42802 Learning courses in Bradford delivered Online

Ignite your dynamic career and strengthen your deep insight knowledge by signing up for Fast Learning Techniques: Make Your Brain Super Fast. This course is the ideal approach for you to obtain a thorough understanding and knowledge of the subject. We are concerned about the progression of your career. Therefore, after conducting extensive studies and consulting with experienced personnel, we formulated this outstanding Fast Learning Techniques: Make Your Brain Super Fast course to improve your pertinent skills. In this easy-to-digest course, you will get exclusive training, which will enable you to stand out in this competitive market. However, the course covers all of the recent materials in order to keep you up to date with the job market and make you a good fit for your career. This top-notch Fast Learning Techniques: Make Your Brain Super Fast course curriculum comprises basic to advanced levels of modules that will increase your skill sets. After completing this programme, you will attain the productivity to succeed in your organisation. So, if you are eager to see yourself in a gratifying career, then enrol in the course today! What will Make You Stand Out? On completion of this Fast Learning Techniques: Make Your Brain Super Fast online course, you will gain: CPD QS Accredited course After successfully completing the Course, you will receive a FREE PDF Certificate as evidence of your newly acquired abilities. Lifetime access to the whole collection of learning materials. Enroling in the Course has no additional cost. 24x7 Tutor Support You can study and complete the course at your own pace. Course Curriculum Fast Learning Techniques: Make Your Brain Super Fast Module 01: Introduction to Super Learning Module 02: Improving Your Memory and Brain Module 03: Crucial Factors of Super Learning Module 04: Preserving Your Focus Module 05: The Process of Problem Solving Show off your new skills with a certificate of completion. After successfully completing the course, you can order your CPD Accredited Certificates as proof of your achievement absolutely free. Please Note: The delivery charge inside the U.K. is £4.99, and international students have to pay £8.99. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Course the Right Option for You? This Fast Learning Techniques: Make Your Brain Super Fast course is open to everybody. You can access the course materials from any location in the world and there are no requirements for enrolment. Requirements Without any formal requirements, you can delightfully enrol in this Fast Learning Techniques: Make Your Brain Super Fast course. Just get a device with internet connectivity and you are ready to start your learning journey. Thus, complete this course at your own pace. Career path The aim of this exclusive Fast Learning Techniques: Make Your Brain Super Fast course is to help you toward your dream career. So, complete this course and enhance your skills to explore opportunities in relevant areas.

This course aims to teach you how to use Python for machine learning and data science.

Overview This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet 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 Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning for Predictive Maps in Python and Leaflet 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 9 sections • 33 lectures • 05:59:00 total length •Introduction: 00:10:00 •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 •Adding the settings.py Code: 00:07:00 •Creating a Django Model: 00:10:00 •Adding the admin.py Code: 00:21:00 •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 •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 •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 •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 •Resource: 00:00:00 •Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00

Master the art of super learning and unlock your brain's true potential with our course on Enhancing Memory and Brain Function. From learning the crucial factors of super learning to preserving your focus and tackling complex problem-solving, this transformative journey will empower you to achieve extraordinary mental feats. Enrol today and unleash the limitless possibilities of your mind. Learning Outcomes: Enhance memory retention and recall for efficient information absorption. Improve cognitive abilities and brain function to facilitate super learning. Develop crucial factors necessary for effective super learning. Cultivate strong focus and concentration skills for sustained learning sessions. Master problem-solving techniques to overcome challenges with ease. Harness the power of your mind to achieve extraordinary mental feats. In a fast-paced world where knowledge is power, the ability to learn quickly and effectively is a game-changer. Introducing our comprehensive course on Enhancing Memory and Brain Function for Super Learning. This Super Learning course is designed to tap into the limitless potential of your mind, equipping you with the knowledge and techniques to become a master of super learning. Throughout this transformative journey, you will delve into the fascinating world of super learning, understanding the historical significance and witnessing real-life examples of individuals who have achieved extraordinary mental feats. By exploring the modules, you will gain invaluable insights into improving your memory and brain function, identifying the crucial factors that contribute to super learning, and preserving your focus amidst distractions. Our course goes beyond theory, providing you with practical strategies to tackle complex problem-solving tasks with confidence. By honing your cognitive abilities, you will become adept at absorbing and retaining vast amounts of information. Prepare to unlock the hidden potential of your mind and embark on a journey towards enhanced learning and accelerated personal growth. 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 Super Learning course will be especially helpful for: Students seeking to optimise their learning abilities and academic performance. Professionals aiming to boost their productivity and absorb new skills rapidly. Lifelong learners eager to expand their knowledge and intellectual capabilities. Individuals interested in personal development and exploring the potential of their minds. Career path Cognitive Trainer: £25,000 - £35,000 per year. Learning and Development Specialist: £30,000 - £45,000 per year. Education Consultant: £35,000 - £55,000 per year. Research Assistant in Cognitive Psychology: £20,000 - £30,000 per year. Memory Coach: £25,000 - £40,000 per year. Academic Tutor: £20,000 - £35,000 per year.

