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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.

About this Virtual Instructor Led Training (VILT) This Virtual Instructor Led Training (VILT) course presents advanced methodologies that implement demand response and energy conservation programs in light of the integration of new technologies, regulatory changes and the accelerated penetration of renewable energy resources. This VILT course provides examples and case studies from North American and European jurisdictions covering the operational flexibilities on the demand side including requirements for new building codes to achieve zero net energy. The course describes a public agency's goals and objectives for conserving and otherwise reducing energy consumption and managing its demand for energy. This course presents the demand response implemented for economics and system security such as system balancing and relieving transmission congestion, or for system adequacy. The course also presents the principal attributes of conservation programs and the associated success criteria. In a system with increased penetration of renewable resources, demand response provides flexibility to system operators, helping them to maintain the reliability and the security of supply. Demand response is presented as a competitive alternative to additional power sources, enhancing competition and liquidity in electricity markets. The unique characteristics are discussed from a local, consumer centric and also from a system perspective bringing to life the ever changing paradigm for delivery energy to customers. Interoperability aspects and standards are discussed, as well as the consumer centric paradigm of Transactive Energy with IOT enabled flexibilities at system level, distribution networks and microgrids. The VILT course introduces the blockchain as a new line of defense against cyber threats and its increasing application in P2P transactions and renewable certificates. Our trainer's industry experience spans three decades with one of the largest Canadian utilities where she led or contributed to large operational studies and energy policies and decades of work with IEEE, NSERC and CIGRE. Our key expert also approaches to the cross sectional, interdisciplinary state of the art methodologies brings real life experience of recent industry developments. Training Objectives Innovative Digital Technologies How systems Facilitate Operational Flexibility on the Demand Side The Ecosystem of Demand Side Management Programs Advanced Machine Learning techniques with examples from CAISO Regulatory Policy Context and how to reduce regulatory barriers Industry Examples from NERC and ENTSO Relevant Industry standards: IEEE and IEC Manage Congestion with Distributed Operational Flexibilities: Grid to Distribution Controls; examples from NERC (NA) and ENTSO (Europe) Grid solutions with IEC 61850 communication protocols Decentralized grid controls The New Grid with accelerated V2G and Microgrids How DSM is and will be applied in Your System: Examples and discussions Target Audience Regulators and government agencies advising on public energy conservation programs All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices Any utility professional interested in understanding the new developments in the power industry Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 x 10 minutes break per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Description Osteoporosis Awareness Diploma Osteoporosis means 'porous bone'; it is a medical condition in which bones become brittle and fragile, thus leading to breaking bones from minor injuries like a fall or even simple actions like sneezing. Osteoporosis may be caused due to hormonal changes or deficiency of mineral calcium or vitamin D. People with osteoporosis either lose too much bone or make too little or both, making their bones have less density or mass, resulting in abnormal bone structure and weak bone tissue. Osteoporosis is a severe disease as weak bones break, accompanied by severe pain that may not quickly disappear. Statistics tell us that around one in every two women and approximately one in four men aged above 50 will get a broken bone from osteoporosis. Osteoporosis is most likely to affect the bones in the hip, spine and wrist and if the bones of the spine collapse or break, your body posture changes. Osteoporosis can even cause some people to lose their height. Osteoporosis restrains body movement and agility, which keeps people from doing everyday activities leading to isolation and depression. Osteoporosis also leads to other health problems, and those affected may require long-term nursing and care. Lack of osteoporosis awareness is a serious issue because osteoporosis is responsible for two million broken bones every year, which translates to $19 billion spent annually on osteoporosis. This amount is expected to reach around $25 billion annually by 2025, with three million broken bones. Osteoporosis Awareness Diploma is an introductory course that provides insights into what is dubbed as a 'silent disease because of its scarcity of noticeable symptoms. Osteoporosis Awareness Diploma is a highly recommended course for everyone, especially those in their middle ages and leading a sedentary lifestyle. What you will learn 1:Understanding Osteoporosis 2:The Bone 3:The Major Risk Factors of Osteoporosis 4:Osteoporosis in Men and Children 5:Maintaining Strong Bones through Healthy Diet 6:Exercise to Maintain Healthy Bones 7:Dangers of Fragile Bones 8:Finding a Doctor 9:Bone Testing 10:Drugs for Osteoporosis Course Outcomes After completing the course, you will receive a diploma certificate and an academic transcript from Elearn college. Assessment Each unit concludes with a multiple-choice examination. This exercise will help you recall the major aspects covered in the unit and help you ensure that you have not missed anything important in the unit. The results are readily available, which will help you see your mistakes and look at the topic once again. If the result is satisfactory, it is a green light for you to proceed to the next chapter. Accreditation Elearn College is a registered Ed-tech company under the UK Register of Learning( Ref No:10062668). After completing a course, you will be able to download the certificate and the transcript of the course from the website. For the learners who require a hard copy of the certificate and transcript, we will post it for them for an additional charge.

