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City & Guilds Level 3 Certificate in Assessing Vocational Achievement This qualification is for anyone working in or looking to enter an assessment role. It is designed for use in England, Wales and Northern Ireland – alternative arrangements exist in Scotland. Learn about the Cavity Training Dental Nurse Assessor Course The units and qualification will provide people who carry out assessment in their organisation with the opportunity to develop and improve their practice as well as achieving a professional qualification for the role. They are available to anyone working in: accredited learning; non accredited learning (where people may assess performance but do not assess for a qualification) and the NQF. Achievers will understand the principles of assessment and have the knowledge to develop and improve systems at their centre. You will gain access to our unique E library of text books. We also have special discounted rates for hard copy text books for our students. Frequently Asked Questions How long is the course? The course duration is 4 to 6 months. When are the classes held? You will attend a live webinar class every Thursday for 16 weeks. Is there an exam at the end? There is no exam at the end, you need to successfully complete 8 assessments and a final professional discussion with your tutor. What if I don’t have student nurses in my practice? We may be able to support you by providing you with learners to assess. Please get in touch. What qualifications do I need to start the course? Preferable English and Maths level 4 and above, you must also be GDC registered. What opportunities for progression is there? This qualification allows candidates to further progress onto various post registration qualifications or career opportunities, such as: – Dental Nurse Teaching – Internal Quality Assurer (IQA) Course Dates 11th April 2024 9:00am - 4:00pm 29th August 2024 9:00am - 4:00pm 2nd January 2025 9:00am - 4:00pm 8th May 2025 9:00am - 4:00pm Costs £800.00 per person (inc. VAT) Other payment options Deposit - £267.00 with 2 further payments Please choose from one of the course start dates above. Each course includes 16 weeks of lessons and up to two months to complete a portfolio and professional discussion.

The driving industry is a vital sector of the economy, offering diverse job opportunities and career paths for those with the necessary skills and qualifications. Learning to drive large vehicles can open doors to exciting and well-paying jobs. Our Learning to Drive Large Vehicles course is designed to equip learners with the knowledge and skills needed to succeed in this industry. Learning outcomes: Develop communication skills to deal with clients Learn to drive both small and large vehicles Overcome disabilities and impairments Tackle ADI exams with ease Pass assessments to ace your exams Gain the confidence to start a career as a driver The Learning to Drive Large Vehicles course is designed to give students a comprehensive understanding of the driver industry. With a curriculum that covers eight modules, including structured driver training, communication skills, and driving large vehicles, this course equips students with the knowledge and skills necessary to become successful drivers. Throughout the course, students will learn from experienced instructors with a wealth of knowledge and expertise in the driver industry. They will also have access to a range of learning resources, including video lectures, interactive quizzes, and assessments to test their understanding of the course material. Whether you're looking to start a new career as a professional driver or simply want to improve your driving skills, this course is the perfect opportunity to do so. So, why wait? Enrol now and take the first step towards a successful career as a driver. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is perfect for: Individuals looking to enter the driver industry Individuals interested in driving large vehicles Individuals who want to overcome disabilities and impairments to become a driver Individuals who want to learn communication skills to deal with clients Individuals who want to tackle ADI exams and pass assessments Career path Some of the career paths related to this field are: Driving Instructor: £20,000 - £35,000 Bus Driver: £18,000 - £28,000 Truck Driver: £20,000 - £40,000 Coach Driver: £20,000 - £35,000 Taxi Driver: £18,000 - £25,000 Delivery Driver: £18,000 - £25,000

