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The aim of the Managing and Improving Quality in Health and Social Care course is to provide learners with an understanding of the principles and practices of quality management in health and social care settings. The course aims to equip learners with the necessary knowledge and skills to manage and improve the quality of care provided to service users. By the end of the course, learners should be able to understand the importance of quality management, identify and implement quality improvement initiatives, and evaluate the effectiveness of quality management systems. After the successful completion of the course, you will be able to: Understand the concept and importance of stakeholders in Quality Improvement Learn about the duties and responsibilities of the stakeholders in healthcare Appreciate the stakeholder's perspectives and analysis Comprehend the four and nine-sector table analysis Understand the concept of the synergy model in health and social care Look into the quality measurement and its framework This course covers the fundamental principles of quality improvement in health and social care. Students will learn about the key stakeholders involved in quality improvement, their responsibilities and perspectives. The course will also explore various models and frameworks for quality improvement, such as the four and nine-sector table analysis and the synergy model. In addition, students will gain an understanding of the process of measuring and evaluating quality in healthcare. By the end of the course, students will have the knowledge and skills necessary to manage and improve quality in health and social care settings. This course covers the fundamental principles of quality improvement in health and social care. Students will learn about the key stakeholders involved in quality improvement, their responsibilities and perspectives. The course will also explore various models and frameworks for quality improvement, such as the four and nine-sector table analysis and the synergy model. In addition, students will gain an understanding of the process of measuring and evaluating quality in healthcare. By the end of the course, students will have the knowledge and skills necessary to manage and improve quality in health and social care settings. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Managing and Improving Quality in Health and Social Care - N Self-paced pre-recorded learning content on this topic. Managing and Improving Quality in Health and Social Care Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. Healthcare Manager Social Care Manager Equality, Diversity and Inclusion (EDI) Manager HR Manager or HR Business Partner Healthcare Professional Social Care Professional Nurse or Caregiver Medical or Allied Health Professional Diversity and Inclusion (D&I) Consultant Employee Relations Specialist Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

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About this Virtual Instructor Led Training (VILT) This 5 half-day VILT course will comprehensively cover the technical aspects of gas processing. The scope will be from the wellhead through the typical gas processing plant and discuss gas gathering (pipeline hydraulics), natural gas treating (H2S, CO2 removal), acid gas injection and sulfur recovery. One unique aspect of this training course is the operations and troubleshooting discussions in each module. This VILT course is suited to technical personnel or technical management. Training Objectives After the completion of this VILT course, participants will be able to: Grasp the key specifications of natural gas and liquid products Understand the physical and transport properties of gases and liquids and liquid-vapor phase behavior Explore the various technologies for processing natural gas and to make the specifications Examine the design of the technologies Learn how to diagnose operating problems to keep facilities running reliably Target Audience This VILT course is intended for all surface technical personnel such as process engineers & technologists, facility engineers and production engineers & technologists. This VILT course will greatly benefit but not limited to: Process, petroleum and production engineers Field operators and technicians Personnel involved in gas treatment and processing Managers and Supervisors involved with gas processing operations Course Level Basic or Foundation Intermediate Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). The maximum number of participants for this course is 20 persons. Case studies and Exercises: This VILT course will use actual case references throughout its duration in various forms. This will allow the application of the participants' newly-acquired knowledge. Case studies also stimulate independent thinking and discussion among the participants Trainer Your expert course leader has written several papers that have been published in both academic and industry journals. He has over 30 years of industry experience, specializing in gas processing (pipeline hydraulics, separation, dehydration, treating, sulphur recovery and refrigeration processes) and also has experience with crude oil dehydration, stabilization and micro-refining topping plants. He has experience with developing new technology and is recently involved in lithium, waste biomass and used motor oil pyrolysis and geothermal projects. He has recognized expertise in thermodynamics and physical and transport properties of fluids. He has consulted for several EPC and operating companies through his company Chem-Pet Process Tech., and currently holds the role of Director of Technology in an integrated engineering and solutions provider to the energy industry. He is currently involved with a small power-based carbon capture project as well as helping clients determine the best options for utilities decisions. He has been involved with CO2 dehydration and CO2 flood gas treating as well as acid gas injection projects for several years. Highlighted Achievements: Developed ORC geothermal model to determine the available power from wells in Alberta Acting on the Technical Advisory Board for E3 Metals, extracting lithium from formation water. Acted as a Subject Matter Expert for assessing the performance of the Plains Midstream Canada, Empress 1 Deep Cut Straddle Plant in a potential litigation. Acted as an Expert Witness for JL Transportation patent defence of a dense phase technology. Process engineer lead on the addition of the new Orloff gas plant for Deltastream. Also troubleshooted the oil battery shipping pump, plate exchanger and FWKO and treater. Evaluated gas processing and sulphur recovery options for new feeds to the Zhaikmunai Zelenovsky Gas Plant, Kazakhstan (with PM Lucas, Serbia). Completed capacity analysis for hydrocarbon dew point versus liquid recovery of three trains at Birchcliff Pouce Coupe facility including amine unit, refrigerated gas plant and acid gas injection. Completed process design for CO2 flue gas dehydration for Husky Energy Inc (with Status Engineering) Provided simulations of EnCana Foster Creek and Christina Lake and Husky McMullen SAGD facilities (with Vista Projects). Performed process engineering for Cenovus Pelican Lake SAGD pilot (with GRB Engineering) Bear Lake heavy oil polymer injection pilot (with GRB Engineering). Lead process engineer on the design of IEC Kerrobert crude oil micro-refinery (topping plant). Provided engineering support and troubleshooting for Enerchem Slave Lake Crude tower and product blending (with Status Engineering). 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 post training support and fees applicable Accreditions And Affliations

