1138 Courses

Staying Human and Happy in a Virtual World How to stay human and happy in a virtual world...sounds catchy, right? Lets face it - while co-located, it is easier to connect with others. When dispersed, there needs to be a concerted effort towards team alignment and successful outcomes. A leader's responsibility is to provide structure, guidance, and a framework. However, studies show that the way you measure a healthy and happy work environment isn't the external governance guardrails, but it's around the motivation employees feel. If we can create environments that ensure our remote employees are engaged, confident, and motivated, we will increase our ability to be competitive and deliver successful outcomes to our customers. In our session, we will build a virtual house of team collaboration and discuss 5 foundational strategies, 6 core statistics, and 2 toolkits to help you and your teams stay human and happy in a virtual world. Key takeaways Learn how we each have an opportunity to influence talent retention in spite of physical location separation Understand the social and economic benefits of making an employee feel valued Practice activities that can be deployed to drive up retention & connectivity, while working remotely

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.

Unlock your potential in business writing with a focus on stock analysis articles. Learn to research, write, and present compelling business articles that not only inform but also command attention. This course is your step-by-step guide to mastering the art of persuasive and insightful business writing.

***Limited Time Offer*** Are you ready to dive into the exciting world of Property Management? As the real estate industry continues to boom, the demand for skilled Property Managers has skyrocketed. In fact, according to the Bureau of Labor Statistics, the employment of Property, Real Estate, and Community Association Managers is projected to grow 8% from 2020 to 2030, adding over 44,800 new jobs to the market. This comprehensive Property Management training bundle covers a wide array of topics, ensuring you gain a well-rounded understanding of the field. Dive into the fundamentals of Property Management, exploring property management principles, legal frameworks, and best practices. Expand your knowledge with courses on Property Development, Property Law and Legislation, Property & Estate Agency, Social Housing and Tenant Management, Wills and Probate Laws. Further, you'll delve into essential business concepts such as Capital Budgeting & Investment Decision Rules, Sales Psychology, Tax Accounting, and Customer Relationship Management, equipping you with the versatile skillset to excel in this dynamic industry. Courses Are Included in this Property Management Bundle: Course 01: Level 3 Diploma in Property Management (Property Manager) - QLS Endorsed Course 02: Property Development Diploma Course 05: Property Law and Legislation Course 03: Property & Estate Agent Course 04: Social Housing and Tenant Management Level 2 Course 06: Understanding Wills and Probate Laws - Level 2 Course 07: Construction Industry Scheme (CIS) Course 08: Capital Budgeting & Investment Decision Rules Course 09: Sales: Psychology of Customers Course 10: Level 3 Tax Accounting Course 11: Customer Relationship Management Learning Outcomes of Property Management Upon completion of the bundle, learners will: Understand the role and responsibilities of a property manager. Gain theoretical knowledge about UK Property laws and regulations. Learn about social housing management and property marketing skills. Understand residential property sales and surveying. Develop foundational knowledge about real estate operations. Understand the Construction Industry Scheme (CIS) and letting agent operations. Learn to write effective business proposals for property projects. Start your learning journey straightaway! Course Curriculum of Property Management 01 Introduction to Property Management 02 The Role and Responsibilities of a Property Manager 03 Listing Properties and Marketing 04 The Letting Process and Tenancy Agreement 05 The Property Management Process 06 Keeping Tenants Long Term 07 Regulations of Property Management 08 Changes in the UK Property Market: An Opportunity CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This bundle is ideal for: Students seeking mastery in this field Professionals seeking to enhance their skills Anyone who is passionate about this topic Career path Property Manager (£22,000 - £45,000) Real Estate Agent (£18,000 - £50,000) Letting Agent (£17,000 - £30,000) Residential Surveyor (£22,000 - £60,000) Property Marketer (£20,000 - £35,000) Social Housing Manager (£26,000 - £40,000)

If you’re looking to start a career in Python coding, but don’t know where to begin, this might be for you. This course is aimed at absolute beginners that have never done any coding before. Early on in the course, you’ll learn what coding is, what certain types of languages are used for, specifically Python, and the types of careers available through learning Python.

