371 Forest courses

Are you struggling to have your kids eat what you think they should eat? Or do you want to help YOUR children to stay fit by having a healthy diet and maintain nutrition for their bodies? Our diploma in healthy diet weight loss for kids is designed to arm you with the most powerful weapon of all, knowledge, which when used correctly can and will combat the threat of childhood malnutrition and help to ensure the well-being of the youth of today. It will provide you with the right information and strategies on what, when and how to eat healthy and nutritious food. This comprehensive course is available to anyone wishing to learn more about child nutrition, health and well-being from either a personal and professional perspective so enrol now and benefit from this course. COURSE HIGHLIGHTS Accredited Diploma in Healthy Diet & Weight Loss for Kids is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Accredited Diploma in Healthy Diet & Weight Loss for Kids into 14 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 8 hours, 10 minutes and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. WHY YOU SHOULD CHOOSE ACCREDITED DIPLOMA IN HEALTHY DIET & WEIGHT LOSS FOR KIDS * Lifetime access to the course * No hidden fees or exam charges * CPD Accredited certification on successful completion * Full Tutor support on weekdays (Monday - Friday) * Efficient exam system, assessment and instant results * Download Printable PDF certificate immediately after completion * Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. * Improve your chance of gaining professional skills and better earning potential. WHO IS THIS COURSE FOR? Accredited Diploma in Healthy Diet & Weight Loss for Kids is CPD certified and IAO accredited. 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 backgrounds. REQUIREMENTS Our Accredited Diploma in Healthy Diet & Weight Loss for Kids 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 You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Obesity in Children Is Growing At A Frightening Fast Rate 00:30:00 The Most Powerful Breakfast for Weight Loss 00:30:00 Overweight Is Injurious To Teens and Kids 01:00:00 Obesity in Teenagers and Children Can Be the Saddest Sights 00:30:00 Tips to Help Your Child Fight Against Childhood Obesity 00:30:00 A Chapter for Your Teen - Top Tips For Weight Loss for Teens 00:30:00 A Chapter for Parents - Discover Safe and Easy Weight Loss for Teens 00:30:00 A Weight Loss Plan That Is Fun to Implement 00:30:00 Emphasis on Being Thin For Teen Girls Makes Weight Loss a Major Issue 00:30:00 Some Diet Plans for Overweight Teenage Boys 00:30:00 Snack Ideas for Kids That Won't Wreck *Mom's* Diet! 00:30:00 Biking - A Great Way to Enjoy Your Exercise 00:30:00 Exercise Anywhere With Your Bicycle - From Beaches to Mountains to Forests 00:30:00 Weight Control with Bowling Anyone? 00:30:00 Mock Exam Mock Exam- Accredited Diploma in Healthy Diet & Weight Loss for Kids 00:20:00 Final Exam Final Exam- Accredited Diploma in Healthy Diet & Weight Loss for Kids 00:20:00

DESCRIPTION: Windows Server 2016 is a server operating system that is designed to handle corporate networking, Internet/intranet hosting, databases, enterprise-scale messaging and similar functions more efficiently. Developed by Microsoft, it is a part of the Windows NT family of operating systems. With the proper knowledge of Windows Server 2016, you can able to handle your office environment proficiently. The Windows Server 2016 Complete Video Training course is for you if you want to master the features and functions of Windows Server 2016. Apart from this, the bundled video course will help you to prepare for the various exam of Microsoft Windows Server 2016 MCSA certification. The course is divided into four sections where each section helps you with a specific exam and the practical use of Windows Server. The 70-740 Exam section teaches you the methods of installing Windows Server in Host and Compute Environments along with the other features such as storage. On the other hand, the 70-741 series teaches you how to do networking with Windows server including implementing Domain Name system, etc. Next, you will learn about the functionality of Windows Server in the 70-742 section that focuses on the Web Application proxy implementations, Microsoft Azure AD and Directory Synchronization, etc. Finally, in the 70-744 part, you will know how to secure your Windows server. In short, the Windows Server 2016 Complete Video Training course helps you to understand all the necessary information skills if you want to use Windows Server 2016. 