24 Hour Flash Deal **25-in-1 Environmental Consultant Diploma Mega Bundle** Environmental Consultant Diploma Enrolment Gifts **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter ** Take the initial steps toward a successful long-term career by studying the Environmental Consultant Diploma package online with Studyhub through our online learning platform. The Environmental Consultant Diploma bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass. This Environmental Consultant Diploma course provides complete 360-degree training on Environmental Consultant Diploma. You'll get not one, not two, not three, but twenty-five Environmental Consultant Diploma courses included in this course. Plus Studyhub's signature Forever Access is given as always, meaning these Environmental Consultant Diploma courses are yours for as long as you want them once you enrol in this course This Environmental Consultant Diploma Bundle consists the following career oriented courses: Course 01: Environmental Management Course 02: Environmental Health Course 03: Environmental Law Course 04: Sustainable Energy, Development and Environmental Impacts Course 05: Environmental Engineering Course 06: Asbestos Awareness Course 07: Renewable Energy Course 08: Structural Geology, Tectonics & Rock Mechanics Course 09: Wildlife Rescue and Rehabilitation Course 10: Agricultural Science Course 11: Forestry Course 12: Carbon Literacy Project Certifications Course 13: Renewable Energy Engineering Course Course 14: Floristry & Plant Care Training Course 15: Water Treatment Course 16: Diploma in Water Chemistry Course 17: Sustainable Energy Course 18: Town Planning Course 19: Biotechnology Course 20: Environmental Science and Climate Change Dynamics Course 21: Marine Biology Courses Online Course 22: Environmental Impact Assessment: Evaluating Sustainability Course 23: Ecology Course 24: Sustainable Living Course 25: Rewilding Training for Environmental Stewardship The Environmental Consultant Diploma course has been prepared by focusing largely on Environmental Consultant Diploma career readiness. 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This Environmental Consultant Diploma training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Environmental Consultant Diploma Requirements To participate in this Environmental Consultant Diploma course, all you need is - A smart device A secure internet connection And a keen interest in Environmental Consultant Diploma Career path You will be able to kickstart your Environmental Consultant Diploma career because this course includes various courses as a bonus. This Environmental Consultant Diploma is an excellent opportunity for you to learn multiple skills from the convenience of your own home and explore Environmental Consultant Diploma career opportunities. Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free
24 Hour Flash Deal **25-in-1 Egyptology (Art, Architecture, Trade & Language) Advanced Diploma Mega Bundle** Egyptology (Art, Architecture, Trade & Language) Advanced Diploma Enrolment Gifts **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter ** Take the initial steps toward a successful long-term career by studying the Egyptology (Art, Architecture, Trade & Language) Advanced Diploma package online with Studyhub through our online learning platform. The Egyptology (Art, Architecture, Trade & Language) Advanced Diploma bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass. This Egyptology (Art, Architecture, Trade & Language) Advanced Diploma course provides complete 360-degree training on Egyptology (Art, Architecture, Trade & Language) Advanced Diploma. 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Certificates CPD Accredited Certificate Digital certificate - Included CPD Accredited e-Certificate - Free CPD Accredited Hardcopy Certificate - Free Enrolment Letter - Free Student ID Card - Free
EA/PA Excellence Workshop Live from London on the 25th of April 2024. Featuring Keynote speaker Reggie Love, former Special Assistant to 44th President of the USA, Barrack Obama. Panel featuring Sophie Chapman, assistant to Steven Bartlett entrepreneur, author, host of the diary of a CEO and youngest ever dragon on BBC's Dragon's Den, Victoria Wratten, CEO of the Executive & Personal Assistants Association. The workshop contains, panel talk, keynote talk and facilitation over key topics from Kate Wood over the course of the day.