Overview Gainup-to-date HR skills with the HR, Payroll,Paye, Tax Professional Diploma course. This HR, Payroll,Paye, Tax Professional Diploma course will provide you with an in-depth understanding of human resource management fundamentals and the skills to manage payroll expertly. It is designed to assist you to grasp every concept, from the basics to the advanced aspects.Boost your career with HR skills and gain the knowledge to work for leading companies. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment on this HR, Payroll,Paye, Tax Professional Diploma. It is available to all students, of all academic backgrounds. Requirements Our HR, Payroll,Paye, Tax Professional Diploma is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G.There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 16 sections • 47 lectures • 12:12:00 total length •Human Resource Management: 01:00:00 •HR Planning, Recruitment and Selection: 01:00:00 •Induction, Training and Development: 00:45:00 •HR Department's Responsibilities: 00:45:00 •The UK Recruitment Legislations Guide: 00:20:00 •Organisational Culture: 00:45:00 •Motivation, Counseling, Resignations and Retirement: 01:00:00 •Performance Appraisal: 00:45:00 •Remuneration Policy: 00:15:00 •Records and Statistics: 00:30:00 •Industrial Relations: 00:15:00 •The UK Recruitment Industry Statistics: 00:25:00 •Introduction to Payroll Management: 00:10:00 •An Overview of Payroll: 00:17:00 •Running the payroll - Part 1: 00:14:00 •Running the payroll - Part 2: 00:18:00 •Manual payroll: 00:13:00 •Benefits in kind: 00:09:00 •Computerised systems: 00:11:00 •Total Photo scenario explained: 00:01:00 •Brightpay conclude: 00:03:00 •Find software per HMRC Brightpay: 00:03:00 •Add a new employee: 00:14:00 •Add 2 more employees: 00:10:00 •Payroll settings: 00:04:00 •Monthly schedule - Lana: 00:14:00 •Monthly schedule - James: 00:08:00 •Directors NI: 00:02:00 •Reports: 00:02:00 •Paying HMRC: 00:05:00 •Paying Pensions: 00:04:00 •RTI Submission: 00:02:00 •Coding Notices: 00:01:00 •Journal entries: 00:07:00 •Schedule: 00:03:00 •AEO: 00:06:00 •Payroll run for Jan & Feb 2018: 00:13:00 •Leavers - p45: 00:03:00 •End of Year p60: 00:02:00 •Installing Brightpay: 00:13:00 •PAYE TAX: 00:13:00 •NI: 00:11:00 •Pensions: 00:06:00 •Online calculators: 00:07:00 •Payslips: 00:03:00 •Journal entries: 00:07:00 •Conclusion and Next Steps: 00:08:00

Highlights of the Course Course Type: Online Learning Duration: 55 minutes Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about drug and alcohol awareness Understand the core competencies and principles of drug and alcohol awareness Explore the various areas of drug and alcohol awareness Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert health and social care worker Drug & Alcohol Awareness This drug and alcohol awareness course is accredited by the CPD UK. CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. This drug and alcohol awareness course is aimed at managers and staff in all industries who play a role in reducing drug, alcohol and substance misuse in the UK. The drug and alcohol awareness course starts with official statistics to illustrate the scale of drug and alcohol abuse in the UK. You'll learn in detail about commonly used drugs, including cannabis, cocaine, heroin, LSD, ecstasy and some new designer drugs. Turning to alcohol abuse, the course will show you how to introduce a 4-stage plan to deal with any problems - including how to write an effective Drug and Alcohol Policy. Beyond this the course will explore best business practice in terms of HR, legislation, spotting signs of drug misuse and the implementation of workplace solutions. The drug and alcohol awareness course also explains how the Advisory, Conciliation and Arbitration Service (ACAS) can help with effective alcohol and drugs policies and the development of related management skills. Finally, it looks at current drug treatments and the options for outside support available to individuals and organisations. Who is this Course for? This comprehensive Drug & Alcohol Awareness course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this drug and alcohol awareness can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This Drug & Alcohol Awareness course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This Drug & Alcohol Awareness course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This Drug & Alcohol Awareness course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Module 1: Statistics and Signs of Misuse Module 2: Illegal Drugs Part 1 Module 3: Illegal Drugs Part 2 Module 4: Alcohol Misuse Module 5: Company Best Practice Part 1 Module 6: Company Best Practice Part 2 Module 7: Company Best Practice Part 3 Module 8: Drug Treatment Services and Further Support Obtain Your Certificate Order Your Certificate of Achievement 00:00:00

Level 3 & 5 Endorsed Diploma | QLS Hard Copy Certificate Included | Plus 5 CPD Courses | Lifetime Access

10 QLS Endorsed Courses for Pentest Programmer | 10 Endorsed Certificates Included | Life Time Access

Our combined "Highway Code andAccidents, Incidents, and Breakdowns Training" module offers a comprehensive learning experience for drivers. Highway Code Training Content: Course introduction, objectives, and expectations. Introduction to the Highway Code and its relevance. Types of road users and training for various groups. Respecting and understanding the risks to different road user categories. Confirmation of knowledge quizzes covering all aspects of the Highway Code and traffic regulations. Accidents, Incidents, and Breakdowns Training Content: Recognizing risks and potential incidents, including breakdowns, collisions, and other scenarios. Duty of care, taking preventative measures, and handling incidents. Understanding health and safety regulations and related statistics. Prevention strategies and appropriate responses in case of an incident. Personal safety and actions to be taken during a vehicle collision. Steps to follow when facing a breakdown, including monitoring gauges and risk assessments. Ensuring the safety of other road users and cooperating with emergency services and recovery operators. Handling bridge strikes, including prevention and actions in case of an incident. Join us to enhance your knowledge of the Highway Code and road safety preparedness. Register today to ensure your drivers are well-versed in the rules of the road and equipped to handle unexpected challenges on their journeys. #HighwayCode #RoadSafety #AccidentHandling #Breakdowns #SafetyTraining