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This Course at a Glance Identify the elements of the scoring system used to determine the food hygiene rating Understand how the food hygiene rating system is structured with the distribution of scores between hygiene, structure and confidence Understand what each score means and indicates about the food hygiene standard Define the scoring criteria and understand how the decision on the final scorecard is assessed Understand the process relating to the appeal of scorecards if you are unsatisfied with your rating Understand how to incorporate Safer Food, Better Business (SFBB) to ensure your business complies with the legal obligations Identify the types of E. coli bacteria and know how to control and prevent E. coli cross-contamination in food by following proper food hygiene and safety Acquire knowledge about the underpinning food hygiene principles that ensure food hygiene and safety Learn to implement effective hygiene and cleaning structure for your business that prevents cross-contamination Achieving 5*( 5 star) Food Hygiene Rating | Online Course Overview Maintaining a proper food hygiene regimen is a legal duty enumerated by several UK and EU laws and legislations. A higher food hygiene rating exhibits your concern for the health and well-being of your consumers and gives them an incentive that your business complies with a certain level of standard in ensuring the quality of food. The higher your rating, the more trust your consumers put in your business. The NFU Mutual Food Hygiene Ratings Report found that 44% of people would turn away from a food establishment if it displayed a rating of 4 or less. Therefore, maintaining a good rating is an important aspect of protecting both your business and brand identity. This course complies with the latest UK and EU laws, rules and regulations to ensure that you can comply with the provisions while maintaining food hygiene and safety practices that satisfy your role. This Achieving 5*( 5 star) food hygiene rating | Online Course is designed to give you a concise insight into the process of the National Food Hygiene Rating Scheme. It solely intends to provide you with an overview of the scoring criteria and how the scores are evaluated by the inspectors. It also gives a clear view of the appeals process, the Safer Food Better Business management system and E-Coli and provides a well-rounded procedure for maintaining the premises with proper hygiene structure and cleaning. A 5-star rating will always be hard to achieve for your business if your employees are not trained properly on how to maintain proper food hygiene and safety. Moreover, a food business with a comparatively low rating is more prone to being frequently examined or inspected. Therefore, training your employees on achieving a 5-star rating will ensure they are equipped with the knowledge of maintaining proper food hygiene and safety through the appropriate use of chemicals, pesticides and other safety procedures. Upon successful completion of this Achieving 5*( 5 star) food hygiene rating | Online Course, you will be able to design and assess sustainable hygiene and cleaning structure for your business that will boost your food hygiene rating. Who should take this course? This Achieving 5*( 5 star) food hygiene rating | Online Course is suitable for anyone associated with the field of food manufacturing, catering or retail industry working in the capacity of: Supervisor Manager Waiter Barista Chef Whether you are looking to gain extensive knowledge about maintaining food hygiene and safety to achieve a 5-star rating for your business as the owner or an employee looking to gain comprehensive knowledge on achieving a high standard of food hygiene in the workplace, this Achieving 5*( 5 star) food hygiene rating | Online Course will set you up with the appropriate credentials to comply with a certain level of food hygiene and safety standards ascertained by the Food Standards Agency. Entry Requirements There are no academic entry requirements for this Achieving 5*( 5 star) Food Hygiene Rating | Online Course, and it is open to students of all academic backgrounds. However, you are required to have a laptop/desktop/tablet or smartphone and a good internet connection. Assessment Method This Achieving 5*( 5 star) food hygiene rating | Online Course assesses learners through multiple-choice questions (MCQs). Upon successful completion of each module, learners must answer MCQs to step into the next module. