Course Overview: This comprehensive Property Law course provides an in-depth understanding of property rights, ownership, and key legal principles. Learners will explore essential concepts such as land law, co-ownership, leases, mortgages, and property rights. The course covers both theoretical and practical aspects of property law, enabling learners to gain a clear understanding of property transactions and disputes. By the end of the course, participants will be equipped with the knowledge to navigate property law in both residential and commercial settings, offering them a strong foundation for a career in property law, real estate, or related sectors. Course Description: This Property Law course covers a range of crucial topics, from the fundamental principles of land law to complex property rights and ownership issues. Learners will examine the different forms of land tenure, including registered and unregistered land, and gain insights into the legalities of co-ownership and leases. Key areas such as mortgages, licenses, and proprietary estoppel will also be explored. Throughout the course, learners will develop an understanding of the rights and responsibilities of property owners, landlords, and tenants, and how these impact property transactions. By the end of the course, learners will have gained valuable legal knowledge applicable to property law disputes, legal agreements, and property transactions in the UK. Course Modules: Module 1: Introduction to Property Law Module 2: Land Law Principles- Rights and Interests Module 3: Registered and Unregistered Land Module 4: Ownership and Possession of the Property Module 5: Co-Ownership in Property Module 6: Leases and Bailment Module 7: Property Law: License Module 8: The Mortgage Law Module 9: Insurance for Property Maintenance Module 10: Proprietary Estoppel (Property Rights) Module 11: Security Interests in Property (See full curriculum) Who is this course for? Individuals seeking to gain a solid understanding of property law Professionals aiming to advance their careers in the property or real estate sectors Beginners with an interest in legal aspects of property ownership Aspiring property investors or those looking to specialise in property law Career Path: Property Lawyer Real Estate Consultant Mortgage Advisor Property Manager Legal Advisor for Property Transactions Estate Agent Landlord/Property Investor
Course Overview The Food Safety and Hygiene Level 2 course is designed to equip learners with a strong understanding of the key principles underpinning food hygiene and safety in the UK. Covering essential topics such as microbiological hazards, legislation, allergen control, and hygiene practices, this course prepares learners to contribute effectively to safe food handling environments. Whether you're working in catering, hospitality, retail, or food production, the knowledge gained through this course helps ensure food is handled in compliance with UK standards. By the end of the course, learners will be confident in identifying hazards, understanding legal responsibilities, and maintaining hygienic practices within food premises. It also includes timely guidance for adapting food businesses during COVID-19, supporting learners in meeting current industry expectations. Course Description This CPD-accredited course explores the foundations of food safety and hygiene, including a detailed look into food legislation, storage, preparation, and cleaning protocols. Learners will gain insights into the causes of foodborne illnesses, methods to prevent cross-contamination, and best practices for managing allergenic, chemical, and physical hazards. The course also highlights the importance of personal hygiene, structural cleanliness, and effective waste control within food premises. A dedicated module addresses how food businesses can operate safely during and after the COVID-19 pandemic. Designed to support learners in understanding their responsibilities under food law, this course promotes awareness and compliance in diverse food-handling settings, from small catering units to large-scale food operations. Course Modules Module 01: Food Safety Legislation Module 02: Microbiological Hazards Module 03: Physical, Chemical and Allergenic Hazards Module 04: Food Storage Module 05: Food Preparation Module 06: Personal Hygiene Module 07: Food Premises Design and Cleaning Schedules Module 08: Further Information Module 09: Reopening and Adapting Your Food Business During COVID-19 (See full curriculum) Who is this course for? Individuals seeking to meet UK food safety training requirements. Professionals aiming to develop their food safety knowledge for supervisory or compliance roles. Beginners with an interest in food hygiene and regulatory standards. Business owners and managers in catering, hospitality, or food production. Career Path Food Safety Officer Catering Assistant Kitchen Supervisor Restaurant or Café Manager Food Retail Worker Compliance Assistant in Food Manufacturing
Course Overview The Xero Accounting and Bookkeeping Level 7 course offers a comprehensive understanding of digital accounting using Xero software, tailored for individuals looking to advance in financial management and bookkeeping roles. This course equips learners with essential knowledge to manage sales, purchases, payroll, VAT, and fixed assets efficiently. Learners will also explore how to maintain accurate financial records and ensure compliance with current UK regulations. Whether you are looking to upgrade your skills or step into a new career, this course supports your professional development by building competence in cloud-based accounting practices. Upon completion, learners will have the confidence to work in a variety of finance-related roles and contribute effectively to any business or organisation’s accounting functions. Course Description This course delves into core areas of Xero accounting, starting with an introduction to the software and progressing through key functionalities including sales invoicing, purchase