This course provides practical training in all areas of sustainable energy, including renewable energy sources, photovoltaic systems and sustainable energy technologies. You will learn about the impact of sustainable energy on the environment and will explore wind, solar, ocean and geothermal energy in detail. This course is ideal for those who are looking to fast track their career in the energy sector. It includes case studies and practical exercises that are designed for those who have little knowledge of sustainable technologies in this field. Learning Objective: Be able to identify the different types of non-renewable energy Demonstrate an understanding of sustainable energy technologies & systems Understand how wind, solar, ocean and geothermal energy works Learn about the potential applications of different renewable energy sources Broaden your understanding of the environmental impacts of renewable energy technologies Fast track your career with an endorsed certificate in Sustainable Energy Explore the idea of hydrogen fuel cells as a source of renewable power Develop your understanding of the future of energy systems Learn about photovoltaic systems and how solar energy is harnessed Who is This Course for? This endorsed training course in Sustainable Energy is ideal for those who are interested in working in the sustainable and renewable energy sector, as well as those who would like to gain a more in-depth understanding of sustainable energy sources. Our online courses are specially designed for distance learning, offering flexible virtual classroom modules that you can study at your own convenience. There are no specific entry requirements for the course, which can be studied part-time or full-time. Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the course. Good understanding of English language, numeracy and ICT are required to attend this course. Career Path This introductory to sustainable energy course is designed to equip you with the skills and practical knowledge to work in the following professions: Sustainable Energy Consultant Graduate Energy Specialist Energy and Utilities Analyst Energy Engineer Course Curriculum Module 1: History of Energy Consumption Module 1: History of Energy Consumption 00:35:00 Assessment Module 1 Module 01 Final Quiz Exam - Sustainable Energy 00:10:00 Module 2: Non-Renewable Energy Module 2: Non-Renewable Energy 00:30:00 Assessment Module 2 Module 02 Final Quiz Exam - Sustainable Energy 00:10:00 Module 3: Basics of Sustainable Energy Module 3: Basics of Sustainable Energy 00:30:00 Assessment Module 3 Module 03 Final Quiz Exam - Sustainable Energy 00:10:00 Module 4: Fuel Cell Module 4: Fuel Cell 00:45:00 Assessment Module 4 Module 04 Final Quiz Exam - Sustainable Energy 00:10:00 Module 5: Solar Energy Module 5: Solar Energy 00:50:00 Assessment Module 5 Module 05 Final Quiz Exam - Sustainable Energy 00:10:00 Module 6: Wind Energy Module 6: Wind Energy 01:20:00 Assessment Module 6 Module 06 Final Quiz Exam - Sustainable Energy 00:10:00 Model 7: Ocean Energy Module 7: Ocean Energy 00:30:00 Assessment Module 7 Module 07 Final Quiz Exam - Sustainable Energy 00:10:00 Module 8: Geothermal Energy Module 8: Geothermal Energy 00:35:00 Assessment Module 8 Module 08 Final Quiz Exam - Sustainable Energy 00:10:00 Module 9: Application of Renewable Energy Module 9: Application of Renewable Energy 00:15:00 Assessment Module 9 Module 09 Final Quiz Exam - Sustainable Energy 00:10:00 Module 10: Being Environment-Friendly Module 10: Being Environment-Friendly 00:25:00 Assessment Module 10 Module 10 Final Quiz Exam - Sustainable Energy 00:10:00 Order Your Certificate
24 Hour Flash Deal **25-in-1 Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) Mega Bundle** Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) Enrolment Gifts **FREE PDF Certificate**FREE PDF Transcript ** FREE Exam** FREE Student ID ** Lifetime Access **FREE Enrolment Letter ** Take the initial steps toward a successful long-term career by studying the Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) package online with Studyhub through our online learning platform. The Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) bundle can help you improve your CV, wow potential employers, and differentiate yourself from the mass. This Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) course provides complete 360-degree training on Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS). You'll get not one, not two, not three, but twenty-five Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) courses included in this course. Plus Studyhub's signature Forever Access is given as always, meaning these Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) courses are yours for as long as you want them once you enrol in this course This Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) Bundle consists the following career oriented courses: Course 01: Occupational Therapy Course 02: Play Therapy, Mental Health and Child Psychology Diploma Course 03: Mental Health Care - MCA & DOLS Course 04: Deprivation of Liberty Safeguards Training Course 05: Mental Health