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 75%. Course Curriculum Module 1: Food Hygiene Ratings - An Introduction Module 2: Scoring Criteria Module 3: Appeals Module 4: Safer Food Better Business (SFBB) Module 5: E.Coli Module 6: Good Hygiene Structure and Cleaning Recognised Accreditation CPD Certification Service 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. CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field. Quality Licence Scheme Endorsed 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. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees.     Certificate of Achievement Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. 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. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35. FAQs Is CPD a recognised qualification in the UK? CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD-certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Are QLS courses recognised? Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards. When will I receive my certificate? For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days. Can I pay by invoice? Yes, you can pay via Invoice or Purchase Order, please contact us at info@lead-academy.org for invoice payment. Can I pay via instalment? Yes, you can pay via instalments at checkout. How to take online classes from home? Our platform provides easy and comfortable access for all learners; all you need is a stable internet connection and a device such as a laptop, desktop PC, tablet, or mobile phone. The learning site is accessible 24/7, allowing you to take the course at your own pace while relaxing in the privacy of your home or workplace. Does age matter in online learning? No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learner's ability to learn new things, diversify their skills, and expand their horizons. When I will get the login details for my course? After successfully purchasing the course, you will receive an email within 24 hours with the login details of your course. Kindly check your inbox, junk or spam folder, or you can contact our client success team via info@lead-academy.org

Description: If you are working in company related to wireless technology, the course is the best solution for you. The course illustrates the fundamentals and essentials functions of wireless network technology and helps you to embrace the system efficiently. The course is sectioned into two parts - one is network administration, and another one is about network security. Both the sections help you to achieve a strong command over the technology. The basic concept of Radio Frequency (RF), WLAN security system, Legal system, Encryption Cipers and methods will be discussed in the Wireless Security Professional section. On the other hand, you gain a crystal clear knowledge about Wi-Fi access, MAC, WLAN, troubleshooting in the Network Administration part. The purpose of the bundled course is to help you to accustom with the troubleshooting process and network configuration process of Wireless technology. The course helps you to handle WLAN network securely. Assessment: At the end of the course, you will be required to sit for an online MCQ test. Your test will be assessed automatically and immediately. You will instantly know whether you have been successful or not. Before sitting for your final exam you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Certified Wireless Network Administrator (CWNA) - Complete Video Course is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Certified Wireless Network Administrator (CWNA) - Complete Video Course is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Overview