This course is perfect for L&D professionals keen to develop their skills and drive change within their organisation and those who want the chance to advance their profession and demonstrate their experience. Course Overview Ready to shape your organisation’s working environment? Discover how to measure your company’s performance and culture, boost people’s confidence and organise different forms of learning across your organisation. Learn how to organise different forms of learning across your organisation to boost people’s confidence and supercharge their development. This course is perfect for L&D professionals keen to develop their skills and drive change within their organisation and those who want the chance to advance their profession and demonstrate their experience. After completing this qualification, you will receive a CIPD Associate Membership. As a result, your professional credibility will be established, your profile will be raised, and new work chances will become available. Is this qualification right for me? This qualification is perfect for you if you enjoy helping employees become the best they can be. You’ll expand your knowledge of L&D with a combination of core units and specialist areas and get an individual plan for your self-development. What will I learn? You’ll study 3 core units + 3 specialist units + the choice of 1 optional unit: Core units: • Organisational performance and culture in practice • Evidence-based practice • Professional behaviours and valuing people Specialist units: • Supporting self-directed and social learning • Learning and development design to create value • Facilitate personalised and performance focused learning Optional units: • Specialist employment law • Advances in digital learning and development • People management in an international context • Diversity and inclusion • Leadership and management development • Well-being at work Typical job titles: • L&D Business Partner or Manager • L&D Consultant • Organisation Design Specialist • Organisational Development Business Partner • Employee Experience Manager • L&D Designer DURATION 12-16 Months WHATS INCLUDED Course Material Case Study Experienced Lecturer Refreshments Certificate

CRRUK equips professionals with the concepts, skills and tools to build conscious, intentional relationships, and to coach relationship systems of any size.

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. 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 Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Experience the future of geographical analysis with our Machine Learning for Predictive Maps in Python and Leaflet course. Master the unique blend of programming, machine learning, and geographic information systems, all while honing your ability to predict and visualise spatial data in a powerful and effective way. This course offers you an unparalleled understanding of modern map creation, combined with the magic of prediction using machine learning models. Starting from the ground up, you'll be introduced to all the necessary setups and installations. After that, you will be diving into the depth of Django server-side code and front-end application code writing. The heart of the course lies in learning how to automate the machine learning pipeline, leading you to easily create predictive models.  Improve your maps with Leaflet programming, making your predictions accurate and also visually striking. By the end of this course, you will be armed with experience furnished by our comprehensive project source code and assignments, empowering you to drive data-driven decisions and insightful spatial analysis. Join us and map your way to success! Sign up today. Learning Outcomes:Upon completion of the Machine Learning course, you will be able to: Understand how to set up and install relevant software and libraries.Master Django server-side and application front-end code writing.Gain proficiency in the concepts and implementation of Machine Learning.Learn to automate Machine Learning pipelines for efficient workflows.Acquire skills in Leaflet programming for enhanced map visuals.Handle project source code effectively for real-world projects.Apply knowledge practically via assignments and gain experience. Who is this course for?This Machine Learning course is ideal for: Aspiring Data Scientists keen on harnessing geographical data.GIS professionals aiming to integrate Machine Learning into their skill set.Software Developers interested in creating geographically-focused applications.Analysts keen on enhancing their data visualisation skills with mapping. CertificationAfter studying the course materials of the Machine Learning for Predictive Maps in Python and Leaflet course, there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test, you have a range of certification options to choose from. You can claim a CPD Accredited PDF Certificate for £4.99, a CPD Accredited Hardcopy Certificate at £8.00, or you may choose to receive a PDF Transcript for £4.99 or a Hardcopy Transcript for £9.99. Select according to your needs, and we assure timely delivery of your chosen certificate. RequirementsThis professionally designed Machine Learning for Predictive Maps in Python and Leaflet course does not require you to have any prior qualifications or experience. It is open to everyone. You will be able to access the course from anywhere at any time. Just enrol and start learning! Career Path:Our Machine Learning course will help you to pursue a range of career paths, such as: Junior Data Analyst: £25,000 - £35,000 annually.Data Scientist: £40,000 - £60,000 annually.GIS Analyst: £30,000 - £45,000 annually.Geospatial Software Developer: £35,000 - £55,000 annually.Machine Learning Engineer: £50,000 - £80,000 annually.Lead Data Scientist (GIS speciality): £70,000 - £100,000+ annually. Course Curriculum Section 01: Introduction Introduction 00:10:00 Section 02: Setup and Installations Python Installation 00:04:00 Creating a Python Virtual Environment 00:07:00 Installing Django 00:09:00 Installing Visual Studio Code IDE 00:06:00 Installing PostgreSQL Database Server Part 1 00:03:00 Installing PostgreSQL Database Server Part 2 00:09:00 Section 03: Writing the Django Server-Side Code Adding the settings.py Code 00:07:00 Creating a Django Model 00:10:00 Adding the admin.py Code 00:21:00 Section 04: Writing the Application Front-end Code Creating Template Files 00:10:00 Creating Django Views 00:10:00 Creating URL Patterns for the REST API 00:09:00 Adding the index.html code 00:04:00 Adding the layout.html code 00:19:00 Creating our First Map 00:10:00 Adding Markers 00:16:00 Section 05: Machine Learning Installing Jupyter Notebook 00:07:00 Data Pre-processing 00:31:00 Model Selection 00:20:00 Model Evaluation and Building a Prediction Dataset 00:11:00 Section 06: Automating the Machine Learning Pipeline Creating a Django Model 00:04:00 Embedding the Machine Learning Pipeline in the Application 00:42:00 Creating a URL Endpoint for our Prediction Dataset 00:06:00 Section 07: Leaflet Programming Creating Multiple Basemaps 00:09:00 Creating the Marker Layer Group 00:10:00 Creating the Point Layer Group 00:12:00 Creating the Predicted Point Layer Group 00:07:00 Creating the Predicted High Risk Point Layer Group 00:12:00 Creating the Legend 00:09:00 Creating the Prediction Score Legend 00:15:00 Section 08: Project Source Code Resource 00:00:00 Assignment Assignment - Machine Learning for Predictive Maps in Python and Leaflet 00:00:00