Updated On: April 2024 All good organisations know the importance of a good HR (Human Resources Training) department. And as remote working has become a popular choice among employees and employers, the way HR Management works has changed dramatically in the last few years. Get essential HR Management skills for 2024. Enrol in this HR Management, UK Payroll & Tax Accounting course to learn every on-demand HR Management skill that employers are looking for nowadays. The Advanced Diploma in (HR) Human Resources at QLS Level 7 Training Offers the Following Courses: Course 01: (HR) Human Resources at QLS Level 7 Course 02: Diploma in Recruitment Management Course 03: UK Payroll Management Course 04: Tax Accounting Course 05: Business Administration This Advanced Diploma in HR Management at QLS Level 7 course is endorsed by The Quality Licence Scheme and Accredited CPD QS. These prestigious accreditations validate its quality and align it with professional standards, making it an ideal choice for individuals seeking to broaden their knowledge and skills in the HR sector. Learning Outcomes of UK Employment Law, HR Management and Payroll Apply core HR practices like recruitment, performance management, and employee relations. Develop effective recruitment strategies to attract top talent. Master the intricacies of UK payroll processing and tax calculations. Gain a solid understanding of relevant employment law and regulations. Implement effective business administration practices to support HR functions. Develop strong analytical and problem-solving skills for the HR field. If you want to get a job in the HR Management industry, then it's time for you to enrol in this course. Experience well-structured, step-by-step lessons on HR Management activities. Start now. What Our Students Say About This UK Employment Law, HR Management and Payroll Course: "I would gladly recommend anyone to take up courses with Red.'' From: Francis Offiong "This is very good medium of learning new era of education." From: MUHAMMAD ANSAR ''It's an interesting course. I hope to use the knowledge to advance in my career as a health worker & carer'' From: Vivian Berenibara. UK Employment Law, HR Management and Payroll Take a step toward a brighter future with HR Management, UK Payroll & Tax Accounting course *** Course Curriculum of HR Management*** Here is the curriculum breakdown of the course: Module 01: Introduction Provides an overview of the recruitment industry, its significance, and the role of recruiters in talent acquisition. Module 02: An Overview of the Recruitment Industry Examines the structure, trends, and key players in the recruitment industry, both globally and in the UK. Module 03: The UK Recruitment Legislation Covers essential UK recruitment laws and regulations, ensuring compliance and ethical practices in hiring. Module 04: The Recruitment Process Details the end-to-end recruitment process, including job postings, candidate sourcing, and selection methods. Module 05: Negotiation Techniques Teaches effective negotiation skills for recruiters to secure the best terms for candidates and employers. Module 06: Key Performance Indicators for the Recruitment Industry Identifies important KPIs and metrics to measure and improve recruitment performance and effectiveness. Module 07: Employee Training and Development Process Explores methods for training and developing employees to enhance their skills and career progression. Module 08: Candidate Management Focuses on managing candidate relationships, from initial contact to job placement and beyond. Module 09: Candidate Interview Processes Covers best practices for conducting effective and fair candidate interviews to assess suitability. Module 10: Managing Meetings and Giving Feedback Provides techniques for managing recruitment meetings and delivering constructive feedback to candidates and clients. Module 11: Performance Appraisal Management Explains the process of conducting performance appraisals to evaluate and enhance employee performance. Module 12: Employee Relations Discusses strategies for maintaining positive employee relations and addressing workplace issues. Module 13: Motivation and Counselling Teaches methods for motivating employees and providing counselling to support their well-being and productivity. Module 14: Ensuring Health and Safety at the Workplace Covers the principles and practices for maintaining a safe and healthy work environment. Module 15: Employer Records and Statistics Focuses on maintaining accurate employer records and using statistics to inform recruitment strategies. Module 16: Conflict Management Provides techniques for managing and resolving conflicts in the workplace effectively. Module 17: Employee Termination Explains the legal and procedural aspects of terminating employment, ensuring compliance and fairness. Module 18: Organisational Skills Develops organizational skills essential for managing recruitment tasks and workflows efficiently. Module 19: Communication Skills Enhances communication skills for effective interactions with candidates, clients, and colleagues. Module 