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? Windows Server 2016 Complete Video Training 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 Windows Server 2016 Complete Video Training 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. Installing Windows Servers in Host and Computer Environments Determining Windows Server 2016 Installation FREE 00:54:00 Installing Windows Server 2016 Core and Nano Editions 01:35:00 Managing Windows Installations with Windows PowerShell 00:01:00 Create, Manage, and Maintain Windows Images to Deploy 00:33:00 Implementing Local and Enterprise Storage Solutions Managing Disks and Volumes in Windows Server 2016 01:00:00 Implementing and Managing Storage Spaces 00:45:00 Configuring Data Deduplication 00:39:00 Understanding Various Types of Storage 00:15:00 Fibre Channel, iSCSI, and Fibre Channel over Ethernet 00:18:00 Understanding iSNS, DCB, and MPIO 00:09:00 Configuring File and Folder Sharing in Windows Server 2016 00:21:00 Implementing Hyper-V Virtualization Installing Hyper-V Virtualization 00:26:00 Configuring Storage and Networking on Hyper-V Hosts 00:38:00 Configuring and Managing Virtual Machines 00:34:00 Implementing Windows Containers Understanding Windows Server and Hyper-V Containers 00:17:00 Deploying Windows Server and Hyper-V Containers 00:08:00 Using Docker to Install, Configure, and Manage Containers 00:12:00 Implementing High Availability Overview of High Availability and Disaster Recovery 00:55:00 Implementing Network Load Balancing 00:25:00 Planning and Configuring Failover Clustering 01:10:00 Maintaining a Failover Cluster 00:15:00 Troubleshooting Failover Clustering 00:11:00 Integrating Failover Clustering and Hyper-V 00:23:00 Configuring Site Availability 00:12:00 Maintaining and Monitoring Server Environments Windows Server Update Services 00:33:00 Windows PowerShell Desired State Configuration (DSC) 00:10:00 Windows Server 2016 Monitoring Tools 00:43:00 Plan and Implement IPv4 and IPv6 Networks Plan and Implement IP Addressing Schemes for IPv4 Networks FREE 01:31:00 Configuring IPv4 Hosts 00:18:00 Managing and Troubleshooting IPv4 Connectivity 00:35:00 Implementing IPv6 for Network Hosts 00:20:00 Implementing IPv6 Transitioning and Coexistence 00:16:00 Installing and Configuring DHCP Overview of the DHCP Server Role 00:16:00 Managing and Troubleshooting DHCP 00:48:00 Installing and Configuring DNS Implementing DNS Servers 00:27:00 Creating and Configuring DNS Zones 00:52:00 Understanding Active Directory Integration 00:23:00 Configuring Advanced DNS Settings 00:41:00 Implementing and Managing IP Address Management Overview of IPAM 00:15:00 IPAM Deployment 00:49:00 Implementing Remote Access Remote Access Overview 00:27:00 Implementing the Web Application Proxy 00:08:00 Planning and Implementing VPNs 00:31:00 Overview of DirectAccess 00:21:00 Implementing DirectAccess 00:27:00 Installing and Configuring Branch Office Networking Configuring Networking for Branch Offices 00:39:00 Implementing Distributed File Systems 00:44:00 Implementing BranchCache 00:19:00 Implementing Advanced Networking Features Implementing Networking Features for High Performance 00:23:00 Implementing Hyper-V Advanced Networking Features 00:13:00 Introduction to Software-Defined Networking 00:10:00 Overview of Network Virtualization 00:06:00 Installing and Configuring Domain Controllers Overview of Active Directory Domain Services FREE 01:00:00 Overview of Domain Controllers 00:30:00 Deploying Domain Controllers 1 01:00:00 Managing Active Directory Objects Overview of AD DS Object Management 00:23:00 Managing User Accounts 01:07:00 Managing Groups 01:06:00 Managing Computer Accounts 00:20:00 Managing Organizational Units 00:41:00 Securing Active Directory Domain Services Securing Domain Controllers 00:33:00 Implementing Account Security 00:48:00 Auditing AD DS 00:26:00 Configuring Managed Service Accounts 00:14:00 Working with Complex AD DS Infrastructures Overview of Advanced AD DS Deployments 00:20:00 Deploying a Distributed AD DS Environment 00:45:00 Overview of AD DS Replication 00:12:00 Configuring AD DS Sites 00:38:00 Implementing Group Policy Overview of Group Policy 00:39:00 Creating and Configuring GPOs 00:56:00 Monitoring