23279 Courses in Cardiff delivered Online

Couples therapy assessment calls Gottman method Insight gaining therapy Communication counselling Positive psychology couples therapy Couples therapy effective communication exercises Homework and couples therapy implementation tasks Attachment therapy Resolve serious conflicts Improve trust and honesty Address core issues Dating advice and relationship advice Couples therapy near me https://relationshipsmdd.com/product/m-d-d-couples-therapy-8-session-package/

The objective of the Diploma in Business Studies - Level 3 qualification (Accredited by OTHM) is to provide learners with an in depth understanding of the operations and structure of businesses. Successful completion of this qualification will equip learners with the underpinning knowledge and skills required to succeed in employment or further studies. Program Overview of Diploma in Business Studies Key Highlights Program Duration: 6 Months (Can be fast tracked) Program Credits: 60 Designed for working Professionals Course Delivery: Online No Written Exam. The Assessment is done via Submission of Assignment Tutor Assist available Dedicated Student Success Manager Timely Doubt Resolution Regular Networking Events with Industry Professionals Direct entry into Year 1 of a three-year UK Bachelor's degree LSBR Alumni Status No Cost EMI Option Top Skills You Will Learn Understanding of operations and structure of businesses. Underpinning knowledge and skills required to succeed in employment or further studies. Who is this course for? Working Professionals, O-Level holders, Sales & Marketing Professionals

The objective of the OTHM Level 3 Certificate in Business Studies qualification is to provide learners with an in depth understanding of the operations and structure of businesses. Successful completion of this qualification will equip learners with some of the underpinning knowledge and skills required to succeed in employment or further studies. Program Overview Key Highlights Program Duration: 3 Months Program Credits: 30 Designed for working Professionals Format: Online No Written Exam. The Assessment is done via Submission of Assignment Tutor Assist available Dedicated Student Success Manager Timely Doubt Resolution Regular Networking Events with Industry Professionals Direct entry into Year 1 of a three-year UK Bachelor's degree LSBR Alumni Status No Cost EMI Option Top Skills You Will Learn Understanding of operations and structure of businesses. Underpinning knowledge and skills required to succeed in employment or further studies. Who is this course for? Working Professionals, O-Level holders, Sales & Marketing Professionals

ITIL® 4 Leader: Digital and IT Strategy: Virtual In-House Training The ITIL® 4 Leader: Digital and IT Strategy (DITS) is one of the two modules in the ITIL® 4 Strategic Leader (SL) certification scheme. The other module in the SL designation is the ITIL® 4 Strategist: Direct, Plan & Improve. Accredited training for the ITIL® 4 Strategic Leader modules is mandatory to enable full understanding of the core material. The ITIL ® 4 Digital and IT Strategy certification focuses on enabling business success through the creation of digital and IT strategies. The IT and Digital Strategy certification adds a new perspective to the ITIL suite and elevates the discussion around ITIL concepts to a strategic level among business leaders and aspiring leaders. The ITIL® 4 Digital and IT Strategy course is based on the ITIL® 4 Digital and IT Strategy exam specification from AXELOS. With the help of ITIL® 4 concepts and terminology, exercises, and examples included in the course, you will acquire relevant knowledge to pass the certification exam. The core learning material in the course is supported by interactive case study, discussions and activities. What You Will Learn The ITIL ® 4 Digital and IT Strategy course covers the content in relation to the following learning outcomes of the exam specification for ITIL ® 4 Digital and IT Strategy: Demonstrate the use of the ITIL guiding principles in Digital and IT Strategy decisions and activities Understand how to leverage digital strategy to react to digital disruption Understand the relationship between the concepts of Digital and IT Strategy, the service value system and the service value chain, and explain how to utilize them to create value Understand how an organization uses Digital and IT Strategy to remain viable in environments disrupted by digital technology Understand strategic approaches made possible by digital and information technology to achieve customer/market relevance and operational excellence Understand the risks and opportunities of Digital and IT Strategy Understand the steps and techniques involved in defining and advocating for a Digital and IT Strategy Understand how to implement a Digital and IT Strategy Key Concepts of Digital and IT Strategy Digital, Information, and Communication Technology Digital Transformation Services, Products, and Competitive Advantage Tiers of Strategy Business Models Operating Models Strategy and the Service Value System Opportunity and Demand Value Governance ITIL® Guiding Principles Continual Improvement ITIL® Practices What is Vision? Disruptions Vision Digital Disruptions Balanced Strategic Focus Positioning Tools for Digital Organizations Assignment 1: Digital Disruption and Digital Positioning Where Are We Now? Environmental Analysis Opportunity Analysis Digital Readiness Assessment How Do We Get There (Strategic Planning) Strategy Planning Financial Aspects of Digital and IT Strategy Business Models for Strategy Planning Portfolio Optimization How Do We Get There (Strategic Approaches) Strategic Approaches for Digital Organizations Strategic Approaches for Operational Excellence Strategic Approaches to Evolution Strategic Approaches to Social Responsibility and Sustainability Assignment 2: Strategic Approaches for Digital Organizations Take Action (Managing Strategic Initiatives) How Strategies are Implemented Coordinating Strategy and Strategic Initiatives Leading Digital Transformation Digital Leadership Assignment 3: Strategy Planning and Communication Did We Get There? (Measuring Strategy) Key Facts About Measurement Measuring a Strategy Instrumenting Strategy How Do We Keep the Momentum Going Long-Term Momentum: Ensuring Organizational Viability Short-Term Momentum: Parallel Operation Assignment: Digital Strategy in VUCA Environment Managing Innovation and Emerging Technologies Managing Innovation Formal Approach to Innovation Management Culture that Supports Innovation Approaches to Innovation Evaluating and Adopting Emerging Technology Managing Strategic Risk Risk Management Risk Identification Risk Posture Risk Treatment

