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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.

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

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

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Are you looking to improve your current abilities or make a career move? Our unique Course might help you get there! Expand your expertise with high-quality training - study the course and get an expertly designed, great value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through the Coaching & Mentoring Skills online training course. This course is accredited by CPD with 10 CPD points for professional development. Students can expect to complete this Effective Minute Taking Training course in around 6 hours. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course. The course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of the course, you will receive an instant e-certificate as proof of the comprehensive skill development and competency. Add these amazing new skills to your resume and boost your employability by simply enrolling on this course. With this comprehensive course, you can achieve your dreams and train for your ideal career. The course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development. You'll get a Free Student ID card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards. Enrolling on this course will ensure that you land your dream career faster than you thought possible. Stand out from the crowd and train for the job you want with the programme. Experts created this course to provide a rich and in-depth training experience for all students who enrol in it. Enrol in the course right now and you'll have immediate access to all of the course materials. Then, from any internet-enabled device, access the course materials and learn when it's convenient for you. Start your learning journey straight away with this course and take a step toward a brighter future! Why Prefer this Course? Opportunity to earn a certificate accredited by CPD after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery) Standards-aligned lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete this programme in your own time, at your own pace Each of our students gets full 24/7 tutor support *** Course Curriculum *** Here is the curriculum breakdown: Module 1: Introduction This course module covers the following topics: What is Coaching? The Five Principles of Coaching Definition of a Coach The Duties of a Coach Characteristics of A Successful Coach Coaching Traps and Problems What is Mentoring? Definition of Mentor and Mentee Roles & Responsibilities of A Mentor Module 2: Coaching & Mentoring: Objectives & Processes This course module covers the following topics: Objectives Processes The Differences Between Coaching & Mentoring Barriers Individual Barriers Organisational Barriers Techniques for Overcoming Barriers Module 3: Ethical Aspects This course module covers the following topics: Association for Coaching's Guiding Principles 'AC' and 'EMCC's Code of Ethics International Coach Federation(ICF) Standards of Ethical Conduct Professional Conduct At Large Professional Conduct with Clients Confidentiality/Privacy Conflicts of Interest Module 4: Models This course module covers the following topics: An Introduction The GROW Model The OUTCOMES Model The JOHARI Window The FLOW Model The SOS Model The Cyclical Mentoring Model The Double Matrix Mentoring Model Module 5: Effective Communication Skills This course module covers the following topics: Creating a Good Coaching & Mentoring Relationship Using Appropriate Language Listening to A Deep Level Asking Effective Questions Limiting Beliefs/Assumptions Giving Effective Feedback Communicating Non-Verbally Presence and Silence Module 6: Personal Skills This course module covers the following topics: Time Management Stress Management Emotional Management and Happiness Maintenance Assertiveness Negotiation Module 7: Management Skills This course module covers the following topics: Motivating Leading Delegation Decision Making and Problem Solving Project Management Module 8: Functional Skills This course module covers the following topics: Sales Skills Sales Management Marketing Management Financial Management Production Management Assessment Process Once you have completed all the modules in the course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course. Show off Your New Skills with a Certificate of Completion The learners have to complete the assessment of this course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is This Course Right for You? Anyone interested in learning more about this subject should take this course. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. All are welcome to take this course. There are no prerequisites for enrolment, and you can access the course materials from any location in the world. Requirements The programme does not require any prior knowledge; everyone may participate! This course is open to anyone interested in learning from anywhere in the world. Every student must be over the age of 16 and have a passion for learning and literacy. This 100% online course can be accessed from any internet-connected device, such as a computer, tablet, or smartphone. This course allows you to study at your speed and grow a quality skillset. Career path After completing this Course, you are to start your career or begin the next phase of your career in this field. Our entire course will help you to gain a position of respect and dignity over your competitors. The certificate enhances your CV and helps you find work in the field concerned.