and Troubleshooting Group Policy 00:18:00 Security Management Using Group Policy 00:54:00 Managing User Environments 00:22:00 Understanding Microsoft Azure AD and Directory Synchronization Planning Directory Synchronization 00:24:00 Implementing Azure AD Connect 00:12:00 Managing Identities with Directory Synchronization 00:14:00 Monitoring and Recovering AD DS Monitoring AD DS 00:27:00 Database Management 00:07:00 Backup and Recovery in AD DS 00:21:00 Implementing Active Directory Certificate Services Overview of Public Key Infrastructure and AD CS 00:17:00 Deploying Certificate Authority Hierarchy 00:19:00 Administering Certificate Authorities 00:13:00 Deploying and Managing Certificates 00:26:00 Managing Revocation and Distribution 00:07:00 Configuring Certificate Recovery 00:08:00 Implementing Active Directory Federation Services (AD FS) Overview of AD FS 00:17:00 Planning and Deploying AD FS 00:35:00 Overview of Web Application Proxy 00:08:00 Implementing Active Directory Rights Management Services Overview of AD RMS 00:14:00 Deploying AD RMS 00:14:00 Protecting Content with AD RMS 00:09:00 Introduction to Attacks, Breaches, and Detection Understanding Types of Attacks FREE 00:33:00 Detecting Security Breaches 00:06:00 Using Sysinternals Tools 00:30:00 Protecting Users and Workstations User Rights and Privileges 01:28:00 Working with Computer and Service Accounts 00:19:00 Protecting User Credentials 00:20:00 Using Privileged Access Workstations 00:12:00 Managing Administrative Access Understanding and Deploying JEA 00:32:00 Using Enhanced Security Administrative Environments (ESAE) Forests 00:12:00 Using Microsoft Identity Manager 00:08:00 Using JIT Administration and PAM 00:16:00 Configuring Anti-Malware and Patch Management Configuring and Managing Windows Defender 00:18:00 Restricting Software 00:28:00 Using Device Guard 00:12:00 Patch Management with WSUS 00:29:00 Auditing and Advanced Threat Analytics Configuring Auditing for Windows Server 2016 00:21:00 Advanced Auditing and Management 00:42:00 Deploying and Configuring ATA 00:15:00 Deploying and Configuring Operations Management Suite 00:07:00 Securing the Infrastructure Secure the Virtualization Infrastructure 00:15:00 Deploying Security Baselines 00:20:00 Deploying Nano Server 00:08:00 Configuring Data Protection Planning and Implementing File Encryption 00:29:00 Planning and Implementing BitLocker 00:32:00 Advanced File Server Management Using File Server Resource Manager 00:58:00 Implementing Classification and File Management Tasks 00:16:00 Working with Dynamic Access Control 00:39:00 Securing the Network Infrastructure Using the Windows Firewall with Advanced Security 00:33:00 Datacenter Firewall 00:08:00 Utilizing IP Security 00:29:00 Configuring Advanced DNS Settings 00:42:00 Monitoring Network Traffic 00:09:00 Securing SMB Traffic 00:07:00 Order Your Certificates and Transcripts Order Your Certificates and Transcripts 00:00:00

Weight loss in medical and health context is the reduction of the total body mass because of the loss of fluid or lean mass. Weight loss is not just losing of weight but you have to consider ways of doing it. If you are someone who is into wellness, learning about weight loss management will be advantageous to you and your career. You will learn about weight loss management, wellness and fitness, and weight loss for adults and children through this course. This will help you learn the advanced methods and its possible effects for a healthier health loss program. You will learn the necessary skills, knowledge and information of weight loss programme.  COURSE HIGHLIGHTS Weight Loss Course for Nutritionist is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Weight Loss Course for Nutritionist into 88 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 2 days, 1 hour hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. WHY YOU SHOULD CHOOSE WEIGHT LOSS COURSE FOR NUTRITIONIST * Lifetime access to the course * No hidden fees or exam charges * CPD Accredited certification on successful completion * Full Tutor support on weekdays (Monday - Friday) * Efficient exam system, assessment and instant results * Download Printable PDF certificate immediately after completion * Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. * Improve your chance of gaining professional skills and better earning potential. WHO IS THIS COURSE FOR? Weight Loss Course for Nutritionist is CPD certified and IAO accredited. 