Learning Coach Qualification – is it right for me? A Learning Coach plays a vital role in guiding and supporting young people in their educational journey, helping them develop a range of skills and attributes that contribute to successful learning, personal growth, and future success. Pursuing a qualification to become a qualified Learning Coach is beneficial for enhancing skills, credibility, and effectiveness in supporting learners’ development. It provides a foundation of knowledge and expertise that contributes to successful coaching experiences. This qualification consists of three units (two mandatory, 1 optional). Please see the Agored Cymru website for full course information, where you can choose the units to suit the needs of your staff. It will cover the following: Young People’s Development: Factors influencing learning, motivation, and barriers to learning. Learning Styles and Inclusive Planning: Learning styles vs. Universal Design for Learning (UDL), planning for inclusive learning. Reflective Practice: Comparison of reflection models, engaging in reflective practice. Coaching for Learning: Communication and coaching skills, coaching models, functions of Learning Coaching Assessing Young People: Interview skills, communication styles, assessing achievements and barriers to learning. Developing Learning Pathways: Coordinating individualised learning pathways, engaging young people in goal-setting Further Information This course spans six months and covers various aspects of Learning Coaching, including understanding learning processes, personal and emotional factors affecting learning, coaching techniques, reflective practice, communication skills, inclusive planning, assessment, and the coordination of individualised learning pathways. Students will engage in assignments, reflective journals, case studies, and portfolio building to demonstrate their understanding and application of the concepts and skills covered in the course. Learning Outcomes Professional Competence: A formal qualification ensures that Learning Coaches have a solid understanding of best practices, theories, and methodologies in the field of education and coaching. It provides them with the necessary knowledge and skills to effectively support learners in their development. Credibility: Having a recognised qualification enhances the Learning Coach’s credibility and reputation. It demonstrates their commitment to their role and their ability to provide high-quality guidance and support. Improved Effectiveness: Learning Coaches who have undergone formal training are better equipped to assess learners’ needs, design personalised learning plans, and provide targeted support. This leads to more effective coaching outcomes. Personal Growth: Going through a qualification process often involves self-reflection, skill development, and continuous learning. This contributes to the personal growth and professional development of the Learning Coach. Network and Community: Enrolling in a qualification program provides Learning Coaches with the opportunity to connect with other professionals in the field. This network can offer support, resources, and collaboration opportunities.

The IOSH Managing Safely® E-Learning course contains learning materials for the whole IOSH Managing Safely® course

The complete guide to creating your own Pose Estimation apps: Learn the full workflow and get up to speed with developing 5 AI apps

Master the art of online teaching with our comprehensive course. Gain practical skills and strategies to engage students, create dynamic online lessons, and effectively utilize digital tools. Enroll now and become a confident and effective online educator!