Overview This comprehensive course on Django Rest Framework Level 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Django Rest Framework Level 4 comes with accredited certification, 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 Django Rest Framework Level 4. It is available to all students, of all academic backgrounds. Requirements Our Django Rest Framework Level 4 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 15 sections • 82 lectures • 04:40:00 total length •Module 01: Course and Instructor Introduction: 00:03:00 •Module 02: How to make the best of this course: 00:02:00 •Module 01: What is REST?: 00:06:00 •Module 02: Why REST: 00:08:00 •Module 03: What and Why DJango REST Framework: 00:06:00 •Module 01: Install DJango: 00:03:00 •Module 02: Install DJango REST Framework: 00:01:00 •Module 03: Install MySql and MySql workbench: 00:03:00 •Module 04: Launch MySql workbench: 00:02:00 •Module 05: Install python mysqlclient: 00:01:00 •Module 06: Install ATOM: 00:03:00 •Module 07: Install Postman: 00:01:00 •Module 01: Create the project: 00:02:00 •Module 02: Create a view: 00:02:00 •Module 03: Configure the URL and TEST: 00:03:00 •Module 04: Create app level urls: 00:02:00 •Module 05: Create a model class: 00:03:00 •Module 06: Configure the database and run migrations: 00:03:00 •Module 07: Use the model in the view and test: 00:03:00 •Module 01: DRF Components: 00:06:00 •Module 02: Function Based Views: 00:05:00 •Module 03: Serializers: 00:04:00 •Module 04: Create the Project: 00:02:00 •Module 05: Create the Model: 00:02:00 •Module 06: Create the Serializer: 00:02:00 •Module 07: GET single student: 00:04:00 •Module 08: Create Student: 00:04:00 •Module 09: Implement Non Primary Key Based Operations: 00:07:00 •Module 10: Use @api_view: 00:01:00 •Module 11: Configure the URLs: 00:02:00 •Module 12: Test: 00:07:00 •Module 13: Test Using Postman: 00:04:00 •Module 01: Introduction: 00:01:00 •Module 02: Create the Project: 00:01:00 •Module 03: Implement Non Primary Key Based Operations: 00:06:00 •Module 04: Implement Primary Key Based Operations: 00:07:00 •Module 05: Configure the URLs and TEST: 00:04:00 •Module 01: Introduction: 00:05:00 •Module 02: Non Primary Key based operations: 00:04:00 •Module 03: Primary Key based operations: 00:02:00 •Module 04: Configure the URLs and TEST: 00:02:00 •Module 01: Generics: 00:03:00 •Module 02: Generics in action: 00:03:00 •Module 01: Introduction: 00:03:00 •Module 02: Create ViewSet: 00:02:00 •Module 03: Configure URLs and Test: 00:04:00 •Module 01: Create the Project: 00:03:00 •Module 02: Create model: 00:03:00 •Module 03: Create Serializers: 00:04:00 •Module 04: Create REST endpoints: 00:03:00 •Module 05: Configure URLs: 00:02:00 •Module 06: Test: 00:03:00 •Module 01: Introduction: 00:06:00 •Module 02: Pagination in action: 00:05:00 •Module 03: Pagination at class level: 00:03:00 •Module 04: Using LimitOffsetPagination: 00:01:00 •Module 01: Introduction: 00:04:00 •Module 02: Authentication in action: 00:03:00 •Module 03: Authorization in action: 00:06:00 •Module 04: Global Security: 00:04:00 •Module 01: Usecase: 00:01:00 •Module 02: Create the Project: 00:01:00 •Module 03: Create Model Classes: 00:03:00 •Module 04: Create Reservation Model: 00:01:00 •Module 05: Create Serializers: 00:01:00 •Module 06: Create ViewSets: 00:02:00 •Module 07: Configure the Router: 00:02:00 •Module 08: Run Migrations: 00:01:00 •Module 09: Initial round of testing: 00:04:00 •Module 10: Implement findFlights endpoint: 00:03:00 •Module 11: Test findFlights: 00:05:00 •Module 12: Implement Save Reservation: 00:06:00 •Module 13: Test Save Reservation: 00:04:00 •Module 01: In-Built Validations: 00:04:00 •Module 02: Allowing Blank and Null Values: 00:02:00 •Module 03: Create Custom Validator: 00:05:00 •Module 04: Two more ways: 00:07:00 •Module 01: Introduction: 00:03:00 •Module 02: Configure Token Auth: 00:05:00 •Module 03: Create Users and Token: 00:04:00 •Module 04: Token Auth in action: 00:03:00 •Module 05: Automate Token Creation: 00:09:00

Explore how you can build interactive and dynamic web content using JavaScript to create fun mini-projects

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content 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 Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Pros of consensus-building are to gain widespread agreement with a group, but it's more time consuming that voting. There's no room for competitive positions trying to win over others in consensus. Agreement requires what's best for the team. Discover ways to navigate agreements and implement six steps for reaching team consensus. Learning Objectives Describe the conditions for successfully reaching consensus, Apply a quick-consensus model for urgent decisions, Implement six steps for reaching team consensus Target Audience Managers, Team Leaders, Young Professionals, Sales Professionals, Customer Service Teams