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(£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 the program 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 of Mental Health Care Training - MCA & DOLS course: Mental Health Care Training - MCA & DOLS Course Module 1. The Mental Capacity Act Introduction to the Mental Capacity The Mental Capacity Act of 2005 Changes that the MCA Will Introduce Module 2. Assessment of Mental Capacity Responsibility for Assessing Capacity Timing of the Capacity Assessment The Test to Assess Capacity Module 3. Best Interest Decision Making Best Interests Dispute About 'Best Interests' Best Interest Decision Making Guide Module 4. 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Authorised Deprivation The Assessment Procedure Assessors Carrying Out the Assessments Timescale for Assessment Module 11. Legal Background to DOLS Defining Deprivation of Liberty - Cheshire West The Code of Practice Safeguarding from Abuse and Neglect Module 12. The Mental Capacity Act (2005) and Deprivation of Liberty Safeguards During a Pandemic Use of the MCA and DoLS in a Pandemic COVID-19 (Coronavirus) Best Interest Decisions Module 13. Liberty Protection Safeguards (LPS) Introduction to the Liberty Protection Safeguards Why Are the Liberty Protection Safeguards Being Introduced? Difference Between the Liberty Protection Safeguards and the Deprivation of Liberty Safeguards. Assessment Process Once you have completed all the modules in the Mental Health Care Training - MCA & DOLS 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. 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The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. 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This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. 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 00:08:00 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 Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 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 00:07:00 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 - Python Machine Learning & Data Science Fundamentals 00:00:00
Learn Python OOP language used diversely in applications like data science, game/web development, machine learning, and AI. This course provides all you need to master OOPs like classes, objects, data abstraction, methods, overloading, and inheritance. The course primarily aims to help you tackle complex programming and use OOP paradigms efficiently.
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(£10 postal charges will be applicable for international delivery) Standard-aligned lesson planning Innovative and engaging contents and activities Assessments that measure higher-level thinking and skills Complete this program in your own time, at your own pace Each of our students gets full 24/7 tutor support *** Course Curriculum *** >> Diploma in Mushroom Growing at QLS Level 5 << Module 01: Introduction to Mushroom Cultivation What Are Mushrooms? Benefits of Mushroom Culture Mushrooms in Ecosystems Techniques for Mushroom Cultivation Cultivation Process Preparation for Mushroom Growing Module 02: Identifying Edible Mushrooms Necessity of Identification Mushroom Hunting Equipment Suitable Hunting Time Places to Look for Mushrooms Picking Wild Fungi Identification Notes Poisonous Fungi Species to Avoid Module 03: Mushroom Culture Part One What are Mushroom Cultures? Spore Prints Liquid Culture (LC) Tissue Culturing to Liquid Culture Making a Spore Syringe LC or Spore Syringe to LC Transfer Agar Plate or Slant to LC Transfer Grain or Sawdust Spawn to LC Transfer Module 04: Mushroom Culture Part Two Agar Culture Preparation of Agar Medium Tissue Culturing to Agar Inoculating Agar with Spores Module 05: Mushroom Spawning Developing Grain Spawn Spawning Spawning Methods Spawning Environment Super Spawning Supplementation at Spawning Supplementation at Casing (S.A.C.) Module 06: Mushroom Compost Part One Necessity of Composting Phase-1 Composting Supplements Composting Elements Pre-Wetting Building Compost Pile Composting Tools Characteristics of the Compost at Filling Module 07: Mushroom Compost Part Two Phase-2 Composting Phase-2 Room Design Phase-2 in Bulk Module 08: Making and Casing Mushroom Beds Mushroom Beds Mushroom Bed Conditions Bed Making Site Bed Making Time Building a Mushroom Bed Casing Mushroom Beds Using Peat Casing Preparation Casing Application Casing Moisture and Mycelial Appearance Module 09: Mushrooms Growing Conditions The Conditions Needed to Grow Mushrooms Sanitation and Techniques to Avoid Contamination Module 10: Growing Mushrooms Outside 'Lasagna' Mulching for Growing Procedure for Lasagna Mulching Growing Mushrooms on Logs Procedure for Growing Mushrooms on Logs Module 11: Harvesting and Storing Mushrooms When to Harvest? How to Harvest? Spore Printing Storing Mushrooms Storing Mushrooms without Refrigerator Drying Mushrooms Freezing Mushrooms Module 12: Mushroom Business Starting the Business Marketing Mushrooms Customer Base Running the Business Assessment Process Once you have completed all the modules in the Substance Misuse Outreach Worker 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 Substance Misuse Outreach Worker course. You'll also be provided with an assignment for further assessing your newly-gained knowledge & skills which is optional to submit. CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about this subject should take this course. This Mushroom Growing 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 Mushroom Growing program 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. Certificates CPD Accredited Certificate Digital certificate - £10 Diploma in Mushroom Growing at QLS Level 5 Hard copy certificate - £119 After successfully completing the Diploma in Mushroom Growing at QLS Level 5 course, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme. The certificate will be home-delivered, with a pricing scheme of - 119 GBP inside the UK 129 GBP (including postal fees) for international delivery CPD Accredited Certificate 29 GBP for Printed Hardcopy Certificate inside the UK 39 GBP for Printed Hardcopy Certificate outside the UK (international delivery)