Use Cases for Business Analysis: In-House Training The use case is a method for documenting the interactions between the user of a system and the system itself. Use cases have been in the software development lexicon for over twenty years, ever since it was introduced by Ivar Jacobson in the late 1980s. They were originally intended as aids to software design in object-oriented approaches. However, the method is now used throughout the Solution Development Life Cycle from elicitation through to specifying test cases, and is even applied to software development that is not object oriented. This course identifies how business analysts can apply use cases to the processes of defining the problem domain through elicitation, analyzing the problem, defining the solution, and confirming the validity and usability of the solution. What you will Learn You'll learn how to: Apply the use case method to define the problem domain and discover the conditions that need improvement in a business process Employ use cases in the analysis of requirements and information to create a solution to the business problem Translate use cases into requirements Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Overview of use case modeling What is a use case model? The 'how and why' of use cases When to perform use case modeling Where use cases fit into the solution life cycle Use cases in the problem domain Use cases in the solution domain Use case strengths and weaknesses Use case variations Use case driven development Use case lexicon Use cases Actors and roles Associations Goals Boundaries Use cases though the life cycle Use cases in the life cycle Managing requirements with use cases The life cycle is use case driven Elicitation with Use Cases Overview of the basic mechanics and vocabulary of use cases Apply methods of use case elicitation to define the problem domain, or 'as is' process Use case diagrams Why diagram? Partitioning the domain Use case diagramming guidelines How to employ use case diagrams in elicitation Guidelines for use case elicitation sessions Eliciting the problem domain Use case descriptions Use case generic description template Alternative templates Elements Pre and post conditions Main Success Scenario The conversation Alternate paths Exception paths Writing good use case descriptions Eliciting the detailed workflow with use case descriptions Additional information about use cases Analyzing Requirements with Use Cases Use case analysis on existing requirements Confirming and validating requirements with use cases Confirming and validating information with use cases Defining the actors and use cases in a set of requirements Creating the scenarios Essential (requirements) use case Use case level of detail Use Case Analysis Techniques Generalization and Specialization When to use generalization or specialization Generalization and specialization of actors Generalization and specialization of use cases Examples Associating generalizations Subtleties and guidelines Use Case Extensions The <> association The <> association Applying the extensions Incorporating extension points into use case descriptions Why use these extensions? Extensions or separate use cases Guidelines for extensions Applying use case extensions Patterns and anomalies o Redundant actors Linking hierarchies Granularity issues Non-user interface use cases Quality considerations Use case modeling errors to avoid Evaluating use case descriptions Use case quality checklist Relationship between Use Cases and Business Requirements Creating a Requirements Specification from Use Cases Flowing the conversation into requirements Mapping to functional specifications Adding non-functional requirements Relating use cases to other artifacts Wire diagrams and user interface specifications Tying use cases to test cases and scenarios Project plans and project schedules Relationship between Use Cases and Functional Specifications System use cases Reviewing business use cases Balancing use cases Use case realizations Expanding and explaining complexity Activity diagrams State Machine diagrams Sequence diagrams Activity Diagrams Applying what we know Extension points Use case chaining Identifying decision points Use Case Good Practices The documentation trail for use cases Use case re-use Use case checklist Summary What did we learn, and how can we implement this in our work environment?

