Struggling with eating disorders can feel like being trapped in an invisible cycle—difficult to explain, even harder to escape. This course has been thoughtfully developed for individuals looking to better understand the complex patterns behind eating disorders and to explore strategies for long-term recovery. Whether you're experiencing disordered eating yourself or supporting someone who is, you'll gain valuable insight into the emotional, psychological, and behavioural aspects of this sensitive subject. Packed with professional guidance, the course gently leads learners through key topics such as body image, emotional triggers, nutritional concerns, and cognitive thought patterns. Designed for clarity and compassion, each module encourages reflection without judgement. There's no jargon or sensationalism—just clear, respectful content presented in a calm, thoughtful tone. Learn at your own pace, with confidence, knowing that you're taking steps towards greater awareness and understanding. Learning outcomes: Understand the different types of eating disorders Learn about the root causes of eating disorders Discover techniques to build a healthier relationship with food Improve self-esteem and overcome negative thought patterns Enhance physical and mental health Our Overcoming Eating Disorders course is designed to help you understand the root causes of eating disorders and provide you with the tools and strategies needed to overcome them. Through this course, you'll learn about the different types of eating disorders and the impact they can have on your physical and mental health. Our expert instructors will guide you through a variety of techniques to help you build a healthier relationship with food, improve your self-esteem, and overcome negative thought patterns. By the end of this course, you'll be on your way to a happier, healthier life. â±â± Overcoming Eating Disorders Course Curriculum Course outline Introduction to course Types of Eating Disorders Bulimia Nervosa Caloric Requirement Research binge eating & purging Studies on Bulimia Nervosa Research on Significance of Binge eating disorder Research on Culture & Eating disorder Research on food insecurity Research on relation between EQ & Eating disorders Research on Incidents & outcomes of eating disorders Binge eating Binge eating continued Symptoms of eating disorders Health effect of binge eating and purging Treatment of binge eating and purging Overcoming your eating disorder (self approach) Introduction to CBT Cognitive Behavioral Therapy Introduction of ACT - Acceptance & Commitment Components of ACT Antecedent and consequential control Goals & Targets of ACT Conclusion How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals who struggle with an eating disorder People who want to learn more about eating disorders and how to overcome them Health professionals who want to expand their knowledge and skills in treating eating disorders Friends and family members of individuals who struggle with an eating disorder Anyone who wants to improve their relationship with food and body image Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Eating Disorder Therapist Nutritionist or Dietician Mental Health Professional Health Coach The salary range for these roles in the UK ranges from £20,000 to £60,000 per year. However, the salary range can vary depending on the industry and level of experience. Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.
Dive into the intricate world of deep learning with this sharply focused course on heuristic techniques using R. This programme is designed for learners keen to understand how heuristics shape machine learning models, particularly in deep neural networks. Whether you're brushing up on your algorithmic intuition or delving deeper into optimisation patterns, this course delivers a solid framework rooted in logic, not lingo. With R as your analytical companion, you'll explore neural computation, gradient-based strategies, backpropagation nuances, and heuristic-inspired adjustments that enhance model efficiency. This isn't about flashy tools or inflated claims — it's about getting your mind around how deep learning truly works, one clever calculation at a time. No fluff, no filler — just clear insights and well-paced learning to support your journey through the matrix of machine intelligence. Learning Outcomes: Develop an understanding of experimental design and how it applies to heuristics. Learn how to apply heuristics to real-world problems in the agriculture, cryptocurrency, energy, and financial markets sectors. Understand how to use R programming language for deep learning heuristics. Develop skills in analyzing data sets and creating predictive models. Learn how to implement different heuristics algorithms in R programming. The Essential Training on Deep Learning Heuristic using R is designed to provide students with a comprehensive understanding of heuristics and how they can be applied to various real-world problems. The course covers experimental design, data analysis, and predictive modelling using R programming language. Students will learn about different heuristics algorithms and how to implement them in R to solve complex problems in the agriculture, cryptocurrency, energy, and financial markets sectors. Throughout the course, students will work on various projects that will help them develop practical skills in analyzing data sets and creating predictive models. They will learn how to design experiments, collect and analyse data, and create models that can be used to make predictions. By the end of the course, students will have a strong understanding of heuristics, and deep learning, and how to apply them to solve real-world problems. Essential Training on Deep Learning Heuristic using R Course Curriculum Section 01: Experimental Design - Heuristics Project 1-Agriculture Section 02: Experimental Design - Heuristics Project 2-Cryptocurrencies Section 03: Experimental Design: Heuristics Project 3-Energy Sector Section 04: Experimental Design: Heuristics Project 4-Financial Markets How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data scientists who want to learn how to apply deep learning heuristics to solve real-world problems. Programmers who want to learn R programming language for data analysis and predictive modeling. Professionals in the agriculture, cryptocurrency, energy, and financial markets sectors who want to apply heuristics to solve complex problems. Students who want to learn about deep learning heuristics and how they can be applied to real-world problems. Anyone interested in developing practical skills in data analysis and predictive modelling using R programming language. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Deep Learning Engineer: £30,000 - £90,000 AI Researcher: £40,000 - £120,000 Data Scientist: £35,000 - £90,000 Machine Learning Engineer: £40,000 - £100,000 AI Architect: £50,000 - £150,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.