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Management in Industry The Roles of an Owner Characteristics of Management Functions of Management Understanding Organisational Structure The Impact of Organisation Design Module 02: Operations Management The Concept of Product: Goods & Services Operations Management Defined The Operation System The Operations Objectives Factors to Consider Role of Operations Manager Module 03: Introduction to Business Analysis Definition Context Core Concepts Importance Knowledge Area Key Terms Module 04: Strategic Analysis & Product Scope Introduction What Is Strategy? Strategy Development External Environment Analysis Porter's Five Forces Model Internal Environment Analysis Degree of Actual & Potential Competition Competitive Strategy Analysis Achieving & Sustaining Competitive Advantage Module 05: Project Management What is Project Management? Constraints of a Project Project Life Cycle Understanding the Project Life Cycle Module 06: Business Development & Succession Planning Definition Laying the Groundwork to Develop a Business SWOT Analysis Process of Development Succession Planning Understanding the value of Succession Planning Elements of a Succession Plan Module 07: Business Process Management Fundamentals The Vision Phase The Design Phase The Modelling Phase The Execution Phase The Monitoring Phase Module 08: Planning & Forecasting Operations Demand & Forecasting Things to Know About Forecasting Forecasting Methods Aggregate Planning Planning for Product Pricing Relationship of Cost Structure to Pricing Module 09: Performance Management Definition Components The Three Phases of Performance Management Kolb's Learning Cycle Goal-setting Theory of Motivation The Importance of Motivation Module 10: Management of Cash & Credit Cash Management The Need for Cash Cash Budget What Is Cashflow? Cash Flow Problems Remedies for Cash Flow Problems Credit Management Module 11: Managing Risk & Recovery Introduction Planning Identifying Risks Creating Risk Categories Identifying the Project Risks Investigating the Results of Risk Identification Module 12: Quality Management Introduction Quality Policy Determination Benefit/Cost Analysis Preparing for Quality Control Quality Assurance Applying Module 13: Communication Skills Effective Listening Skills Verbal Communication Non-Verbal Communication Communication Strategies Module 14: Business Environment Importance Types of Business Environment Social Responsibility of a Business Ethics Module 15: Organisational Skills Organising Daily Work Organising Workplace Organising Resources Organising Tools Cultivating Organisational Habits Module 16: Negotiation Techniques Basic Types of Negotiations Phases of Negotiation Negotiation Techniques Strategies for Identifying Mutual Gain Effective Negotiation Practise Negotiation on Behalf of Others Module 17: Human Resource Management HRM Models of HRM The Role of the HR Department Aims of HRM HRM & personnel management Module 18: Motivation & Counselling The process of motivation Types of motivation Motivation theory Motivation strategies Module 19: Customer Service Introduction The Power of Positive Thinking in Customer Service Types of Difficult Customers & How to Help them How to Deal with Difficult Customers Aspects of Phone Etiquette Using Proper Phone Language Eliminate Phone Distractions Inbound Calls Outbound Calls Handling Rude or Angry Callers Module 20: Time Management Activities Planning & Prioritising Overcoming Procrastination Crisis Handling Organising Workspace to Make Better Use of Time Planning of Meetings Module 21: Conflict Management Definition of Conflict Benefits of Confrontation Prevention of Conflicts Anger Management Conflict Resolution Techniques CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Business Management Course has been professionally-designed for motivated learners who are looking to add a new skill to their CV and stand head and shoulders above the competition. Learn the latest industry-specific information with the Business Management - Course. Enrol on the Business Management Course and learn a new professional skill from anywhere, at any time! Requirements Enrol on the Business Management Course with no formal entry requirements! If you have a passion for knowledge and want to learn something new, register on the Business Management Course without any delay. We only ask that all students have a passion for learning and literacy, and be over the age of 16. Complete the Business Management Course online from your computer, tablet, or smartphone, and learn in a way that suits you. Career path After completing this Business Management 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. Certificates CPD Accredited Certificate Digital certificate - £10 CPD Accredited Certificate Hard copy certificate - £29 If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.