of Wireless Communications Overview of Wireless Communications FREE 00:23:00 Communication Fundamentals 00:15:00 Fundamentals of RF Fundamentals of RF 00:07:00 Characteristics of RF 00:17:00 RF Behaviors 00:17:00 Components and Measurements of RF Components and Measurements of RF 00:19:00 dB Mathematics 00:18:00 Math Examples (eNotes) 00:20:00 Noise Floor 00:07:00 RF Signal and Antenna Concepts RF Signal and Antenna Concepts 00:13:00 Antenna Types 00:15:00 Beamforming 00:09:00 IEEE 802.11 IEEE 802.11 00:15:00 802.11i 00:10:00 Spread Spectrum Technologies Course Overview Direct Sequence Spread Spectrum (Part 1) 00:22:00 Direct Sequence Spread Spectrum (Part 2) 00:21:00 WLAN Topologies WLAN Topologies 00:10:00 Distribution Service 00:08:00 Mesh BSS 00:15:00 Wi-Fi Access Wi-Fi Access 00:14:00 Interframe Space (IFS) 00:13:00 MAC Architecture MAC Architecture 00:18:00 Beacon Frames 00:11:00 WLAN Architecture WLAN Architecture 00:17:00 WLAN Controller 00:11:00 WLAN Deployment WLAN Deployment 00:10:00 Network Extension to Remote Areas 00:13:00 Troubleshooting Troubleshooting 00:18:00 802.11 Coverage Considerations 00:17:00 Capacity vs. Coverage 00:19:00 Security Security 00:22:00 Robust Security 00:24:00 Types of Wireless Attacks Types of Wireless Attacks 00:30:00 Intrusion Monitoring 00:08:00 Fundamentals of Site Surveys Fundamentals of Site Surveys 00:16:00 Site Survey Tools Site Survey Tools 00:05:00 Site Survey 00:15:00 PoE PoE 00:09:00 Midspan 00:08:00 High Throughput (HT) High Throughput (HT) 00:11:00 Spatial Multiplexing (SM) 00:12:00 Very High Throughput (HT) Very High Throughput (VHT) 00:18:00 BYOD BYOD 00:19:00 Over the Air Management 00:10:00 WLAN Security Overview WLAN Security Overview and Data Privacy 00:58:00 Networking Basics 00:04:00 Web GUI Introduction 00:05:00 Security Options 00:03:00 Legacy Security Legacy Security 00:32:00 VPNs 00:21:00 Security Association 00:09:00 MAC Spoofing 00:07:00 Encryption Ciphers and Methods Encryption Ciphers and Methods 00:19:00 TKIP 00:26:00 CCMP 00:20:00 Encryption Examples 00:06:00 802.11 Authentication Methods 802.11 Authentication Methods 00:26:00 802.1X 00:20:00 EAP 00:25:00 Certified Authority Server Credentials 00:06:00 Dynamic Encryption Key Generation Dynamic Encryption Key Generation 00:21:00 Authentication and Key Management 00:13:00 RSNA Key Hierarchy 00:12:00 EAP 00:05:00 Information Elements 00:06:00 SOHO 802.11 Security SOHO 802.11 Security 00:26:00 Cracking Hashes 00:09:00 Cracking Hashes 00:09:00 Fast Secure Roaming Fast Secure Roaming 00:24:00 PMKSA 00:29:00 FT Key Hierarchy (e-notes) 00:30:00 802.11K-2008 00:28:00 Wireless Security Risks Wireless Security Risks 00:22:00 Authentication Attacks 00:20:00 Rogue Devices 00:04:00 Public Hotspots 00:06:00 Wireless LAN Security Auditing Wireless LAN Security Auditing 00:28:00 Wireless Security Monitoring Wireless Security Monitoring 00:21:00 Device Tracking 00:17:00 VPNs, Remote Access and Guest Access Services VPNs, Remote Access and Guest Access Services 00:23:00 Remote Access 00:14:00 WLAN Security Infrastructure WLAN Security Infrastructure 00:37:00 Management Protocols 00:23:00 Other RADIUS Solutions 00:15:00 Wireless Security Policies Wireless Security Policies 00:17:00 Other Policies 00:14:00 Order Your Certificates and Transcripts Order Your Certificates and Transcripts 00:00:00

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

Explore the intricacies of partnership accounting with our comprehensive course, covering essential practices and principles. Learn about partnership agreements, capital accounts, income allocation, financial statements, taxation basics, and more. Gain practical insights and skills to navigate partnership structures and financial management effectively. Enroll now!

This course covers the important topics needed to pass the AWS Certified Data Analytics-Specialty exam (AWS DAS-C01). You will learn about Kinesis, EMR, DynamoDB, and Redshift, and get ready for the exam by working through quizzes, exercises, and practice exams, along with exploring essential tips and techniques.