management, bank reconciliation, and payroll processing. Learners will be guided through each section in a structured and accessible way, allowing them to understand how to set up and manage accounts, handle tax returns, and record transactions accurately. Additional topics such as fixed asset tracking and product/service management provide a complete view of digital bookkeeping in a professional context. The curriculum is designed to align with UK financial standards and includes a detailed exploration of VAT return procedures. By the end of the course, learners will develop a strong grasp of Xero’s interface, gain proficiency in managing financial tasks digitally, and enhance their confidence to support accounting operations within various business settings. Course Modules Module 01: Introduction Module 02: Getting Started Module 03: Invoices and Sales Module 04: Bills and Purchases Module 05: Bank Accounts Module 06: Products and Services Module 07: Fixed Assets Module 08: Payroll Module 09: VAT Returns (See full curriculum) Who is this course for? Individuals seeking to develop advanced accounting skills using cloud-based software. Professionals aiming to improve their bookkeeping knowledge and career progression. Beginners with an interest in digital finance and business accounting. Small business owners and administrative staff managing company accounts. Career Path Xero Bookkeeper Accounts Assistant Payroll Officer Finance Administrator VAT Compliance Officer Office Manager (with financial duties) Small Business Accountant
Course Overview The Baking and Cake Decorating course provides an exciting opportunity to explore the artistry of baking and the creative techniques of cake design. This course is designed to equip learners with the essential knowledge and refined skills needed to produce elegant baked goods and stunning cake presentations. Throughout the course, participants will discover professional approaches to sophisticated baking, icing techniques, and fondant decoration. Whether learners aspire to enhance their home baking abilities or pursue a career in the culinary arts, this course delivers a comprehensive foundation. By the end of the programme, learners will have developed the expertise to produce bakery-quality cakes and sophisticated decorative finishes, enhancing both personal and professional opportunities in the culinary sector. Course Description The Baking and Cake Decorating course covers a wide range of topics essential for mastering the art of elegant baking and cake embellishment. Learners will begin with sophisticated baking and cake design principles before progressing to icing techniques and the intricacies of fondant creation. A focus on decorating with fondant ensures that participants gain a thorough understanding of professional presentation standards. Each module is structured to build confidence and competence, ensuring learners acquire not just technical knowledge but also an appreciation of creative aesthetics. Through a structured and supportive learning experience, participants will emerge with enhanced skills in cake preparation, artistic decoration, and contemporary bakery trends. This course is ideal for those seeking to establish or expand their credentials within the baking and cake design industry. Course Modules Module 01: Sophisticated Baking & Cake Design Module 02: Icing Module 03: Fondant Making Module 04: Decorating with Fondant Module 05: Everything in Brief (See full curriculum) Who is this course for? Individuals seeking to develop skills in professional baking and cake decoration. Professionals aiming to enhance their culinary expertise and artistic presentation techniques. Beginners with an interest in learning the fundamentals of baking and decorative arts. Enthusiasts wishing to explore career opportunities within the culinary or event industries. Career Path Cake Decorator Professional Baker Pastry Chef Assistant Event Catering Specialist Artisan Bakery Business Owner Dessert Designer
Course Overview The DeepSeek Masterclass: A Complete DeepSeek Zero to Hero! is designed to provide learners with a comprehensive understanding of DeepSeek AI from the ground up. Whether you are new to artificial intelligence or seeking to deepen your expertise, this course offers a structured journey through DeepSeek's functionalities and real-world applications. Learners will discover how to navigate DeepSeek for software development, business innovation, and educational advancement. Through this masterclass, individuals will build a strong theoretical foundation, explore diverse use cases, and emerge with the confidence to implement DeepSeek-driven strategies in a range of professional environments. By the end of the programme, learners will have developed the knowledge and insights necessary to use DeepSeek as a transformative tool across multiple disciplines. Course Description This in-depth course covers a wide range of essential topics, including the foundations of artificial intelligence, DeepSeek system setup, and its applications across various sectors such as business, education, and software development. Learners will explore how DeepSeek can be leveraged to create smart solutions for students, empower business professionals, and support teaching practices. The masterclass delivers an immersive learning experience that blends conceptual knowledge with strategic application insights. Participants will build expertise in utilising DeepSeek to enhance efficiency, support innovation, and foster professional growth. Whether learners are looking to enter the AI space or to future-proof their careers, this course equips them with the essential skills and understanding to confidently engage with DeepSeek technologies in a competitive landscape. Course Modules Module 01: Getting Started Module 02: Foundations of Artificial Intelligence (AI) Module 03: Setting up DeepSeek AI for Beginners Module 04: DeepSeek for Software Developers Module 05: DeepSeek for Business Professionals Module 06: DeepSeek Smart Solutions for Students Module 07: The Power of DeepSeek Module 08: DeepSeek for Teaching Professionals (See full curriculum) Who is this course for? Individuals seeking to master DeepSeek AI from basic to advanced levels. Professionals aiming to integrate DeepSeek solutions into their organisations. Beginners with an interest in artificial intelligence, software development, or educational technology. Educators and trainers wishing to incorporate AI-based strategies into teaching. Career Path AI Solutions Specialist Software Developer (AI Focus) Business Innovation Consultant Educational Technology Specialist Data Analysis Support Roles AI Application Support Officer Digital Transformation Assistant