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 backgrounds. REQUIREMENTS Our Weight Loss Course for Nutritionist 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 You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Weight Loss Management Introduction 00:30:00 Why Do You Want To Lose Weight? 01:00:00 Does Your Weight Have an Emotional Control Over You? 01:00:00 How Did You Get Here? 00:30:00 Why We Eat 00:30:00 The Diets That Lead Us Here 00:30:00 Fad Diets 01:00:00 Factors Affecting How We Lose Weight 01:00:00 How To Dump The Weight For Good This Time 00:30:00 Inches or Pounds? 00:30:00 Starting Point - The Importance Of A Goal 01:00:00 Watching What You Eat - Keeping Tabs On Those Calories What Exactly Is a Calorie? 01:00:00 Good Fat vs. Bad Fat 00:30:00 Simple Carbohydrates 00:30:00 Complex Carbohydrates 00:30:00 We Have All Of This Knowledge - Now What? 00:30:00 Getting Physical 01:00:00 Exercise And Its Far Reaching Benefits 01:00:00 Finding an exercise program that is right for you 01:00:00 Your Personal Weight Loss Plan 00:30:00 Exercise As Part Of Your Weight Loss Plan 00:30:00 Eating Plan 00:30:00 To achieve your weight loss goal 00:30:00 Conclusion 00:15:00 Weight Loss for Kids Obesity in Children Is Growing At A Frightening Fast Rate 00:30:00 The Most Powerful Breakfast for Weight Loss 00:30:00 Overweight Is Injurious To Teens and Kids 01:00:00 Obesity in Teenagers and Children Can Be the Saddest Sights 00:30:00 Tips to Help Your Child Fight Against Childhood Obesity 00:30:00 A Chapter for Your Teen - Top Tips For Weight Loss for Teens 00:30:00 A Chapter for Parents - Discover Safe and Easy Weight Loss for Teens 00:30:00 A Weight Loss Plan That Is Fun to Implement 00:30:00 Emphasis on Being Thin For Teen Girls Makes Weight Loss a Major Issue 00:30:00 Some Diet Plans for Overweight Teenage Boys 00:30:00 Snack Ideas for Kids That Won't Wreck *Mom's* Diet! 00:30:00 Biking - A Great Way to Enjoy Your Exercise 00:30:00 Exercise Anywhere With Your Bicycle - From Beaches to Mountains to Forests 00:30:00 Weight Control with Bowling Anyone? 00:30:00 Wellness and Fitness Today's Concerns about Wellness and Fitness FREE 01:00:00 The Blissful Union of Wellness and Fitness FREE 00:30:00 The Interchangeability of Wellness, Fitness and Health 00:30:00 The Quality of Life: Is Health Important? 00:30:00 Wellness Terminology 00:30:00 What Makes Us Well? 00:30:00 Wellness 00:30:00 Information on Wellness 00:30:00 How Do We Evaluate Wellness? 00:30:00 What Are Your Wellness Needs? 00:30:00 Wellness of the Body 00:30:00 Wellness of the Spirit 00:30:00 Wellness of the Mind 00:30:00 Benefits of Meditation for the Wellness of Ourselves 00:30:00 Do We Need Meditation? 00:30:00 Quiet Reflection: A B12 Shot for the Spirit? 00:30:00 Are You Well? 00:30:00 Fitness Terminology 00:15:00 Fitness 00:30:00 Information on Fitness 00:30:00 What Are Your Fitness Needs? 00:30:00 Metabolism: What Is It? 00:30:00 Metabolism for the Fit Individual 00:30:00 Metabolism: Can We Control It? 00:30:00 Obesity in Adolescents 00:30:00 Fitness of the Body 00:30:00 Fitness of the Spirit 00:30:00 Fitness of the Mind 00:30:00 Are You Fit? 00:30:00 Where You Live Affects Your Fitness 00:30:00 Fitness Centers: An Investigation 00:30:00 Does Your Income Affect Your Health? 00:30:00 What Role Does Our Intelligence Play in Our Health? 00:30:00 What Role Does Nutrition Play in Our Health? 00:30:00 Is There Health Without Water? 00:30:00 Vitamins: To Be or Not To Be? 00:30:00 How the Brain Affects Our Health 00:30:00 What Are Your Nutritional Needs? 00:30:00 Exercise and Play: What Do We Learn? 00:30:00 The Benefits of Walking 00:30:00 The Mind, Body and Soul Interconnectivity 00:30:00 Chiropractic Care: A Benefit to the Well Individual? 00:30:00 Acupuncture: A Benefit to the Well Individual? 00:30:00 The Benefits of Being Well 00:30:00 Where You Live Affects Your Wellness 00:30:00 The Benefits of Being Fit 00:30:00 Music: Our Connection to the Higher Conscious 00:30:00 The Yin and Yang of the Healthy Individual 00:30:00 Right Hand vs. Left Hand: Who's Healthier? 00:30:00 Is Your Mind Playing Tricks? 00:30:00 Mock Exam Final Exam