Awareness and Psychiatric Disorders Course 06: Dialectical Behaviour Therapy (DBT): Counselling, Physiotherapy & Treatment Course 07: Mental Health First Aid Certification Course 08: Psychological Wellbeing and Crisis Intervention Course 09: Neuroscience of Brain Disorders Course 10: Common Childhood Illnesses & Paediatric First Aid Level 2 Course 11: Infection Control Diploma Course 12: Cognitive Behavioural Therapy (CBT) Training Course 13: Duty of Candour in Healthcare: Ethical Practices and Legal Obligations Course 14: Care Planning and Record Keeping Course 15: Emotional Freedom Technique (EFT) Certification Course 16: Paediatric First Aid and Medical Emergency Training Course 17: Resuscitation and Life Support: Vital Skills and Techniques Course 18: Anaphylaxis and Basic Life Support (CSTF) Course 19: Pain Management Course 20: Wound Care and Tissue Viability Course 21: Human Anatomy, Physiology and Medical Terminology Diploma Course 22: Child Behaviour: Child Psychology, Mental Health Certification, Autism and Development Course 23: Early Childhood Mental Health: Strategies and Interventions Course 24: Crisis and Trauma Counselling in Early Childhood Course 25: Child and Adolescent Counselling The Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) course has been prepared by focusing largely on Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) career readiness. 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Every one of the topics is divided into Advanced Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) Elementary modules, allowing our students to grasp each lesson quickly. The Advanced Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) course is self-paced and can be taken from the comfort of your home, office, or on the go! With our Student ID card you will get discounts on things like music, food, travel and clothes etc. In this exclusive Advanced Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) bundle, you really hit the jackpot. 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This Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) training is suitable for - Students Recent graduates Job Seekers Individuals who are already employed in the relevant sectors and wish to enhance their knowledge and expertise in Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Requirements To participate in this Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) course, all you need is - A smart device A secure internet connection And a keen interest in Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) Career path You will be able to kickstart your Diploma in Occupational Therapy, Play Therapy & Mental Health (MCA & DOLS) career because this course includes various courses as a bonus. 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Key Highlights of the fast track Level 7 Diploma in Human Resource Management programme are: Program Duration: 6 Months (Regular mode also available) Program Credits: 120 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 Become eligible to gain direct entry into relevant Master's degree programme. LSBR Alumni Status No Cost EMI Option The objective of this fast track Level 7 Diploma in Human Resource Management qualification (accredited by OTHM, UK) is to provide learners with the skills and understanding in Human Resource Management (HRM) that align with good strategic decision making to maintain organisations' competitive advantage. You will acquire knowledge through an integrated approach of theory in Human Resource Management and practice using real-time activities. Successful completion of this fast track Level 7 Diploma in Human Resource Management qualification will develop learners' Strategic Human Resource Management and Leadership skills and their ability to focus on the requirements of implementing an organisation's strategy. This fast track Level 7 Diploma in Human Resource Management qualification enables learners to progress into or within employment and/or to work toward a relevant Master's programme with advanced standing. Who is this course for? Who is this Program For?Working Professionals, Level 6 / Year 3 of a three-year UK Bachelor's degree holders or learners who are looking for Career Progression and a formal Postgraduate qualification leading to award of degrees in future. Requirements Minimum EligibilityFor entry onto the fast track Level 7 Diploma in Human Resource Management qualification, learners must possess an honours degree in related subject or UK level 6 diploma or an equivalent overseas qualification. Learner must be 18 years or older at the beginning of the course. No formal qualification is required from mature learners (over 21 years) who have relevant management experience. Please speak to the Admission Counsellors for waiver information. Career path OpportunitiesUpon successful completion of the fast track level 7 Diploma in Human Resource Management programme, you will also become eligible to gain direct entry into relevant Master's and MBA degree programme.
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.
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