2416 Courses delivered Online

Overview The growing global health and wellness industry, valued at $4.5 trillion, has witnessed an increased demand for professionals trained in the ancient art and science of baby massage. This course, Baby Massage, is meticulously designed to meet industry demands and equip learners with the knowledge and skills necessary to excel in this rewarding profession. The course curriculum includes Meridian Theory, Pediatric Massage, various massage techniques, acupoints for babies and children, and much more. It comprises modules such as 'Introduction to Pediatric Massage,' 'Meridian Theory Introduction,' and various techniques and protocols in Traditional Chinese Medicine (TCM) Pediatric Massage.Transform your passion into a profession. Enrol now in the Baby Massage course and take the first step towards a fulfilling career in the health and wellness industry. 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 Baby Massage. It is available to all students, of all academic backgrounds. Requirements Our Baby Massage is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 1 sections • 53 lectures • 01:23:00 total length •01 - EAMFC - Baby Massage Marketing final: 00:03:00 •02 - EAMFC - Meridian Theory Introduction 2020: 00:04:00 •03 - EAMFC - Introduction to Pediatric Massage 2020: 00:01:00 •03 - 1 - EAMFC - TCM Paediatric Massage Protocol 2020: 00:01:00 •03 - 2 - EAMFC - Massage For Immunity Strengthening 2020: 00:03:00 •03 - 3 - EAMFC - Massage For Night Sweating 2020: 00:03:00 •03 - 4 - EAMFC - Massage For Stomach-ache 2020: 00:03:00 •03 - 5 - EAMFC - Massage For Constipation 2020: 00:02:00 •03 - 6 - EAMFC - Massage For Sinusitis 2020: 00:03:00 •03 - 7 - EAMFC - Massage for Imsomnia 2020: 00:04:00 •04 - EAMFC - Meridian Flows 2020: 00:07:00 •04 - 1 - EAMFC - Pushing Manipulation Technique 2020: 00:03:00 •04 - 2 - EAMFC - Arc Manipulation Technique 2020: 00:01:00 •04 - 3 - EAMFC - Kneeding Manipulation Technique 2020: 00:02:00 •04 - 4 - EAMFC - Pinching Manipulation Technique 2020: 00:02:00 •04 - 5 - EAMFC - Pressure Manipulation Technique 2020: 00:01:00 •04 - 6 - EAMFC - Rubbing Manipulation Technique 2020: 00:01:00 •04 - 7 - EAMFC - Stroking Manipulation Technique 2020: 00:02:00 •04 - 8 - EAMFC - Wiping Manipulation Technique 2020: 00:01:00 •05 - 0 - EAMFC - Introduction to Baby and Child Acupoints 2020: 00:01:00 •05 - 1 - EAMFC - Da zhui GV14 2020: 00:01:00 •05 - 2 - EAMFC - Lung Shu BL13 2020: 00:01:00 •05 - 3 - EAMFC - Spleen shu BL20 2020: 00:01:00 •05 - 4 - EAMFC - Kidney Shu BL 23 2020: 00:01:00 •05 - 5 - EAMFC - Spinal Column 2020: 00:02:00 •05 - 6 - EAMFC - QI Jie Gu2020 - Copy: 00:01:00 •05 - 7 - EAMFC - Stomach 2020: 00:01:00 •05 - 8 - EAMFC - Shan zhong CV17 2020: 00:01:00 •05 - 9 - EAMFC - Zhongwan CV 12 2020: 00:01:00 •05 - 10 - EAMFC - Tianshu ST 25 2020: 00:01:00 •05 - 11 - EAMFC - Xue hai (Bai chong) SP10 2020: 00:01:00 •05 - 12 - EAMFC - Zu San Li ST 36 2020: 00:01:00 •05 - 13 - EAMFC - San yin jiao SP 6 2020: 00:01:00 •05 - 14 - EAMFC - Yong quan KI 1 2020: 00:01:00 •05 - 15 - EAMFC - Liver Channel 2020: 00:01:00 •05 - 16 - EAMFC - Heart Channel 2020: 00:01:00 •05 - 17 - EAMFC - Spleen Channel 2020: 00:01:00 •05 - 18 - EAMFC - Lung Channel 2020: 00:01:00 •05 - 19 - EAMFC - Kidney Channel 2020: 00:01:00 •05 - 20 - EAMFC - Shen Ding - Tip of Kidney 2020: 00:01:00 •05 - 21 - EAMFC - Large intestine Channel 2020: 00:01:00 •05 - 22 - EAMFC - Ban men 2020: 00:01:00 •05 - 23 - EAMFC - Tianheshui - The Milky Way 2020: 00:01:00 •05 - 24 - EAMFC - Liu Fu - The Six Fu Visceral 2020: 00:01:00 •05 - 25 - EAMFC - Baihui GV 20 2020: 00:01:00 •05 - 26 - EAMFC - Yintang EX HN 3 2020: 00:01:00 •05 - 27 - EAMFC - Kan Gon 020: 00:01:00 •05 - 28 - EAMFC - Tianmen - Heaven Gate 2020: 00:01:00 •05 - 29 - EAMFC - Taiyang 2020: 00:01:00 •05 - 30 - EAMFC - Yingxiang LI 20 2020: 00:01:00 •05 - 31 - EAMFC - Ren zhong - The Philtrum GV 26 2020: 00:01:00 •05 -32 - EAMFC - Stomach Rubbing 2020: 00:01:00 •06 - 1 - EAMFC - Do and Don't 2020: 00:02:00