OVERVIEW By enroling in Statistics & Probability for Data Science & Machine Learning, you can kickstart your vibrant career and strengthen your profound knowledge. You can learn everything you need to know about the topic. The Statistics & Probability for Data Science & Machine Learning course includes all of the most recent information to keep you abreast of the employment market and prepare you for your future. The curriculum for this excellent Statistics & Probability for Data Science & Machine Learning course includes modules at all skill levels, from beginner to expert. You will have the productivity necessary to succeed in your organisation once you have completed our Statistics & Probability for Data Science & Machine Learning Program. So enrol in our Statistics & Probability for Data Science & Machine Learning course right away if you're keen to envision yourself in a rewarding career. DESCRIPTION Enroling in this Statistics & Probability for Data Science & Machine Learning course can improve your Statistics & Probability for Data Science & Machine Learning perspective, regardless of your skill levels in the Statistics & Probability for Data Science & Machine Learning topics you want to master. If you're already a Statistics & Probability for Data Science & Machine Learning expert, this peek under the hood will provide you with suggestions for accelerating your learning, including advanced Statistics & Probability for Data Science & Machine Learning insights that will help you make the most of your time. This Statistics & Probability for Data Science & Machine Learning course will act as a guide for you if you've ever wished to excel at Statistics & Probability for Data Science & Machine Learning. WHY CHOOSE US? * This course is accredited by the CPD Quality Standards. * Lifetime access to the whole collection of the learning materials. * Online test with immediate results. * Enroling in the course has no additional cost. * You can study and complete the course at your own pace. * Study for the course using any internet-connected device, such as a computer, tablet, or mobile device. CERTIFICATE OF ACHIEVEMENT Upon successful completion, you will qualify for the UK and internationally-recognised CPD certificate and you can choose to make your achievement formal by obtaining your PDF Certificate at a cost of £4.99 and Hardcopy Certificate for £9.99. WHO IS THIS COURSE FOR? This Statistics & Probability for Data Science & Machine Learning course is a great place to start if you're looking to start a new career in Statistics & Probability for Data Science & Machine Learning field. This training is for anyone interested in gaining in-demand Statistics & Probability for Data Science & Machine Learning proficiency to help launch a career or their business aptitude.  REQUIREMENTS The Statistics & Probability for Data Science & Machine Learning course requires no prior degree or experience. All you require is English proficiency, numeracy literacy and a gadget with stable internet connection. Learn and train for a prosperous career in the thriving and fast-growing industry of Statistics & Probability for Data Science & Machine Learning, without any fuss. CAREER PATH This Statistics & Probability for Data Science & Machine Learning training will assist you develop your Statistics & Probability for Data Science & Machine Learning ability, establish a personal brand, and present a portfolio of relevant talents. It will help you articulate a  Statistics & Probability for Data Science & Machine Learning professional story and personalise your path to a new career. Furthermore, developing this Statistics & Probability for Data Science & Machine Learning skillset can lead to numerous opportunities for high-paying jobs in a variety of fields. ORDER YOUR CERTIFICATE To order CPD Quality Standard Certificate, we kindly invite you to visit the following link: COURSE CURRICULUM Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Order Your Certificate Order Your Certificate 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. LEARNING OUTCOMES * Understanding the foundations and functionalities of Python, focusing on its application in data science. * Applying various Python libraries like NumPy and Pandas for effective data analysis. * Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. * Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. * Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. * Exploring advanced topics, encompassing recommender systems and natural language processing with Python. * Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Player https://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp4 00:00 00:00 00:00 Use Up/Down Arrow keys to increase or decrease volume. WHY BUY THIS CERTIFICATE IN DATA SCIENCE AND VISUALISATION WITH MACHINE LEARNING AT QLS LEVEL 3? 