Spring Boot 3.0 and MongoDB make quite the duo—clean architecture meets agile data management, with none of the usual chaos. This course has been crafted for those who appreciate structured logic, lightning-fast performance, and the occasional sense of relief when code behaves as expected. Whether you're designing microservices or working with APIs, Spring Boot 3.0 brings clarity to complex Java development. Paired with MongoDB’s flexible document model, this course gives you a deep technical grounding without ever overcomplicating the process. You’ll be walked through essential configurations, RESTful services, and powerful integration patterns with MongoDB—all with a focus on cleaner code, scalable solutions, and secure deployments. From dependency injection to working seamlessly with Spring Data, every step is designed to make the backend behave. No fluff, just solid development principles with the latest tools in your hands. If you’re looking to sharpen your backend logic using two of the most talked-about technologies in modern application development, this course ticks that box—elegantly, of course. Learning Outcomes: Gain a solid understanding of the Spring Boot and MongoDB frameworks and their capabilities. Learn how to set up and configure a MongoDB environment, and integrate it with a Spring Boot application. Understand the CRUD operations and how to perform them using both MongoDB and Spring Boot. Discover the advanced concepts of DBRef and Collections Relationships, OpenAPI integration, and Documents Queries. Learn how to use Query Methods to access and manipulate data in MongoDB. The Master Spring Boot 3.0 and MongoDB course is the ultimate guide to mastering these two powerful technologies. Designed for both newcomers and seasoned professionals, this course will provide you with a comprehensive understanding of the Spring Boot and MongoDB frameworks and their capabilities. You'll learn how to set up and configure a MongoDB environment, and integrate it with a Spring Boot application. The course covers a range of topics, from the basics of CRUD operations to the advanced concepts of DBRef and Collections Relationships, OpenAPI integration, and Documents Queries. By the end of the course, you'll be equipped with the skills and knowledge you need to succeed in this dynamic and competitive field. Master Spring boot 3.0 and MongoDB Course Curriculum Section 01: Introduction Section 02: Prepare the Mongo Environment Section 03: Mongo Terms Section 04: Bootstrapping the Application Section 05: CRUD Operations Section 06: DBRef and Collections Relationships Section 07: OpenApi integration Section 08: Documents Queries and Mongo Template Section 09: Query Methods How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Software developers who want to enhance their skills and knowledge in Spring Boot and MongoDB. Professionals who want to stay up-to-date with the latest technologies and trends in software development. Individuals who are new to the field and want to learn about Spring Boot and MongoDB. Entrepreneurs who want to build scalable and reliable software applications using Spring Boot and MongoDB. Anyone who wants to develop their skills in the software development industry. Career path Full-Stack Developer: £27,000 - £71,000 Software Engineer: £25,000 - £62,000 Senior Software Engineer: £43,000 - £90,000 Technical Lead: £53,000 - £119,000 Solutions Architect: £63,000 - £150,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.