20: Stress Management Offers strategies for managing stress in the fast-paced recruitment industry to maintain well-being and performance. Module 21: Time Management Teaches effective time management techniques to optimize productivity and meet recruitment deadlines. Why Choose Our UK Employment Law, HR Management and Payroll Course: Get instant access to this UK Employment Law, HR Management and Payroll course. Learn UK Employment Law, HR Management and Payroll from anywhere in the world UK Employment Law, HR Management and Payroll is affordable and simple to understand UK Employment Law, HR Management and Payroll is entirely online, interactive lesson with voiceover audio Lifetime access to the UK Employment Law, HR Management and Payroll course materials UK Employment Law, HR Management and Payroll comes with 24/7 tutor support Assessment Process After completing an online HR Management and UK Payroll course module, you will be given a specially designed MCQ test. The passing score for each test will be set at 60%. After passing the Advanced Diploma in HR Management at QLS Level 7 exam, you will be able to request a certificate at an additional cost that has been endorsed by the Quality Licence Scheme. CPD 220 CPD hours / points Accredited by CPD Quality Standards Module 01: Introduction 15:18 1: Introduction Video Preview 00:53 2: Introduction to Human Resources Preview 14:25 Module 02: An Overview of the Recruitment Industry 19:09 3: An Overview of the Recruitment Industry Preview 19:09 Module 03: The UK Recruitment Legislation 18:25 4: The UK Recruitment Legislation Preview 18:25 Module 04: The Recruitment Process 20:54 5: The Recruitment Process Preview 20:54 Module 05: Negotiation Techniques 10:26 6: Negotiation Techniques Preview 10:26 Module 06: Key Performance Indicators for the Recruitment Industry 15:21 7: Key Performance Indicators for the Recruitment Industry 15:21 Module 07: Employee Training and Development Process 14:27 8: Employee Training and Development Process 14:27 Module 08: Candidate Management 12:51 9: Candidate Management 12:51 Module 09: Candidate Interview Processes 14:07 10: Candidate Interview Processes 14:07 Module 10: Managing Meetings and Giving Feedback 13:17 11: Managing Meetings and Giving Feedback 13:17 Module 11: Performance Appraisal Management 14:15 12: Performance Appraisal Management 14:15 Module 12: Employee Relations 09:35 13: Employee Relations 09:35 Module 13: Motivation and Counselling 13:32 14: Motivation and Counselling 13:32 Module 14: Ensuring Health and Safety at the Workplace 13:29 15: Ensuring Health and Safety at the Workplace 13:29 Module 15: Employer Records and Statistics 09:01 16: Employer Records and Statistics 09:01 Module 16: Conflict Management 07:47 17: Conflict Management 07:47 Module 17: Employee Termination 10:45 18: Employee Termination 10:45 Module 18: Organisational Skills 17:06 19: Organisational Skills 17:06 Module 19: Communication Skills 16:24 20: Communication Skills 16:24 Module 20: Stress Management 09:09 21: Stress Management 09:09 Module 21: Time Management 24:53 22: Time Management 24:53 Assessment (Optional) 03:00 23: Assignment On - HR (Human Resources) at QLS Level 7 03:00 Order Your Certificate 02:00 24: Order Your CPD Certificate 01:00 25: Order Your QLS Endorsed Certificate 01:00 Who is this course for? Anyone interested in learning more about the topic is advised to take this HR Management course. This course is open to everybody. Transformation: You can move forward once you've finished this course towards- HR Management CIPD HR Practice Level 3 Certificate in Principles of Human Resource (HR) Practice (RQF) Level 4 Diploma in Human Resource Management Level 7 Diploma in Human Resource Management NCFE Level 3 Diploma in Skills for Business: Human Resources Level 2 Certificate in Recruitment Resourcing Requirements You will not need any prior background or expertise to enrol in this course. Career path Our entire HR Management course will help you to gain a position of respect and dignity over your competitors. Human Resources Executive HR Administration Human Resources Officer Human Resources Assistant Depending on your position, you may receive anything between £25,500 - £70,500 per year in the UK. Certificates Certificate Accredited by CPDQS Digital certificate - Included Advanced Diploma in Human Resources Management at QLS Level 7 Hard copy certificate - £139 Show off Your New Skills with a Certificate of Completion After successfully completing the Advanced Diploma in Human Resources Management at QLS Level 7, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme. The certificate will be home-delivered, with a pricing scheme of - 139 GBP inside the UK 149 GBP (including postal fees) for international delivery Certificate Accredited by CPDQS Upon finishing the HR (Human Resources) course, you will receive a Certificate Accredited by CPDQS that is recognised all over the UK and also internationally. The pricing schemes are - 29 GBP for Printed HardCopy Certificate inside the UK 39 GBP for Printed HardCopy Certificate outside the UK (international delivery)

