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Care and Support for Vulnerable Children Are you interested in learning Care and Support for Vulnerable Children? This Care and Support for Vulnerable Children course will ensure that you stand out from the crowd. The goal of this Care and Support for Vulnerable Children course is to provide students a thorough understanding of working closely with youngsters. You will learn how to look after and support vulnerable children in this course on Care and Support for Vulnerable Children. You'll learn how to treat and aid unresponsive victims in this Care and Support for Vulnerable Children course as well. This course on Care and Support for Vulnerable Children is divided into a number of short, in-depth courses that will give you comprehensive information. Enrol You'll stand out from the crowd with our Care and Support for Vulnerable Children course. Learning Outcomes After completing this Care and Support for Vulnerable Children course, you will be able to: Care and Support for Vulnerable Children will help you to Know how to recognise vulnerable children. Understanding the Importance of Awareness in Education. You will Know the Difference Between Vulnerability and Risk Care and Support for Vulnerable Children. Care and Support for Vulnerable Children will help you to Learn about Child Crisis. Learn about Identifying the Organizations Providing Support. Care and Support for Vulnerable Children will help you to Know about the History of Child Protection in the UK. Special Offers of this Care and Support for Vulnerable Children Course This Care and Support for Vulnerable Children Course includes a FREE PDF Certificate Lifetime access to this Care and Support for Vulnerable Children Course Instant access to this Care and Support for Vulnerable Children Course Get FREE Tutor Support to this Care and Support for Vulnerable Children Course Care and Support for Vulnerable Children The Care and Support for Vulnerable Children course offers a comprehensive guide for those dedicated to working with at-risk youngsters. Through this Care and Support for Vulnerable Children training, you will develop the skills to provide essential care and emotional support to vulnerable children, ensuring their well-being. Additionally, you will learn vital techniques to assist unresponsive victims, making this Care and Support for Vulnerable Children course essential for anyone in the field. With easily digestible modules, the Care and Support for Vulnerable Children course equips you with the knowledge and expertise needed to truly make a difference in children's lives. Who is this course for? Care and Support for Vulnerable Children Our Care and Support for Vulnerable Children course is open to everyone. Requirements Care and Support for Vulnerable Children To enrol in this Care and Support for Vulnerable Children Course, students must fulfil the following requirements. To join in our Care and Support for Vulnerable Children Course, you must have a strong command of the English language. To successfully complete our Care and Support for Vulnerable Children Course, you must be vivacious and self driven. To complete our Care and Support for Vulnerable Children Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Care and Support for Vulnerable Children Course. Career path Care and Support for Vulnerable Children Our Care and Support for Vulnerable Children course is designed to assist you in getting the job of your dreams.

Mental Health First Aid (MHFA) England Training with Mindmaps Wellbeing Enhance workplace wellbeing and mental health awareness with MHFA England-certified training by Mindmaps Wellbeing. Our expert-led courses, delivered by Registered Mental Health Nurses and Healthcare Educators, equip you with the skills to recognize, support, and respond to mental health challenges. Whether online or in-person, our training ensures flexible learning options without compromising quality. Join us to gain certification as a Mental Health First Aider and access exclusive benefits like ongoing peer support, expert forums, and resources for self-care. Book now with Mindmaps Wellbeing and take the first step toward a healthier, more supportive environment for all.

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.

The IWFM Level 3 qualifications in workplace and facilities management are for you if you are a first-line manager or supervisor in workplace and facilities management or if you are new to the industry. They are designed to develop an understanding and knowledge of facilities management matters.On successful completion of these qualifications, recognition by employers enables learners to progress into or within employment and/or continue their study in the vocational area.

Diploma in Project and Quality Management - Level 7 is a 120 credits qualification. Project and quality management can be used in a variety of industries to bring projects in on time, on budget and to the right quality. Project management elements of this Diploma in Project and Quality Management - Level 7 course will focus on management techniques and applications to help you plan and implement activities to complete projects to your customers expectations. Quality management elements of the course will help you make sure that the outcome of the project is fit for your customer's purposes. Program Overview: Diploma in Project and Quality Management - Level 7 Key Highlights of Diploma in Project and Quality Management - Level 7 qualification are: Program Duration: 9 Months (Fast Track Mode 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 Masters Degree programme. Alumni Status No Cost EMI Option Key facts about Level 7 Diploma in Project and Quality Management 100% Online: Study online with the UK's leading online course provider. Global programme: Study anytime, anywhere using your laptop, phone or a tablet. Study material: Comprehensive study material and e-library support available at no additional cost. Payment plans: Interest free monthly, quarterly and half yearly payment plans available for all courses. Why choose LSBR ? Transform your career: Enrol today and make a life changing decision, get necessary knowledge to transform your career. Move up in your career: With our fully accredited course, you can move up to the next level in your organisation with ease. Upgrade your skills: Add value to your current educational profile and achieve skill sets to compete in your job role. Cost effective: Typically a British qualification starts from GBP £3000 per annum, but with LSBR, you enjoy savings of up to 60% on your educational investment. Assessments: Assessment is done through written assignments and/ or dissertation project. Support: We offer live tutor support via online chat and email for all qualifications delivered by us. Career ProgressionLearners completing the Diploma in Project and Quality Management - Level 7 can progress to: A University partner to complete a dissertation to then receive a full master's degree, or Level 8 Diploma qualification, or Directly into employment in an associated profession University ExemptionsLearners can progress to a number of universities to complete a Master's Degree after completing their Diploma in Project and Quality Management - Level 7. This generally requires completion of a Dissertation only. The pathways are an indication of a learner's progress towards a university degree and are based on the university's review of Eduqual's learning programmes and outcomes. As our EduQual accredited qualifications are approved and regulated by Ofqual (Office of the Qualifications and Examinations Regulation)and Scottish Credit and Qualifications Framework (SCQF), learners are also eligible to progress to a Top-Up Degree, Master's programme, or MBA at many universities in UK and Overseas with advanced standing. Our qualifications are credit-rated for the Scottish Credit and Qualifications Framework (SCQF), a globally-recognised national qualifications framework aligned to other recognised frameworks such as the European Qualifications Framework (EQF) and the Ofqual Regulated Qualifications Framework (RQF).