Course Overview The "Store Assistant" course offers learners an in-depth understanding of the retail sector, covering essential aspects such as customer service, store management, and retail operations. By completing this course, learners will gain the skills necessary to effectively contribute to the day-to-day operations of a retail environment. The course will also equip them with knowledge of retail management practices, customer interaction strategies, and industry regulations. Learners will come away with a comprehensive understanding of the role and the ability to enhance their professional practice in a retail setting, making them well-prepared for a variety of store assistant positions. Course Description This course is designed to provide learners with essential knowledge and skills for a career as a store assistant. Topics include the roles and responsibilities of store assistants, the basics of retail management, and how to effectively manage customer relationships. Learners will explore visual merchandising, consumer behaviour, and the psychological aspects of retail, along with understanding how to interact with suppliers. Additionally, the course covers relevant retail legislation to ensure compliance in day-to-day operations. Through a structured curriculum, learners will gain insights into managing a retail store, enhancing customer experiences, and applying effective store strategies to improve business outcomes. The course is ideal for those seeking to develop a strong foundation in retail roles and prepare for a successful career in the industry. Course Modules Module 01: Introduction to Store Assistant Module 02: Roles and Responsibilities of a Store Assistant Module 03: Introduction to Retail Management Module 04: Managing a Retail Store Module 05: Visual Merchandising Module 06: Consumer Behaviour Module 07: Dealing with Customers Module 08: Dealing with Suppliers Module 09: Store Psychology Module 10: Legislations Related to Retail (See full curriculum) Who is this course for? Individuals seeking to start a career in retail. Professionals aiming to enhance their retail management skills. Beginners with an interest in customer service and retail operations. Anyone looking to understand retail environments and store dynamics. Career Path Store Assistant Retail Associate Retail Manager Visual Merchandiser Customer Service Representative Retail Supervisor Supply Chain Assistant
The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? 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 Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00
Early Years Support Worker is a wonderful learning opportunity for anyone who has a passion for this topic and is interested in enjoying a long career in the relevant industry. It's also for anyone who is already working in this field and looking to brush up their knowledge and boost their career with a recognised certification. This Early Years Support Worker consists of several modules that take around 14 hours to complete. The course is accompanied by instructional videos, helpful illustrations, how-to instructions and advice. The course is offered online at a very affordable price. That gives you the ability to study at your own pace in the comfort of your home. You can access the modules from anywhere and from any device. Why Choose this Course? Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full tutor support on weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.
Early Years Lead Practitioner is a wonderful learning opportunity for anyone who has a passion for this topic and is interested in enjoying a long career in the relevant industry. It's also for anyone who is already working in this field and looking to brush up their knowledge and boost their career with a recognised certification. This Early Years Lead Practitioner consists of several modules that take around 14 hours to complete. The course is accompanied by instructional videos, helpful illustrations, how-to instructions and advice. The course is offered online at a very affordable price. That gives you the ability to study at your own pace in the comfort of your home. You can access the modules from anywhere and from any device. Why Choose this Course? Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full tutor support on weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.
Level 3 Diploma for the Children's Workforce (Early Years Educator) - CPD is a wonderful learning opportunity for anyone who has a passion for this topic and is interested in enjoying a long career in the relevant industry. It's also for anyone who is already working in this field and looking to brush up their knowledge and boost their career with a recognised certification. This Level 3 Diploma for the Children's Workforce (Early Years Educator) - CPD consists of several modules that take around 14 hours to complete. The course is accompanied by instructional videos, helpful illustrations, how-to instructions and advice. The course is offered online at a very affordable price. That gives you the ability to study at your own pace in the comfort of your home. You can access the modules from anywhere and from any device. Why Choose this Course? Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full tutor support on weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99.