Course Overview Learn how to make useful digital representations of complex patterns and statistics by taking this Computer Simulation of Realistic Mathematical Models Level 2 course. This intuitive course uses real-world examples to teach you how data can be transformed into online recreations, which can then be more easily understood and changed for research purposes. You'll be capable of turning a complex set of results into simplified visual models, guided by expert tuition and step-by-step instructions.  This Computer Simulation tutorial empowers sophisticated cross-platform computational packages and programming languages to be used in imaginative ways. This will allow the construction of two models on factual data and genuine results. Gaining the ability to perfect these projects will bring the talent to produce further models of this type. You will soon be able to use your capabilities in a wealth of presentations and other projects. This best selling Computer Simulation of Realistic Mathematical Models Level 2 has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Computer Simulation of Realistic Mathematical Models Level 2 is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Computer Simulation of Realistic Mathematical Models Level 2 is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Computer Simulation of Realistic Mathematical Models Level 2 is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Computer Simulation of Realistic Mathematical Models Level 2, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Computer Simulation of Realistic Mathematical Models Level 2 will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Computer Simulation of Realistic Mathematical Models Level 2 to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

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

This course focuses on understanding all the basic theory and programming skills required as a data scientist, featuring 35+ practical case studies covering common business problems faced by them. This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of data science and deep learning to real-world business problems.

Our combined "Highway Code andAccidents, Incidents, and Breakdowns Training" module offers a comprehensive learning experience for drivers. This training covers two essential aspects: understanding the Highway Code and road safety measures to handle accidents, incidents, and breakdowns. 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

Imagine waking up to the sound of birds chirping and the sight of a beautiful garden outside your window. Imagine being able to walk through rows of plants that you have grown yourself, and being able to enjoy the fruits of your labour. This is what our horticulture course can offer you - a chance to learn the secrets of plant care and cultivation, and to turn your passion for gardening into a fulfilling career. With our comprehensive course curriculum, you will gain a deep understanding of the science behind plant growth and development, as well as useful knowledge of gardening techniques and tools. From basic botany to landscaping and garden design, you will learn everything you need to know to become a skilled horticulturist. So if you're ready to embark on a journey of discovery and growth, join our horticulture course today. With our in-depth lessons you'll be well on your way to cultivating your own beautiful garden and building a successful career in horticulture. This Advanced Diploma in Horticulture at QLS Level 7 is endorsed by The Quality Licence Scheme and accredited by CPDQS (with 180 CPD points) to make your skill development & career progression more accessible than ever! To give you the most convenient and comprehensive learning experience possible, the Horticulture course has been divided into a number of in-depth modules. An instant e-certificate that you may order as confirmation of your new abilities and knowledge will be displayed in your profile when the Horticulture course has been successfully completed. Simply enrolling in this Horticulture course will increase your employability and allow you to add these incredible new talents to your resume. Join the Horticulture course today to equip yourself with the necessary skills to position yourself for success! Learning Outcomes: Gain a deep understanding of plant growth and development, including soil science, plant nutrition requirements, and plant protection. Learn essential techniques for plant care and cultivation, such as weed control, plant propagation, and lawn care. Explore the world of organic gardening and permaculture, and learn how to work with native and exotic plants. Develop skills in landscaping and garden design, and learn how to create beautiful outdoor spaces. Understand the principles of arboriculture and ornamental horticulture, and learn how to care for indoor plants. Gain knowledge of horticulture statistics and the labour market in the industry. Develop a passion for horticulture and the natural world, and be inspired to pursue a career in the field. Our Horticulture course provides you with the