1. Unlimited access to the course for a lifetime. 2. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. 3. Structured lesson planning in line with industry standards. 4. Immerse yourself in innovative and captivating course materials and activities. 5. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. 6. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. 7. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. WHO IS THIS CERTIFICATE IN DATA SCIENCE AND VISUALISATION WITH MACHINE LEARNING AT QLS LEVEL 3 COURSE FOR? * Aspiring data scientists aiming to harness the power of Python. * Researchers keen to enrich their analytical and visualisation skills. * Analysts aiming to add machine learning to their toolkit. * Developers striving to integrate data analytics into applications. * Business professionals desiring data-driven decision-making capabilities. CAREER PATH * Data Scientist: £55,000 - £85,000 Per Annum * Machine Learning Engineer: £60,000 - £90,000 Per Annum * Data Analyst: £30,000 - £50,000 Per Annum * Data Visualisation Specialist: £45,000 - £70,000 Per Annum * Natural Language Processing Specialist: £65,000 - £95,000 Per Annum * Business Intelligence Developer: £40,000 - £65,000 Per Annum PREREQUISITES This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. CERTIFICATION After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. COURSE CURRICULUM Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

The 'Chainsaw Safety Training' course is a comprehensive program designed to educate individuals about the safe and efficient use of chainsaws. It covers fundamental concepts such as chainsaw basics, equipment understanding, personal protective gear, pre-operation safety checks, proper handling and operation, advanced techniques, safety measures, and post-operation and emergency procedures. This training is essential for those who work with chainsaws to prevent accidents and ensure a secure working environment.   Learning Outcomes of Chainsaw Safety Training: Upon completion of this course, participants will be able to: * Understand the fundamental principles of chainsaw operation. * Identify and comprehend the various components and equipment associated with chainsaws. * Learn how to select, wear, and maintain personal protective equipment (PPE) for chainsaw use. * Perform pre-operation safety checks to ensure the chainsaw is in proper working condition. * Develop the skills required for safe chainsaw handling and operation. * Explore advanced chainsaw techniques for increased efficiency and precision. * Implement safety measures and protocols to prevent accidents. * Know how to respond to post-operation and emergency situations effectively.   WHY BUY THIS CHAINSAW SAFETY 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 Chainsaw Safety Training 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 CHAINSAW SAFETY TRAINING COURSE FOR? This Chainsaw Safety Training does not require you to have any prior qualifications or experience. You can just enrol and start learning.  * Forestry and arborist professionals who use chainsaws in their work. * Landscapers and tree care specialists. * Farmers and agricultural workers. * Outdoor enthusiasts, such as campers and hikers. * Anyone interested in learning how to safely operate a chainsaw.   PREREQUISITES This Chainsaw Safety 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   * Arborist - Median earning of £20,000 - £40,000 per year. * Forestry Worker - Median earning of £18,000 - £30,000 per year. * Landscaper - Median earning of £18,000 - £35,000 per year. * Agricultural Worker - Median earning of £18,000 - £35,000 per year. * Safety Instructor - Potential earning of £25,000 - £45,000 per year. COURSE CURRICULUM Module 01: Chainsaw Basics Chainsaw Basics 00:16:00 Module 02: Understanding the Equipment Understanding the Equipment 00:18:00 Module 03: Personal Protective Equipment (PPE) Personal Protective Equipment (PPE) 00:13:00 Module 04: Pre-Operation Safety Checks Pre-Operation Safety Checks 00:12:00 Module 05: Chainsaw Handling and Operation Chainsaw Handling and Operation 00:11:00 Module 06: Advanced Chainsaw Techniques Advanced Chainsaw Techniques 00:17:00 Module 07: Safety Measures Safety Measures 00:18:00 Module 08: Post-Operation and Emergency Procedures Post-Operation and Emergency Procedures 00:12:00