If you’ve ever wondered how websites behave the way they do, JavaScript is the engine that brings them to life. This course offers a solid journey through developing interactive web applications using JavaScript—designed for learners keen to understand how functional apps are built from scratch. Whether you're a beginner with some HTML and CSS under your belt or someone looking to sharpen your scripting skills, this course walks you through structured, engaging projects that reflect how things work behind the screen. The lessons are smartly arranged to help you write better code, manage logic efficiently, and shape features that respond smoothly to user interactions. From dynamic interfaces to responsive designs, each module focuses on real applications of JavaScript, avoiding fluff and straightening out confusion with clean, sensible explanations. Think of it as coding with clarity, not chaos. You're not just learning JavaScript—you’re learning how to make it work the way developers use it to build sleek, functional web experiences. Learning outcomes: Gain a thorough understanding of the basics of event-driven programming and the property or style object Learn how to create a login page with validation and implement JavaScript functions Understand the concepts of a shopping cart and how to manage items in it Develop skills to create user-friendly interfaces using JavaScript Gain hands-on experience in creating a web app using JavaScript The JavaScript Project Development - Creating Web Apps course is designed to teach students how to create user-friendly web applications using JavaScript. The course covers a wide range of topics, including event-driven programming, managing a shopping cart, creating a login page with validation, and implementing JavaScript functions. By the end of the course, students will have gained a thorough understanding of JavaScript and how it can be used to create effective and engaging web applications. JavaScript Project Development - Creating Web Apps Course Curriculum Section 01: Introduction Introduction to Java Script Event Driven Programming Property or Style Object Section 02: Shopping Cart Creating Login Page Validation on Login Page Implementing Java Script Example of Shopping Cart Functions in Java Script Adding Items to Cart Removing Items from Cart Terms of Shopping Cart Files in Local Storage Section 03: Shopping Cart GUI Function for Display Cart Function for Deleting Cart Creating Input Id Section 04: Online Examination Developing Application Function for Return Document Function Check Answer How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Beginner web developers who want to learn how to create user-friendly web applications using JavaScript Experienced developers who want to expand their knowledge of JavaScript and its capabilities Freelancers who want to offer their clients high-quality web application development services Employees who want to improve their web development skills and become more valuable to their company Anyone interested in creating engaging and effective web applications using JavaScript. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Junior web developer: £20,000 - £30,000 Web developer: £30,000 - £40,000 Front-end developer: £35,000 - £50,000 Full-stack developer: £40,000 - £60,000 Senior web developer: £50,000 - £70,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.
Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00
Children don’t just play — they explore, imagine, build friendships, and figure out the world around them. As a playworker, your role is to support this vital journey while keeping play environments stimulating, supportive, and safe. Our Playworker: Child Playwork Training Course is tailored for those with a genuine interest in child development and the unique value of play. You’ll gain insights into the psychology behind play, the stages of childhood development, and how to create environments where children can flourish emotionally and socially through play. Designed for learners looking to deepen their understanding of playwork without stepping into a traditional classroom, this online course covers everything from managing risks in play settings to understanding the role of the adult in play without being intrusive. Whether you're looking to build a career in childcare or just want to understand the science of play, this course offers structured learning in a format that’s easy to follow, flexible, and entirely online. Let children play — but do it with purpose, confidence, and the right knowledge to guide them. Key Features The Playworker: Child Playwork Training course includes the following offers: CPD Quality Standards Accredited Playworker: Child Playwork Training Course Lifetime Access No Hidden Fees 24/7 Tutor Support Certificate Available with reasonable price Discover a wealth of learning opportunities with our diverse range of online courses including Playworker: Child Playwork Training. From professional development to personal enrichment, we offer courses in a variety of subjects including business, technology, arts, languages, and more. This Playworker: Child Playwork Training course is carefully curated by industry experts and delivered through engaging multimedia content, interactive quizzes, and hands-on projects to ensure an immersive learning experience. Curriculum Module 1: Introduction To Child Playwork Module 2: Playwork And Playworkers Module 3: Educational And Learning Benefits Of Playwork Module 4: Economic And Social Benefits Of Playwork Module 5: Health And Well-Being Benefits Of Playwork Module 6: Developmental Benefits Of Playwork Module 7: Negative Impact Of Play Deprivation Module 8: Designing Play Spaces Module 9: Health And Safety Management In Playwork Why This Online Course is Better for You: Unlike traditional classroom settings, our online Playworker: Child Playwork Training course offers flexibility and convenience tailored to fit your busy lifestyle. With 24/7 access to Playworker: Child Playwork Training course materials and the ability to learn at your own pace, you can study whenever and wherever it's most convenient for you. Plus, our online platform provides a supportive community of fellow learners and dedicated instructors to guide you every step of the way. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Our Playworker: Child Playwork Training course is designed for anyone eager to expand their knowledge and skills, regardless of their background or experience level. Whether you're a working professional looking to upskill, a student seeking supplemental education, or an enthusiast pursuing a passion project, our courses are accessible to learners of all ages and abilities. Career path Invest in your future and unlock new career opportunities with our online Playworker: Child Playwork Training course. Gain valuable skills and credentials that are in high demand in today's competitive job market. Whether you're looking to switch careers, climb the corporate ladder, or start your own business, This course provide the expertise and certification you need to succeed. Certificates Digital certificate Digital certificate - £9 Hard copy certificate Hard copy certificate - £15 A Hardcopy Certificate (international): £15 + £10 (postal charge) = £25
In today’s increasingly digital workplace, ensuring your computer workstation is set up safely isn’t just good practice—it’s essential for wellbeing and productivity. This Computer Workstation Safety Training Course guides you through all the vital elements of creating an ergonomic and secure workspace. From correct chair positioning to screen height adjustments, this course helps reduce the risk of discomfort and repetitive strain injuries, making long hours at the desk far more manageable. Designed with clarity and precision, the course delivers essential knowledge to identify potential hazards linked to computer use, such as poor posture, glare, and inadequate breaks. It offers practical advice on optimising your environment to maintain focus and reduce fatigue. Whether you’re a home worker or office-based, this training equips you with the insights to keep your workstation safe, comfortable, and conducive to effective work—all without the need for face-to-face sessions. It’s the perfect way to bring safer working habits into your daily routine with a professional yet approachable touch. Key Features The Computer Workstation Safety Training course includes the following offers: CPD Quality Standards Accredited Computer Workstation Safety Training Course Lifetime Access No Hidden Fees 24/7 Tutor Support Certificate Available with reasonable price Discover a wealth of learning opportunities with our diverse range of online courses including Computer Workstation Safety Training. From professional development to personal enrichment, we offer courses in a variety of subjects including business, technology, arts, languages, and more. This Computer Workstation Safety Training course is carefully curated by industry experts and delivered through engaging multimedia content, interactive quizzes, and hands-on projects to ensure an immersive learning experience. Curriculum Module 1 Introduction To Computer Workstation Safety Module 2 Ergonomics In Computer Workstation Module 3 Preventing Repetitive Strain Injuries (RSI) Module 4 Preventing Eye Injuries Module 5 Posture And Movement Module 6 Stretching And Relaxation Techniques Module 7 Digital Security Why This Online Course is Better for You: Unlike traditional classroom settings, our online Computer Workstation Safety Training course offers flexibility and convenience tailored to fit your busy lifestyle. With 24/7 access to Computer Workstation Safety Training course materials and the ability to learn at your own pace, you can study whenever and wherever it's most convenient for you. Plus, our online platform provides a supportive community of fellow learners and dedicated instructors to guide you every step of the way. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Our Computer Workstation Safety Training course is designed for anyone eager to expand their knowledge and skills, regardless of their background or experience level. Whether you're a working professional looking to upskill, a student seeking supplemental education, or an enthusiast pursuing a passion project, our courses are accessible to learners of all ages and abilities. Career path Invest in your future and unlock new career opportunities with our online Computer Workstation Safety Training course. Gain valuable skills and credentials that are in high demand in today's competitive job market. Whether you're looking to switch careers, climb the corporate ladder, or start your own business, This course provide the expertise and certification you need to succeed. Certificates Digital certificate Digital certificate - £9 Hard copy certificate Hard copy certificate - £15 A Hardcopy Certificate (international): £15 + £10 (postal charge) = £25
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Scientific information demonstrates that workplace safety and efficiency are paramount. Enrol in our PUWER course and delve into comprehensive modules covering essential aspects of work equipment regulations, selection, functionality, inspection, and maintenance. Equip yourself with the knowledge to ensure the highest standards of safety and compliance.
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