abilities to: Learning Objectives for the Course on Horticulture: Learn about the anatomy of flowers and how plants are classified in detail. Know how photosynthesis works and why it's so crucial for plants. Learn how to evaluate soil PH and expand your knowledge of soil chemistry. Discover some organic gardening techniques and the advantages of organic farming. Understand how to maintain indoor landscaping, sports fields, and gardens. Learn about plant diseases, as well as how to control weeds and pests. Learn more about plant nutrition and soil health. Discover how to plant a tree and care for it until it reaches maturity step by step. Our horticulture course is designed to provide students with a comprehensive understanding of plant care and cultivation, as well as necessary skills in gardening and landscaping. Through the in-depth lessons students will gain the knowledge and confidence they need to succeed in the field of horticulture. The course begins with an introduction to basic botany and plant classification, followed by modules on soil science, plant nutrition, and plant pests and diseases. Students will then delve into the world of organic gardening, learning about weed control, plant propagation, and the use of native and exotic plants in landscaping. Other modules cover indoor plants, lawns, and plant care and planting techniques. In addition to gardening skills, the course also covers more specialised areas of horticulture, such as arboriculture and ornamental horticulture. Students will also gain an understanding of permaculture and the principles of sustainable gardening. The course concludes with modules on horticulture statistics and the labour market in the industry, giving students a comprehensive overview of the opportunities available to them in the field of horticulture. Whether you're a budding gardener or looking to start a career in horticulture, our course is the perfect place to start. *** Course Curriculum *** Here is the curriculum breakdown of horticulture course: Module 01: Basic Botany Horticulture Module 02: Plant Classification Module 03: Soil Science Module 04: Plant Nutrition Requirements Module 05: Plant Pests & Diseases Module 06: Basic Concepts of Organic Gardening Module 07: Weed Control Module 08: Plant Propagation Module 09: Amenity Horticulture, Plant Selection & Native Plants Module 10: Exotic Plants Module 11: Indoor Plants Module 12: Lawns Module 13: Planting & Plant Care Module 14: Plant Nodes & Indigenous Plants Module 15: Plant Protection, Landscaping & Garden Design Module 16: Ornamental Horticulture Module 17: Permaculture Module 18: Arboriculture Module 19: Horticulture Statistics Module 20: Results from the 2018 Seasonal Labour in Horticulture End of Year Why Prefer Us? Opportunity to earn a certificate endorsed by the Quality Licence Scheme and another certificate accredited by CPDQS. Get a free student ID card! (£10 postal charge will be applicable for international delivery) Innovative and engaging content. Free assessments 24/7 tutor support. Assessment Process You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam.Our expert trainers will assess your assignment and give you feedback after you submit the assignment. After passing the Advanced Diploma in Horticulture at QLS Level 7 course exam, you will be able to request a certificate at an additional cost that has been endorsed by the Quality Licence Scheme. CPD 180 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals who have a passion for plants and gardening and want to turn it into a career. Anyone interested in learning more about plant care and cultivation. People looking to start their own garden or improve their existing one. Professionals in the landscaping and gardening industry who want to broaden their knowledge and skills. Students looking to pursue further studies in related fields. Requirements Working in the field of Horticulture typically requires at least a high school diploma or equivalent, although many employers prefer applicants with a post-secondary education in related field. Career path Horticulturist - Average salary £24,000 to £40,000 per year. Landscape Architect - Average salary £22,000 to £45,000 per year. Arborist - Average salary £20,000 to £32,000 per year. Garden Designer - Average salary £18,000 to £35,000 per year. Park Ranger - Average salary £18,000 to £25,000 per year. Garden Centre Manager - Average salary £20,000 to £35,000 per year. Certificates CPDQS Accredited Certificate Digital certificate - £10 Advanced Diploma in Horticulture Worker at QLS Level 7 Hard copy certificate - £139 Show off Your New Skills with a Certificate of Completion After successfully completing the Advanced Diploma in Horticulture Worker at QLS Level 7 course, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme. The certificate will be home-delivered, with a pricing scheme of - 139 GBP inside the UK 149 GBP (including postal fees) for international delivery CPDQS Accredited Certificate 29 GBP for Printed Hardcopy Certificate inside the UK 39 GBP for Printed Hardcopy Certificate outside the UK (international delivery)