Highlights of the Course Course Type: Online Learning Duration: 1 Hour 56 Minutes Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about addiction counselling Understand the core competencies and principles of addiction counselling Explore the various areas of addiction counselling Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert addiction counsellor Addiction Counselling Course Diploma Course Master the skills you need to propel your career forward in addiction counselling. This course will equip you with the essential knowledge and skillset that will make you a confident addiction counsellor and take your career to the next level. This comprehensive addiction counselling course diploma course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying thisaddiction counselling course diploma course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective addiction counselling practice and equip you with the essential skills, confidence and competence to assist you in the addiction counselling industry. You'll gain a solid understanding of the core competencies required to drive a successful career in addiction counselling. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for addiction counsellor or for people who are aspiring to specialise in addiction counselling. Enrol in this addiction counselling course diploma course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive addiction counselling course diploma course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this addiction counselling can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This addiction counselling course diploma course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This addiction counselling course diploma course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This addiction counselling course diploma course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum About Introduction: About instructor & the course 00:02:00 Theories of Addiction The Moral Model 00:05:00 The Psychological Model 00:06:00 The Medical / Disease Model 00:09:00 The Socio-Cultural Model 00:05:00 Addiction Treatments Pharmacotherapy 00:03:00 The Minnesota Model 00:04:00 Counselling and Therapy 00:07:00 Harm Reduction Model 00:04:00 Treatments in Practice 00:05:00 Addiction in Society Drug policies, Legislation and Decriminalisation 00:08:00 Community change, Outreach, Harm Reduction or Abstinence 00:06:00 Alcohol and Drug education 00:05:00 Alcohol- and drug related issues in the workplace 00:06:00 Addiction in Families Codependency, Children of alcoholic families, parenting styles, family factors 00:08:00 Relapse for families, 'letting go', dependent attitudes and dependent behaviours 00:04:00 Al-Anon 00:04:00 The Intervention Approach3 00:04:00 Working with Addiction Why be a 'helper' 00:03:00 'Helper' qualities and attitudes 00:03:00 Counselling / 'helping' skills 00:04:00 Assessment Assessment - Addiction Counselling and Psychology 00:10:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

In this practical workshop session we will explore ways of including pupils who have been labelled as being on the autism spectrum. The session will be values based and practical and will aim to allow the sharing of experiences and good practice as well promoting innovative approaches to inclusion through the design of best practice. Course Category Autism and Communication Description In this practical workshop session we will explore ways of including pupils who have been labelled as being on the autism spectrum. The session will be values based and practical and will aim to allow the sharing of experiences and good practice as well promoting innovative approaches to inclusion through the design of best practice. Parental perspectives and experiences will also be explored. This is not a ‘medical model’ day on autism. Our motto for the day is ‘People do things for a Reason (and the reason isn’t autism).’ We make full use of first hand accounts of the experience of autism – the autobiographies – to deepen participants’ understanding of what it means to be labeled ‘autistic’ “We are all much more simply human than otherwise, be we happy and successful, contented and detached, miserable and disordered, or whatever.”HARRY STACK SULLIVAN Testimonials ‘A great day – going away buzzing with ideas’?? ‘Thanks for a wonderful day. Useful informative and a real ‘eye opener’. I feel that I am able to understand why some autistic children carry out certain actions’ ‘I have gained a lot of knowledge and understanding and will be able to help support and accommodate children better. Thank you.’ ‘I now know autism is part of us all’ ‘Useful to stand in shoes of autistic people’ ‘I was blessed to be on this day’ ‘I will take all these ideas back to the nursery’ ‘Very respectful of people on the spectrum.’ ‘Ways of reaching a person, not a condition.’ ‘Really gave me an idea of how people feel.’ Learning Objectives Increased confidence regarding autistic pupils and their inclusion in mainstream schools Access to a wider range of practical strategies to impact on communication and behaviour issues Deeper understanding of core values surrounding inclusion New skills and processes to strengthen the inclusion of young Autistic people in all settings Who Is It For ? Early years and school based practitioners Heads and deputies Guidance staff Learning support teams SENCOs Primary and secondary teachers Parents Local authority support services Community workers and carers Course Content The course answers the questions : What is autism? How do we go about including autistic children or young people? What does autism have to do with me? Key themes include: Movement differences Strategies for Facilitating Communication Supports and Accommodations for Sensory Sensitivities Developing Friendships and Peer Support School and Family Partnerships ‘Learning to Listen’ – Positive Behavioural Supports Developing School wide Supports for Teachers and Students

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