This module provides a guide to signal detection and management for approved products. The subject is presented as a process comprising four stages: signal detection, signal validation, signal analysis and prioritisation, and risk assessment and minimisation.

A comprehensive two days, delivered using a variety of teaching styles, by professionals who manage medical emergencies on a day-to-day basis. A number of the more common presenting conditions are covered providing a structured approach to the pathophysiology, initial assessment and management of the acutely ill medical patient.

Personal Tax Return and Self Assessment training Course Most self-employed people and directors of companies have to do submit a Tax Return every year. If you are a self-employed person you may learn how to do tax return yourself. As a result, you can save money by not having to pay an external agent. Don't forget You can also save more money as you will know more about how to apply for a tax rebate. According to statistics, more than 60% of taxpayers not sure how to do tax return correctly and lose money for not knowing how to apply for a tax rebate correctly. If you want to offer tax services to the general public, then skills in this sector can dramatically improve your job prospect or business prospect. How to do a tax return Firstly, you need to be registered with HMRC to process your tax return. You should get a UTR (Unique Tax Reference) no, which is your personal identification no for tax purpose. Once you have details for all incomes and expenditure, you can submit them electronically to HMRC. The deadline for submitting a personal tax return is 31 January for the previous tax year. Apply for a Tax Rebate It is possible that you could be eligible for a tax rebate. The most possible scenarios are When you pay more tax than required Submitting an incorrect tax return Claiming special Tax relief There could be many more reasons why should you get a tax refund. It is vital to know the scenarios under which you should apply for a tax rebate. Identify the type(s) of returns that may be completed Understand the duties and responsibilities of a bookkeeper / tax agent when completing self-assessment tax returns Calculating the taxes on profits for Self Employed & on income for Employed individuals Understanding differences between Drawings & Dividends Introduction to UTR and NI Classes Understanding Tax Return submission procedures to HMRC (using 2 individual Scenarios) Analysing Class 2 & Class 4 NIC Analysing Personal Allowance Analysing Income from Self Employments Employment benefits Analysis Analysis of Car & Fuel benefits Analysis on savings and investment income and tax implications on them. Introduction to Capital Gains Tax analysis Introduction to Inheritance Tax Analysis Understanding the procedure for payment and administration of both tax and National Insurance Contributions

If you got a call from a TV producer asking you to appear on Newsnight, would you say ‘yes’? And if you did, could you make your argument in a way that captured the attention of the audience without being interrupted? Our media training courses are aimed at senior spokespeople and experts who give interviews on TV, radio or in print. We equip them with the skills and confidence to take control and give engaging, memorable and effective performances in which they deliver their key messages, no matter what the circumstances. Highly interactive and practical, each course includes a series of realistic print, radio and television exercises with experienced journalists. We provide immediate feedback following each interview, including techniques for improvement, advice about potential answers and the framing of key messages. While all our media training courses are bespoke, on a typical course we will cover: how the media operates how to prepare for interviews the differences between TV, radio and print interviews how to conduct different types of interview, such as pro-active, reactive, expert commentator and hostile (crisis communications) developing key messages which convey your views persuasively how to take control of an interview, stick to your own agenda and deliver key messages successfully use of language, body language, dress and delivery After the course, each delegate receives the Rough House Media Toolkit, including written feedback, recorded copies of their interview exercises, the Rough House Media Guide to Interviews and further supporting materials. We also provide a confidential assessment to the PR team of each delegate’s suitability for different types of interview. Venue We deliver courses in the most appropriate format for your circumstances – whether face to face or online. Face to face courses are portable: they can be held in purpose-built studios, at your own offices or at an external venue. In the latter two cases, we create a mock studio for the practical exercises. Online courses give you flexibility and enable you to offer training to delegates from all over the world. We have run virtual courses for people from the Far East, South Asia, North America and Europe, as well as the UK.

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.