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This training gives an opportunity to focus on how to embed effective approaches to meeting emotional needs in schools. We explore a range of ways into meeting emotional needs of pupils across a school. We focus on including pupils with extreme emotional needs. Course Category Meeting emotional needs Description This training gives an opportunity to focus on how to embed relevant ideas and materials in schools. We explore how to make these materials really come to life as we explore a range of ways into meeting emotional needs of pupils across a school. We focus on including pupils with extreme emotional needs. There are lots of opportunities for personal and professional reflection on engagement with challenging pupils as we provide processes to support reflection, visioning and problem solving. Testimonials ‘Thank you so much for the work you did with us yesterday – I have since been in 2 schools today and have spoken to an number of other colleagues who were present – all were totally overwhelmed by the session – they loved it.”NOTTINGHAM SEAL COORDINATOR “I was totally blown away, when I realised how passionate people were about SEAL” “So nice to reflect and realise what a long way we have come” “That was so powerful and motivational”.’ Learning Objectives Shared vision of a school that is truly meeting all social and emotional needs Access to a wider range of practical strategies to impact on meeting emotional and behaviour problems Deeper understanding of how to embed positive Mental Health approaches in a school Opportunity to reflect on professional attitudes and behaviour towards children with emotional challenge Who Is It For? All practitioners who are leading on Mental Health work in schools or on behalf of a Local Authority Full range of agencies committed to meeting social and emotional needs in schools Course Content The training explores the questions: What would a school look like when Mental Health was truly part of everything that was happening, a shared vision? How can we truly embed Mental Health approaches and materials in our school? What can we do to meet complex and challenging emotional needs in schools? Can we learn a process to understand at a deeper level highly complex social and emotional needs? This training will cover: Bringing positive Mental Health approaches to life in schools: creating a shared vision and a set of grounded goals together Circle of Adults process for self-reflection and understanding emotional needs of high profile pupils. We will model and teach how this process links in and strengthens PSHE work in schools. If you liked this try: FRESH APPROACHES TO BEHAVIOUR AND RELATIONSHIPS or: RESTORATIVE INTERVENTIONS

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So you appreciated a Keys to Inclusion day? Wondering what next? The Next Set follows on from our lead workshop/training day and is both values driven and a practical guide to successful strategies for further developing inclusive practice in educational settings for children and young people of all ages. Course Category Inclusion Description So you appreciated a Keys to Inclusion day? Wondering what next? The Next Set follows on from our lead workshop/training day and is both values driven and a practical guide to successful strategies for further developing inclusive practice in educational settings for children and young people of all ages. On this day we explore processes and ideas ranging from the individual practitioner’s imagination through to the creating of a community gathering to strengthen inclusion of disabled and disempowered adults and children. This too is a ‘hearts and minds’ day in which you can expect participants to both laugh and cry in equal measure! The day gives those present lots of opportunities to reflect on their attitudes and practice in relation to the inclusion of pupils who are different and most challenging. Testimonials I have learned such a lot. I have learned so much. Keep an Open Mind. Really inspired! I can’t wait to share the day Learning Objectives Increased confidence regarding developing inclusive practice in mainstream schools Access to a wider range of practical strategies to impact on behaviour problems Deeper understanding of core values surrounding inclusion of disabled children Opportunity to reflect on professional attitudes and behaviour towards parents and pupils New skills and processes to make inclusion successful Who Is It For ? Early Years and School based Practitioners Heads and Deputies SENCOs Advanced Skills Teachers Primary and secondary teachers Parents Local Authority Support Services Course Content The course answers the questions : What next after a Keys day? How do we take people with us? What else can we do to go about including high profile children or young people? What does inclusion really have to do with me? Best delivered over the course of a full day, ‘Keys to Inclusion’ introduces participants to 6 guiding Ideas that underpin inclusive practice. The power of imagination Determination and persistence Growing Relationships How to help not hinder Communicating honestly and directly Creating Community Circles If you liked this course you may well like: KEYS TO INCLUSION Or: INCLUSION: IT DOESN’T JUST HAPPEN