The assessments will be pass/fail in line with the other Functional Skills qualifications. Progression Opportunities in this Acquiring certified NCFE Digital Functional Skills qualifications at Level 1 will open your doors to the following career path:  BTEC Level 2 or 3 Qualifications for IT Users (ITQ) Level 2 Qualifications in Digital Applications for IT Users DIDA You can apply to your desired university You can access a wide range of career opportunities Course Curriculum 1. Using Devices and Handling Information • Device refers to examples such as desktop, laptop, mobile devices, and smart devices. An appropriate file naming convention refers to naming files in a way that describes or indicates the content or the use of the file, or includes the date and/or time information. • Limitations on file sizes when using some services refers to email attachments and file size upload limits. • Online resources refers to examples such as online tutorials, FAQs or help facilities. 2. Creating and Editing • Using appropriate layout conventions refers to adopting common conventions, such as text, tables, images and charts, for specific purposes, such as a formal report for managers, an advertisement for consumers or a presentation for colleagues. • An appropriate tool for editing refers to a desktop application or an application on a touchscreen device. • Simple formulae refers to up to two mathematical operators. Sorting numeric data refers to one criterion. Filtering data refers to one criterion. • An appropriate type of chart refers to bar/column charts, pie charts and line graphs. 3. Communicating • Using email or online messages for a range of contexts and audiences refers to common work or real-life scenarios, such as to colleagues at work, the general public, or users of a social media platform. 4. Transacting • Online services refers to examples such as shopping, banking, utilities, government services or media services. • Uploading documents or images refers to locating a file and understanding that file sizes may need to be reduced before submitting. 5. Being safe and responsible online • In understanding key rights under data protection laws, it is not necessary to understand issues of data protection compliance relating to organisations. • Health risks resulting from using devices and the internet refers to physical and/or psychological. Minimising these refers to examples such as taking regular breaks, using a wrist rest with a mouse, limiting screen time, avoiding screen time close to bedtime or reporting cyberbullying. Recognised Accreditation This Course is Accredited by NCFE and Regulated by OFQUAL This Course is accredited by NCFE and regulated by Ofqual which is a nationally recognised qualification that will add value to your CV. It is an approved subject by Department for Education (DfE) that provides a foundation for progression to employment and further technical education. Certificate of Achievement Upon successful passing of the official exam, you will be awarded an Ofqual regulated nationally recognised NCFE Digital Functional Skills qualification at Level 1.  FAQs When will I be able to access the course? You will be able to access the course as soon as you enroll. The course materials and resources will be available to you online 24/7, allowing you to study at your own pace and convenience. Are there any prerequisites or eligibility criteria for taking the course? There are no prerequisites or eligibility criteria for taking this course. This certification is open to anyone who wants to enhance their digital skills and knowledge. When will I be able to access the course? You will be able to access the course as soon as you enroll. The course materials and resources will be available to you online 24/7, allowing you to study at your own pace and convenience. Is there any age limit for enrollment in this course? There is no age limit for enrollment in this course. Learners of all ages are welcome to join and benefit from the course materials and resources provided. What is the difference between NCFE and Edexcel? NCFE and Edexcel are both awarding bodies that provide qualifications, but there are some differences between them. NCFE is a national awarding organization in the UK, while Edexcel is a subsidiary of Pearson, a multinational education company. Additionally, NCFE focuses on vocational qualifications and skills-based learning, while Edexcel offers a wider range of academic and vocational qualifications. Can I access this course material offline, or do I need a continuous internet connection? To access the course material, you need internet access, and you won't be able to access it offline. If I encounter any technical issues, what kind of support is available? We have a very supportive and friendly customer support team, available for you to ask for any help or assistance with any technical issues you may encounter. They can be reached through email or phone, and will promptly address any concerns you have to ensure a smooth learning experience. Do I need to have any special software to access this course? No, you do not need any special software to access this course. All you need is a device with internet access and a web browser. The course materials are accessible online, making it convenient for you to learn from anywhere at any time. Do I need to visit the exam center for the exam, or can I give it from home? You can take the online exam at the designated exam center or remotely. What is the difference between DFSQ and Essential Digital Skills Qualifications (EDSQ)? The DFSQ qualification focuses specifically on digital skills for work, while the EDSQ qualification covers only the essential digital skills for everyday life. The Guided learning hours for DFSQ are 55 hours, and those for EDSQ are 50 hours. What Will I Learn in the Digital Functional Skills Level 1 course? In the Digital Functional Skills Level 1 course, you will gain a comprehensive understanding of using digital devices, navigating online platforms, and conducting tasks on the internet. Additionally, you will develop knowledge and understanding of online safety and security measures to protect personal information.

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills 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. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods 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. Resources and Support 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. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise 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 receive 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 to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.