Getting Started OTHM Level 7 Diploma in Logistics and Supply Chain Management aims to provide a broader understanding of logistics and supply chain management. It is designed for logistics and supply chain professionals in the early stages of their careers looking to enhance their knowledge. Upon successfully completing this program, the learners will be equipped with skills needed to further their careers as logistics and supply chain professionals and to work toward a relevant Master's programme with advanced standing. Key Benefits All the important management theories and models are covered in this course. As a result, the students will gain a better understanding of the various management techniques that are applicable in the workplace. Will be helpful to the students to develop their problem-solving skills through the practical application of the various management models and theories. A nationally - recognised qualification, the credits earned at this course can be transferred to other courses, if the students want to pursue MBA or any other Masters. On successful completion of the course the students will be able to demonstrate their proficiency in the various management practices which will improve their chances of making a successful career progression. About Awarding Body OTHM is an established and recognised Awarding Organisation (Certification Body) launched in 2003. OTHM has already made a mark in the UK and global online education scenario by creating and maintaining a user-friendly and skill based learning environment. OTHM has both local and international recognition which aids OTHM graduates to enhance their employability skills as well as allowing them to join degree and/or Master top-up programmes. OTHM qualifications has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Business Studies, Leadership, Tourism and Hospitality Management, Health and Social Care, Information Technology, Accounting and Finance, Logistics and Supply Chain Management. What is included? Time-constrained scenario-based assignments No examinations Entry Requirements For entry onto the OTHM Level 7 Diploma in Logistics and Supply Chain Management qualification, learners must possess: An honours degree in related subject or UK level 6 diploma or an equivalent overseas qualification Mature learners (over 21 years) with management experience International students whose first language is not in English, they will need to have score of 5.5 or above in IELTS (International English Language Testing System) Progression   On successful completion of the OTHM Level 7 Diploma in Logistics and Supply Chain Management, a number of progression opportunities become available: Master's top-up programmes at many universities in the UK and overseas with advanced standing or Directly into employment in an associated profession.   Why gain a OTHM Qualification?   Quality, Standards and Recognitions- OTHM qualifications are approved and regulated by Ofqual (Office of the Qualifications and Examinations Regulation); hence, the learners can be very confident about the quality of the qualifications as well. Career Development to increase credibility with employers- All OTHM qualifications are developed to equip learners with the skills and knowledge every employer seeks. The learners pursuing an OTHM qualification will obtain an opportunity to enhance learning and grow key competencies to tackle situations and work projects more effectively, giving learners the potential to get promotions within the workplace. Alternatively, it allows them to progress onto an MBA top-up/Bachelor's degree / Master's degree programme around the World. Flexible study options- All OTHM qualifications have a credit value, which tells you how many credits are awarded when a unit is completed. The credit value will indicate how long it will normally take you to prepare for a unit or qualification. Three different types of qualification are: The award is achieved with 1 - 12 credits The certificate is earned with 13 - 36 credits The diploma is completed with at least 37 credits The OTHM Level 7 Diploma in Logistics and Supply Chain Management consists of 6 mandatory units for a combined total of 120 credits, 1200 hours Total Qualification Time (TQT) and 600 Guided Learning Hours (GLH) for the completed qualification. 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- Logistics Management Reference No : J/618/1227 Credit : 20 || TQT : 200 The unit focuses on the valuing adding role of logistics in supply networks. It aims to impart learners with a thorough understanding of key theoretical and operational aspects of managing specifically transportation, storage/warehousing and packaging logistics. The related considerations for business competitiveness is emphasised as is the interdependency between operational, technological and regulatory aspects. UNIT2- Supply Chain Planning, Modelling and Analytics Reference No : R/618/1229 Credit : 20 || TQT : 200 The unit aims to provide learners with in-depth knowledge about planning processes across all key aspects of supply chain management. The relevance of each of the planning processes, the associated information requirements and modelling and analytic techniques are covered. UNIT3- Procurement and Supply Management Reference No : L/618/1231 Credit : 20 || TQT : 200 The unit seeks to provide learners with a thorough understanding of procurement and supply management from a strategic, technological, process and relationship perspective. The goal is to provide insights on the role of procurement within supply chain management, the negotiation and contractual issues encountered with suppliers , effective supplier relationship management, the tools and techniques to assess sourcing options and technological enablers in procurement. UNIT4- Supply Chain and Operations Strategy Reference No : Y/618/1233 Credit : 20 || TQT : 200 The aim of this unit is to develop learners' understanding of supply chain and operations management, including its scope, impact and importance as well as the strategic decisions that need to be made in today's world of global markets and global supply, taking into account the major competitive drivers. The unit discusses approaches and supply chain and operations management practices in a range of contexts. UNIT5- Sustainable Operations Management Reference No : H/618/1235 Credit : 20 || TQT : 200 The aim of this unit is to develop learners understanding including key elements of sustainability and their importance to businesses, knowledge and skills of sustainable operations management, the different practices across the supply chain that can be worked upon to improve sustainability as well as the performance measures and the business impact of sustainability, the business drivers and barriers affecting the move towards sustainability. A variety of different sectors are explored. UNIT6- Business Research Methods Reference No : T/508/0626 Credit : 20 || TQT : 200 The aim of this unit is to develop learners understanding of research principles including the formulation of literature reviews, statistical analysing using SPSS, research proposals, referencing, data collection using surveys and interviews, questionnaire design, qualitative data and methods for drawing conclusions from the analysed data. 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.