Embarking on a journey through the world of arboriculture opens doors to a realm where nature and knowledge intertwine. With its comprehensive curriculum, the 'Arboriculture' course guides learners through the fascinating intricacies of tree care and management. Beginning with an introduction to arboriculture, the course delves into the heart of tree planting techniques, ensuring students grasp the foundational concepts of this green science. As the course progresses, learners explore the nuances of tree selection tailored for arboricultural purposes, delving deeper into the biological aspects of trees in the fourth module. This journey of discovery then leads students through the critical relationship between soil and tree growth, an essential component of healthy arboricultural practices. Continuing this enlightening path, the course covers the vital skills of pruning, a key technique in maintaining tree health and aesthetics. This is complemented by a detailed exploration of tree diseases and their management, a crucial aspect for any arboricultural consultant. The course then equips students with knowledge about arboriculture equipment and operations, culminating in a crucial module on workplace health and safety. This comprehensive curriculum is not just a series of lessons; it's an invitation to become part of an arboricultural association, where learners can share their passion and knowledge with like-minded individuals. The beauty of this course lies in its ability to transform enthusiasts into professionals. Every module, from the arboricultural survey to the final assessment, is meticulously designed to offer practical and theoretical knowledge. Whether it's understanding the meaning of arboriculture or diving into the specifics of an arboricultural impact assessment, the course prepares students for a range of arboriculture jobs. Additionally, the opportunity to engage with an arboricultural report and partake in arboriculture courses further reinforces the learning experience, setting a solid foundation for a fulfilling career in this field. Learning Outcomes 1. Acquire comprehensive knowledge of tree biology, soil dynamics, and their interrelation in tree growth. 2. Develop expertise in tree planting, pruning techniques, and managing tree diseases. 3. Gain proficiency in using arboriculture equipment and implementing workplace health and safety practices. 4. Learn to conduct detailed arboricultural surveys and impact assessments. 5. Understand the process of creating professional arboricultural reports and consultations. WHY BUY THIS ARBORICULTURE COURSE? 1. Unlimited access to the course for a lifetime. 2. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. 3. Structured lesson planning in line with industry standards. 4. Immerse yourself in innovative and captivating course materials and activities. 5. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. 6. Flexibility to complete the Course at your own pace, on your own schedule. 7. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. 8. Unlock career resources for CV improvement, interview readiness, and job success. CERTIFICATION After studying the course materials of the Arboriculture 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 ARBORICULTURE COURSE FOR? * Individuals passionate about tree care and environmental sustainability. * Beginners seeking foundational knowledge in arboriculture. * Professionals in landscaping or gardening aiming to specialize in tree care. * Environmental science students looking to broaden their knowledge. * Career switchers interested in pursuing a role in environmental conservation. PREREQUISITES This Arboriculture 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 * Arboricultural Consultant: £30,000 - £50,000 Per Annum * Tree Surgeon: £25,000 - £40,000 Per Annum * Urban Forester: £28,000 - £45,000 Per Annum * Parks Manager: £30,000 - £50,000 Per Annum * Landscape Architect: £27,000 - £40,000 Per Annum * Environmental Manager: £35,000 - £55,000 Per Annum COURSE CURRICULUM Module 01: Introduction to Arboriculture Introduction to Arboriculture 00:27:00 Module 02: Tree Planting Techniques Tree Planting Techniques 00:18:00 Module 03: Tree Selection for Arboriculture Tree Selection for Arboriculture 00:33:00 Module 04: Tree Biology Tree Biology 00:35:00 Module 05: Soil and Tree Growth Soil and Tree Growth 00:36:00 Module 06: Pruning Trees Pruning Trees 00:29:00 Module 07: Tree Diseases and Management Tree Diseases and Management 00:44:00 Module 08: Arboriculture Equipments and Operations Arboriculture Equipment and Operations 00:38:00 Module 09: Workplace Health and Safety Workplace Health and Safety 00:40:00 Assignment Assignment - Arboriculture 00:00:00

Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you! In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R. Learning Outcomes By the end of this course, you will be able to: * Apply descriptive statistics, distributions, and probability theory to summarise and visualise data * Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data * Use Python and R to implement statistical and machine learning methods * Interpret and communicate the results of your analysis using appropriate metrics and visualisations * Solve real-world problems and scenarios using statistics and probability WHY CHOOSE THIS ADVANCED DIPLOMA IN STATISTICS & PROBABILITY FOR DATA SCIENCE & MACHINE LEARNING AT QLS LEVEL 7 COURSE? 1. Unlimited access to the course for a lifetime. 2. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. 3. Structured lesson planning in line with industry standards. 4. Immerse yourself in innovative and captivating course materials and activities. 5. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. 6. Flexibility to complete the Course at your own pace, on your own schedule. 7. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. 8. Unlock career resources for CV improvement, interview readiness, and job success. WHO IS THIS ADVANCED DIPLOMA IN STATISTICS & PROBABILITY FOR DATA SCIENCE & MACHINE LEARNING AT QLS LEVEL 7 COURSE FOR? This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for: * Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge * Students and researchers who want to learn the mathematical foundations of data science and machine learning * Professionals and managers who want to understand and apply data-driven decision making * Hobbyists and enthusiasts who want to explore and learn from data * Anyone who loves statistics and probability and wants to challenge themselves CAREER PATH * Data Scientist (£35,000 - £55,000) * Machine Learning Engineer (£40,000 - £60,000) * Statistician (£35,000 - £55,000) * Data Analyst (£40,000 - £60,000) * Business Intelligence Analyst (£45,000 - £65,000) * Senior Data Analyst (£50,000 - £70,000) PREREQUISITES This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. CERTIFICATION After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. COURSE CURRICULUM Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Assignment Assignment - Statistics & Probability for Data Science & Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

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

OVERVIEW In this age of technology, data science and machine learning skills have become highly demanding skill sets. In the UK a skilled data scientist can earn around £62,000 per year. If you are aspiring for a career in the IT industry, secure these skills before you start your journey. The Complete Machine Learning & Data Science Bootcamp 2023 course can help you out. This course will introduce you to the essentials of Python. From the highly informative modules, you will learn about NumPy, Pandas and matplotlib. The course will help you grasp the skills required for using python for data analysis and visualisation. After that, you will receive step-by-step guidance on Python for machine learning. The course will then focus on the concepts of Natural Language Processing.  Upon successful completion of the course, you will receive a certificate of achievement. This certificate will help you elevate your resume. So enrol 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? Anyone with an interest in learning about data science can enrol in this course. It will help aspiring professionals develop the basic skills to build a promising career. Professionals already working in this can take the course to improve their skill sets. 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 COURSE CURRICULUM 18 sections • 98 lectures • 23:48:00 total length •Welcome & Course Overview6: 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): 00:17:00 •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