Overview This Marketing Principles course will unlock your full potential and will show you how to excel in a career in Marketing Principles. So upskill now and reach your full potential. Everything you need to get started in Marketing Principles is available in this course. Learning and progressing are the hallmarks of personal development. This Marketing Principles will quickly teach you the must-have skills needed to start in the relevant industry. In This Marketing Principles Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Marketing Principles skills to help you advance your career. Acquire a comprehensive understanding of various Marketing Principles topics and tips from industry experts. Learn in-demand Marketing Principles skills that are in high demand among UK employers, which will help you to kickstart your career. This Marketing Principles course covers everything you must know to stand against the tough competition in the Marketing Principles field.  The future is truly yours to seize with this Marketing Principles. Enrol today and complete the course to achieve a Marketing Principles certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Marketing Principles course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Marketing Principles course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Marketing Principles course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Marketing Principles is suitable for anyone aspiring to start a career in Marketing Principles; even if you are new to this and have no prior knowledge on Marketing Principles, this course is going to be very easy for you to understand.  And if you are already working in the Marketing Principles field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Marketing Principles course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Marketing Principles course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Marketing Principles course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Marketing Principles course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Section 01: Marketing and the Firm Marketing and the Firm 00:01:00 Marketing Orientation and Context 00:01:00 Creating Value and Competitive Advantage #1 00:01:00 Creating Value and Competitive Advantage #2 00:01:00 Marketing Definition 00:01:00 Marketing Exchange 00:01:00 Marketing Interactions #1 00:01:00 Marketing Interactions #2 00:02:00 BCG's Advantage Matrix Model 00:01:00 Section 02: Situational Marketing Analysis External Environment - Analysis #1 00:01:00 External Environment - Analysis #2 00:01:00 External Environment - Analysis #3 00:01:00 External Forces Facing Marketing 00:01:00 Demographic Shift 00:01:00 Demographic Changes 00:02:00 Stakeholder Mapping #1 00:01:00 Stakeholder Mapping #2 00:01:00 Section 03: Microenvironments - Industry and Market Microenvironments - Industry and Market 00:01:00 Difference between an Industry and a Sector 00:02:00 Common Mistakes #1 00:02:00 Common Mistakes #2 00:01:00 Market Analysis #1 00:01:00 Market Analysis #2 00:01:00 Internal Firm Analysis and Environment Analysis 00:02:00 Enterprise Value Chain Analysis #1 00:01:00 Enterprise Value Chain Analysis #2 00:01:00 Enterprise Value Chain Analysis #3 00:01:00 Porter's Value Chain 00:01:00 Elements in Porter's Value Chain #1 00:01:00 Elements in Porter's Value Chain #2 00:01:00 SWOT - Gap Analysis 00:02:00 TOWS and Building Conversion Strategies 00:01:00 Section 04: Formulating a Marketing Plan - Building Components Formulating a Marketing Plan - Building Components #1 00:01:00 Formulating a Marketing Plan - Building Components #2 00:02:00 Formulating a Marketing Plan - Building Components #3 00:01:00 Product Life Cycle and Building a Product Strategy 00:01:00 Segmentation and Targeting- Geography, Consumer Behaviour and Cultures 00:01:00 Positioning Your Market Offering 00:01:00 Pricing Your Product for the Market 00:01:00 Channels and Distribution 00:01:00 Promotion and Brand Advertising 00:01:00 Business Development and Customer Relationship Marketing (CRM) 00:01:00 Hard-selling 00:01:00 Sales Funnel 00:01:00 Stages in the Sales Funnel 00:02:00 Section 05: Executing the Marketing Plan Action Planning, Roles and Responsibilities 00:01:00 Metrics and Measures 00:02:00 Marketing and Information Technology 00:01:00 Marketing Information (MIS) Systems: Sorting Data and Reporting 00:02:00 Marketing and Information Technology 00:01:00 The Marketing Profession and Building the Marketing Team 00:01:00