Overview This comprehensive course on Financial Modelling for Decision Making and Business plan will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Financial Modelling for Decision Making and Business plan comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Financial Modelling for Decision Making and Business plan. It is available to all students, of all academic backgrounds. Requirements Our Financial Modelling for Decision Making and Business plan is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 4 sections • 19 lectures • 03:20:00 total length •Introduction to the course: 00:02:00 •Introducton to the Business Priocess: 00:03:00 •What is Financial Modelling: 00:08:00 •Starting Point of a Financial Model: 00:04:00 •First Steps before Starting to create Financial Model and Linking Business Model: 00:07:00 •Starting with End in Mind-Comparative P&L: 00:13:00 •Customer Acquisition Model: 00:16:00 •Revenue and Cost Models: 00:22:00 •Adding Product and Modelling Labour and Other Costs: 00:21:00 •Modelling Capital Investments and ROI Calc: 00:10:00 •Detailed Customer Acquisition Model and Revenue Model: 00:17:00 •Cost of Sale Model: 00:08:00 •Modelling Labour Cost: 00:07:00 •Modelling Other Operating Expenses: 00:14:00 •Modelling Income Statement and Cash Flows: 00:27:00 •Modelling Balance Sheet: 00:14:00 •Fixing the Error in Financial Model and Brief of RR: 00:07:00 •Financial Model for Business plan for New Business: 00:00:00 •Assignment - Financial Modelling for Decision Making and Business plan: 00:00:00

Overview This comprehensive course on Quality Management and Strategic Training - ISO 9001 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Quality Management and Strategic Training - ISO 9001 comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Quality Management and Strategic Training - ISO 9001. It is available to all students, of all academic backgrounds. Requirements Our Quality Management and Strategic Training - ISO 9001 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 13 sections • 85 lectures • 08:37:00 total length •Course Structure: 00:07:00 •What is Quality: 00:02:00 •What is ISO: 00:08:00 •What is a System - Management System: 00:02:00 •What is Policy - Quality Policy: 00:06:00 •What is Vision, Mission & Strategy: 00:03:00 •QA Vs QC: 00:06:00 •Effectiveness Vs Efficiency: 00:06:00 •Verification Vs Validation: 00:11:00 •Conformity Vs Nonconformity Vs Defect: 00:04:00 •Correction Vs Corrective Action Vs Preventive Action: 00:08:00 •Risk & Preventive Action: 00:06:00 •What is Competence: 00:03:00 •What is the Context of the Organization: 00:05:00 •Who are the Interested parties: 00:03:00 •What are the Needs & expectations: 00:05:00 •Management System Requirements: 00:01:00 •Who is a customer: 00:02:00 •What is Customer Satisfaction: 00:06:00 •Product Vs Service Vs Process: 00:05:00 •Document Vs Record: 00:06:00 •What is Customer Complaint: 00:02:00 •Measuring Vs Monitoring Vs Performance: 00:02:00 •Who is Responsible: 00:12:00 •Responsibility Vs Accountability: 00:02:00 •Quality Management Principles: 00:17:00 •ISO 9001:2015 Core Concepts: 00:08:00 •Major terminology Differences: 00:04:00 •Documented Information: 00:07:00 •Major changes - Organizational Knowledge: 00:05:00 •Major changes - Risk Based Thinking: 00:06:00 •Process Approach Concept-1: 00:04:00 •What is PDCA: 00:05:00 •Process Approach Concept-2: 00:03:00 •Process Approach in ISO 9001:2015: 00:04:00 •Key Benefits: 00:07:00 •PDCA in ISO 9001 2015: 00:10:00 •Understanding the Organization and its Context: 00:08:00 •Internal & External issues: 00:03:00 •SWOT Analysis: 00:06:00 •Interested Parties & their Needs & Expectations: 00:03:00 •KANO Model: 00:10:00 •Understanding the context - Summary: 00:08:00 •Choosing your Strategic Objective: 00:05:00 •Strategic Map Examples-1: 00:03:00 •Strategic Planning Process: 00:06:00 •What is a Vision: 00:06:00 •How to Create a Vision Statement: 00:08:00 •What is a Mission: 00:06:00 •SMART GOAL: 00:06:00 •SMART Goal Example: 00:04:00 •Strategic Map Examples-2: 00:10:00 •Context Chapter Summary: 00:07:00 •Quality Objectives & Planning: 00:05:00 •ISO & SMART: 00:02:00 •Objectives Origin: 00:06:00 •Objectives Examples: 00:07:00 •Goal Vs Objective-1: 00:07:00 •Goal Vs Objective Example: 00:02:00 •Goal Vs Objective-2: 00:10:00 •Performance Evaluation in ISO 9001:2015: 00:10:00 •Customer Satisfaction: 00:06:00 •Analysis & Evaluation: 00:12:00 •Key Performance Indicators: 00:08:00 •Dashboard Examples: 00:07:00 •Management Review Meetings: 00:11:00 •Improvement: 00:16:00 •Nonconformity & Corrective Action: 00:06:00 •Nonconformity & Corrective Action Example: 00:06:00 •Nonconformity & Corrective Action Origin: 00:06:00 •Continual Improvement: 00:01:00 •Analysis Mindset: 00:09:00 •Quantitative Vs Qualitative: 00:16:00 •Now What?: 00:11:00 •Course Summary: 00:10:00 •SIPOC: 00:06:00 •Flowcharts: 00:04:00 •Control Charts: 00:04:00 •Cause and Effect Diagram: 00:06:00 •Pareto Chart: 00:07:00 •5 WHYs: 00:03:00 •Other Tools: 00:08:00 •Finally!: 00:01:00 •Bonus Lecture: 00:02:00 •Assignment - Quality Management and Strategic Training - ISO 9001: 00:00:00