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(£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 the program in your own time, at your own pace Each of our students gets full 24/7 tutor support *** Course Curriculum *** Medical Sales Representative Course Module 01: Introduction to Pharmacy Pharmacy What is a Profession? The Business of Pharmacy Types of Pharmacy Module 02: History & Development of Pharmacy The Origins of Pharmacy The Organisation of Pharmacy The Professionalisation of Pharmacy Pharmacy in The National Health Service Module 03: The Pharmacy Team Pharmacy Support Team Medicine Counter Assistants Dispensing/Pharmacy Assistants Pharmacy Technician Pharmacist Module 04: Training of the Pharmacy Team Training Needs Analysis Training Methods in the Pharmacy On-the-Job Training Off-the-Job Training Making a Presentation Using Role-Play Module 05: Standards for Pharmacy Professionals The Importance of Having Standards The Standards of Pharmacy Students & Trainees Applying the Standards The Nine Standards Person-Centred Care Work in Partnership Communicate Effectively Maintain, Develop & Use Professional Knowledge & Skills Use Professional Judgement Behave in a Professional Manner Respect & Maintain a Person's Confidentiality & Privacy Speak Up Demonstrate Leadership Module 06: Pharmacy Practice Clinical Pharmacy Practice Medicines Optimisation Pharmaceutical Consultation Clinical Pharmacy Functions & Knowledge Module 07: Health & Safety in the Pharmaceutical Industry Basic Laboratory Safety Health & Safety in the Pharmacy Module 08: Legislation on Public Health and Health Service (Part 1) Public Health Act (Northern Ireland) 1967 Public Health (Control of Disease) Act 1984 Summary Module 09: Legislation on Public Health and Health Service (Part 2) National Health Service Act 2006 Summary Module 10: Legislation on Public Health and Health Service (Part 3) Public Health etc. (Scotland) Act 2008 Summary Module 11: Legislation on Public Health and Health Service (Part 4) Health and Social Care Act 2012 Summary Module 12: Introduction to Sales What is Sales? Basic Rules of Sales Improving Sales Skills Sales Agents Module 13: Sales Growth Getting Personal in Selling Mastering Multichannel Sales Blending Remote Sales and Field Sales Integrating Online and Offline Engaging Customers Early Module 14: Sales and Marketing Marketing's Relationship to Sales Old Rules of Marketing New Rules of Marketing Reaching Buyers Directly Dealing with Customers Building Marketing and PR Plan Module 15: Communication Skills Introduction to Communication Communication Styles The Four-Quadrant System Listening Skills Roles and Situations Affect Communication Styles Strategies for Improving Communications Changing Profiles Module 16: Sales Negotiations What Is Involved in Sales Negotiations? Selling and Negotiating The Basics of Sales Negotiations Principles of Sales Negotiation Stages of Negotiating Negotiating Crimes Effective Sales Negotiators Module 17: Tips and Tricks for Sale Bad Advice on the Internet Using Email for Sales Closing Sales Ideal Selling Process Verifying Information Avoiding Common Mistakes Assessment Process Once you have completed all the modules in the Medical Sales Representative 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. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about the topic is advised to take this course. This course is open to everybody. Requirements You will not need any prior background or expertise to enrol in this course. Career path After completing this course, you are to start your career or begin the next phase of your career. Certificates CPD Accredited Certificate Digital certificate - £10 CPD Accredited Certificate Digital certificate - £29 If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.
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