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

The underlying patterns in your data hold vital insights; unearth them with cutting-edge clustering and classification techniques in R

The 'Understanding Learning Difficulties and Safeguarding Diploma' course offers a comprehensive exploration of effective learning support and safeguarding practices, equipping participants with essential skills to assist learners with diverse needs. Delve into the role and responsibilities of a Learning Support Assistant, master various teaching methodologies, and acquire the skills needed to provide targeted assistance to students with special educational needs. Learn how to create an inclusive and supportive learning environment while prioritizing the safety and well-being of children and young people. Learning Outcomes: Develop proficiency as a Learning Support Assistant in diverse educational settings. Acquire a thorough understanding of effective teaching methodologies. Cultivate essential skills for providing specialized support to learners with learning difficulties. Gain insight into the crucial role and responsibilities of a Learning Support Assistant. Explore strategies for supporting pupils with special needs, enhancing their learning experiences. Learn how to create an inclusive classroom environment that accommodates diverse learning needs. Understand the principles and practices of safeguarding children and young people. Develop the ability to identify and address potential safeguarding concerns. Why buy this Understanding Learning Difficulties and Safeguarding Diploma? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Understanding Learning Difficulties and Safeguarding Diploma 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 will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Understanding Learning Difficulties and Safeguarding Diploma does not require you to have any prior qualifications or experience. You can just enrol and start learning.  Aspiring Learning Support Assistants seeking comprehensive training. Current Learning Support Assistants aiming to enhance their skills and knowledge. Teachers and educators interested in expanding their understanding of learning difficulties and safeguarding. Individuals considering a career in special education or student support. Prerequisites This Understanding Learning Difficulties and Safeguarding Diploma was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Learning Support Assistant - Median salary of £16,000 - £25,000 per year. Special Education Teacher - Median salary of £25,000 - £40,000 per year. Educational Consultant - Median salary of £30,000 - £45,000 per year. Behaviour Specialist - Median salary of £25,000 - £40,000 per year. Safeguarding Officer - Median salary of £25,000 - £35,000 per year. Course Curriculum Module 01: Learning Support Assistant: Workplace & Work Module 01: Learning Support Assistant: Workplace & Works 00:30:00 Module 02: Teaching Methodologies Module 02: Teaching Methodologies 00:30:00 Module 03: Skills of a Learning Support Assistant Module 03: Skills of A Learning Support Assistant 00:20:00 Module 04: The Role and Responsibilities of the Learning Support Assistant Module 04: The Role and Responsibilities of the Learning Support Assistant 00:20:00 Module 05: SEN Teaching Module 05: SEN Teaching 01:00:00 Module 06: How to Support Pupils with Special Needs Part 1 Module 06: Supporting Pupils with Special Needs (Part 01) 00:30:00 Module 07: How to Support Pupils with Special Needs Part 2 Module 07: How to Support Pupils with Special Needs Part-2 00:50:00 Module 08: Safeguarding Children & Young People Module 08 Safeguarding Children and Young People 00:20:00 Mock Exam Mock Exam - Understanding Learning Difficulties and Safeguarding Diploma 00:20:00 Final Exam Final Exam - Understanding Learning Difficulties and Safeguarding Diploma 00:20:00

Aim To increase the confidence and knowledge of participants to support adults with learning disabilities in terms of their sexual health and sex and relationships rights.   Outcomes By the end of the training participants will have: -had an update around the law, mental capacity act and capacity to consent to sexual relationships and CQC guidance - considered how to support patients with their sex and relationships rights -more knowledge of current easy read and other resources and organisations available to support our work   Agenda Welcome, introductions and working agreement The law, capacity to consent and CQC guidance Rights of people with learning disabilities to sex and relationships Resources and organisations Close   Suitable for   Anyone supporting adults with learning disabilities as a care worker or social worker.

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