Are you fascinated by risk, probability and financial security? Do you want to dive deep into the world of actuarial science? Our comprehensive course covers everything from basic deterministic models to stochastic life contingencies. You'll gain a thorough understanding of principles of premium calculation, taxation and inflation, and multiple decrement theory. The demand for qualified actuaries is on the rise, as businesses increasingly rely on data-driven insights to make informed decisions. According to the Bureau of Labor Statistics, the employment of actuaries is projected to grow by 18% from 2020 to 2030, much faster than the average for all occupations. The actuarial industry presents a plethora of exciting opportunities for individuals who are passionate about risk management, financial planning, and statistical analysis. As an actuary, you can enjoy a fulfilling career that combines your love for mathematics with your desire to make a positive impact on society. Learning outcomes: Gain a solid understanding of actuarial science principles and concepts Understand the stochastic approach to insurance and annuities Learn to value cash flows and apply probabilistic models Acquire knowledge of life tables, life annuities and life insurance Explore individual risk models and principles of premium calculation Develop skills in multiple decrement theory and profit testing Our Actuary course is designed for those with a keen interest in the theoretical aspects of finance and risk management. You'll learn from industry experts about topics ranging from basic models to complex stochastic approaches. Our course modules provide a comprehensive foundation of actuarial science concepts, including the valuation of cash flows, life tables, life annuities, and life insurance. Through our structured approach, you will learn to apply probabilistic models and gain an understanding of taxation and inflation in the context of actuarial science. Our course content is presented in a concise and easy-to-understand manner, allowing you to build your knowledge gradually and confidently. As an actuary, you can work for insurance companies, consulting firms, government agencies, or financial institutions, depending on your area of interest. You can also specialise in various subfields, such as health insurance, reinsurance, or risk management, and work with clients from diverse industries. So, if you are looking for a challenging and rewarding career that offers ample opportunities for growth and advancement, the actuarial industry may be the perfect fit for you! Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Students with a background in mathematics, statistics, or finance Professionals in the insurance and finance industries looking to expand their knowledge Individuals with a strong interest in actuarial science and financial risk management Anyone seeking a career in actuarial science Career path Actuary (£35,000 - £100,000+) Risk analyst (£20,000 - £60,000) Investment analyst (£25,000 - £65,000) Insurance underwriter (£22,000 - £70,000) Pension scheme actuary (£35,000 - £100,000+) Finance manager (£25,000 - £70,000)