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 Course Overview Course Overview Video 00:05:00 Building Your Virtual Lab Environment Downloading ISO and OVA Fles for VirtualBox 00:08:00 Create Virtual Install of Server 2016 Full GUI Using VirtualBox 00:12:00 Video and Lab - Creating a Virtual Install of Server 2016 Core Using VirtualBox 00:11:00 Video and Lab - Creating a Virtual Install Of Windows 10 Pro Using Virtualbox 00:16:00 Take a Snapshot of Your Current Configuration 00:04:00 Building a Microsoft Server 2016 Domain Preparing Your Network for Active Directory 00:09:00 Prepare Server 2016 for Promotion to a Domain Controller 00:09:00 Video and Lab - Promote Server 2016 to a Domain Controller 00:09:00 Join Server 2016 Core to Windows 2016 Domain 00:08:00 Promote Server Core to a Domain Controller 00:14:00 Add a Windows 10 Workstation to a Microsoft Domain 00:15:00 Create a Server 2016 Replica Domain Controller 00:13:00 Domain Naming System (DNS) Installing the DNS Role Using Server Manager 00:05:00 Create a Secondary or Backup DNS Server 00:07:00 Create a Secondary or Backup DNS Server Using Server Core 00:08:00 Create a DNS Reverse lookup Zone in Server 2016 00:02:00 Create a New DNS Host Record 00:01:00 Create a New MX record in DNS 00:04:00 Dynamic Host Configuration Protocol (DHCP) Install and Configure DHCP Using PowerShell 00:08:00 Authorize a Windows 2016 DHCP Server 00:03:00 Server and Scope Options in Windows Server 2016 00:03:00 How to Edit the Default Gateway Settings in DHCP 00:02:00 How to Edit DNS Server List in DHCP 00:03:00 Use Filters in DHCP to Deny Clients DHCP Services 00:02:00 Use DHCP User Classes to assign alternate scope options 00:05:00 Edit a DHCP Scope 00:02:00 How to Backup and Restore the DHCP Database 00:03:00 Create Predefined Options in DHCP 00:06:00 Speed Learning Active Directory Administration Create a User in Active Directory 00:01:00 Create an Administrator User in Server 2016 00:04:00 Create a Distribution Group in Active Directory 00:02:00 Create and Use a Security Group 00:03:00 Create an Organizational Unit 00:02:00 Unlock a User account 00:01:00 Move an Object to a New Organizational Unit in Active Directory 00:02:00 Change the Domain Administrator Password 00:01:00 Fix Access Denied When deleting Active Directory objects 00:01:00 Speed Learning Group Policy Prevent Automatic Logoff Due to Inactivity 00:03:00 Create and Link a Group Policy Object to an OU 00:04:00 Edit Group Policy Objects to Affect a User 00:03:00 Edit a Group Policy Object to Affect a Computer 00:03:00 Backup and Restore Group Policy Objects 00:03:00 Force Screensaver and Timeouts Using Group Policy 00:06:00 Change Users Desktop Background Using Group Policy 00:09:00 Speed Learning Server 2016 Administration Overview of the New Start Menu for Server 2016 00:02:00 Working with Task View in Server 2016 00:02:00 Enable Remote Desktop Using PowerShell 00:10:00 Rearm the 180-day Evaluation Period for Wndows Server 00:02:00 Rearm the 30-day Evaluation Period for Windows 10 00:03:00 Create a Heads-up Display Using BgInfo 00:08:00 Change the Date, Time and Numbers Format in Server 2016. 00:02:00 Rename Windows Server 2016 Using PowerShell 00:02:00 Manage Files and Shares Setup Work Folders in a Windows Domain 00:15:00 Configure a Distributed File System Using Windows Server 00:16:00 Create a Shared Folder on a Windows Server 00:04:00 Create a Shared Folder Using Server Manager 00:06:00 Speed Learning Managing Printers Add a Network Printer in Windows Server 2016 00:04:00 Install and Use the Print Management role in Windows Server 2016 00:04:00 Deploy Printers Using Group Policy in Windows Server 2016 00:03:00 Speed Learning Server 2016 Firewall Turn the Firewall on or off in Windows 2016 Server 00:01:00 Allow an Inbound Port Through a Windows Firewall 00:02:00 Enable PING for Server 2016 and Windows 10 00:04:00 Using Netsh to Manage the Windows Firewall 00:04:00 Using Powershell to Gather Firewall Information 00:04:00 Disk Management Adding Additional Hard Disks Using VirtualBox 00:06:00 Shrink or Extend a Volume in Windows Server 00:04:00 Format a Volume with ReFS in Windows Server 00:03:00 Format a Volume With FAT32 in Windows Server 00:02:00 Troubleshooting NSLookup 00:05:00 Troubleshooting Internet Connectivity 00:16:00 Overview of Windows Sysinternal Tools 00:08:00 Overview of Sysinternal's Process Explorer 00:17:00 Obtain Your Certificate Order Your 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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Overview This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis 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 Python for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis 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 19 sections • 99 lectures • 00:08:00 total length •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 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 •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 •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 •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 •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 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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- Python for Data Analysis: 00:00:00