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:04:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:06:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Overview Delve into the world of flowers and their profound language with the 'Floristry Academy Diploma'. This course offers a comprehensive journey through the enchanting universe of floristry, from the basics of flower care to the intricacies of design. Whether you're a budding enthusiast or a fervent flower lover, this curriculum provides the expertise to transform your passion into artistry. As the cycle of life unfolds, flowers stand as timeless witnesses to joy, love, and remembrance. This diploma not only immerses you in the world of floral designs for celebrations and solemn occasions but also imparts the know-how to bloom into a successful career. Learning Outcomes: Understand the fundamentals of floristry, including flower care, treatment, and popular choices. Master the elements and principles of floral design, with an emphasis on arrangement techniques. Develop proficiency in crafting diverse floral compositions including bouquets, corsages, and basket gardens. Gain insights into special occasion floristry, such as weddings and funerals. Acquire the necessary knowledge to either secure a role in the floristry industry or launch your own business. Why buy this Floristry Academy Diploma? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Floristry Academy Diploma there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? Aspiring florists aiming to hone their skills and knowledge. Individuals looking to start their own floristry enterprise. Hobbyists keen to enhance their floral arrangement abilities. Event planners wishing to integrate floristry into their service offerings. Couples or families eager to craft their own floral designs for occasions. Prerequisites This Floristry Academy Diploma does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Floristry Academy Diploma was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Floral Designer: £20,000 - £28,000 per annum Wedding Florist: £22,000 - £30,000 per annum Retail Florist Manager: £23,000 - £31,000 per annum Floral Event Coordinator: £24,000 - £32,000 per annum Floristry Business Owner: £25,000 - £40,000 per annum (varies based on success) Floral Instructor: £21,000 - £27,000 per annum Course Curriculum Floristry Academy Diploma Introduction to Floristry 00:21:00 Services Provided by Florists 00:21:00 Flowers and Plants 01:08:00 Flower Care and Treatment 00:36:00 Choosing Popular Flowers and Fillers 00:54:00 Elements and Principles of Design 00:54:00 How to Make Floral Arrangements 01:04:00 Making Bouquet, Corsage, Fruit Basket & Basket Garden 00:35:00 Wedding Floristry 00:10:00 Making Funeral Flower Arrangements 00:31:00 Beautiful Floral Designs 00:45:00 Getting a Job in the Floristry Industry 00:30:00 Starting Your Own Floristry Business 00:54:00 Assignment Assignment - Floristry Academy Diploma 00:00:00

Overview Get started in setting up your own floristry business and learn the art of flower arranging with this floristry masterclass! In the Floristry & Plant Care Training, you will learn how to create stunning floral displays for special occasions such as weddings and festive holidays. You will also deepen your knowledge of the role of the florist as well as the fundamental elements and principles of floral design. Take your first steps towards a career in the floral industry and learn how to create stunning floral bouquets, displays, and more, with this introductory training course! Why buy this Floristry & Plant Care Training? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Floristry & Plant Care Training you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Floristry & Plant Care Training does not require you to have any prior qualifications or experience. You can just enrol and start learning.  Prerequisites This Floristry & Plant Care Training was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Floristry & Plant Care Training is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Floristry & Plant Care Training Module 01: Introduction to Floristry 00:15:00 Module 02: The Florist 00:30:00 Module 03: Flower Colors & Symbolism 00:30:00 Module 04: Different Flowers and Their Meaning 01:00:00 Module 05: Potted Plant Care 00:30:00 Module 06: Cut Flowers 01:00:00 Module 07: Plant Diseases 01:00:00 Module 08: Common Cultural Disorders 00:30:00 Module 09: Insects and Pests of Roses 00:30:00 Module 10: Garden Care to Prevent Diseases 01:00:00 Module 11: Principles of Floral Arrangement 01:00:00 Module 12: Floral Design 01:00:00 Module 13: Types of Greenery 01:00:00 Module 14: Role of Foliage in Arrangements 00:15:00 Module 15: Popular Styles and Arrangements 01:00:00 Module 16: Making Floral Arrangements 00:30:00 Module 17: Container Preparation 00:30:00 Module 18: Corsage & Boutonniere 00:30:00 Module 19: Wedding Bouquet 00:15:00 Module 20: Funeral Flowers & Meanings 00:15:00 Module 21: Funeral Wreath 00:15:00 Module 22: Surviving in Florist Sector 00:15:00 Mock Exam Mock Exam - Diploma in Floristry and Flower Arrangement Training Courses 00:20:00 Final Exam Final Exam - Diploma in Floristry and Flower Arrangement Training Courses 00:20:00

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