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Our Aim Is Your Satisfaction! Offer Ends Soon; Hurry Up!! Are you looking to improve your current abilities or make a career move? Our unique Data Analytics with Tableau course might help you get there! Expand your expertise with high-quality training - study the Data Analytics with Tableau course and get an expertly designed, great-value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through theonline training course. The Data Analytics with Tableau course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of the Data Analytics with Tableau course, an instant e-certificate will be exhibited in your profile that you can order as proof of your skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course. This Data Analytics with Tableau training can help you to accomplish your ambitions and prepare you for a meaningful career. So, join us today and gear up for excellence! Why Prefer Us? Opportunity to earn a certificate accredited by CPDQS. Get a free student ID card!(£10 postal charge will be applicable for international delivery) Innovative and Engaging Content. Free Assessments 24/7 Tutor Support. Take a step toward a brighter future! *** Course Curriculum *** Here is the curriculum breakdown of the Data Analytics with Tableau course: Data Analytics with Tableau Module 01: Introduction to the Course Module 02: Project 1: Discount Mart (Sales and Profit Analytics) Module 03: Project 2: Green Destinations (HR Analytics) Module 04: Project 3: Superstore (Sales Agent Tracker) Module 05: Northwind Trade (Shipping Analytics) Module 06: Project 5: Tesla (Stock Price Analytics) Module 07: Bonus: Introduction to Database Concepts Module 08: Tableau Stories Assessment Process Once you have completed all the modules in the Data Analytics with Tableau course, you can assess your skills and knowledge with an optional assignment. Certificate of Completion The learners have to complete the assessment of this Data Analytics with Tableau course to achieve the CPDQS accredited certificate. Digital Certificate: £10 Hard Copy Certificate: £29 (Inside UK) Hard Copy Certificate: £39 (for international students) CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about the topic is advised to take this Data Analytics with Tableau course. This course is open to everybody. Requirements You will not need any prior background or expertise to enrol in this course. Career path After completing this course, you are to start your career or begin the next phase of your career.

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 Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use 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? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. 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. 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

Compliance and Risk Management Diploma Level 5 Course Overview The Compliance and Risk Management Diploma Level 5 provides a comprehensive introduction to the fundamental principles of compliance and risk management. This course covers essential topics such as compliance audits, risk management processes, compliance ethics, and risk types, ensuring that learners gain a solid foundation in the field. Upon completion, learners will possess the knowledge and skills necessary to effectively manage compliance and risk in various organisations, enhancing their career prospects within compliance-focused roles. The course is suitable for professionals looking to upskill and those new to the field, offering valuable insights for practical application in today’s regulatory environments. Course Description This diploma-level course explores key concepts in compliance and risk management, beginning with an overview of compliance principles and progressing through modules that delve into specific areas, including risk identification, management strategies, and the ethics of compliance. The course will provide learners with a thorough understanding of compliance management systems (CMS), audit procedures, and the diverse types of risks organisations face. Learners will gain the expertise required to assess, mitigate, and manage risks while ensuring compliance with industry regulations. The curriculum includes real-world case studies and examples that will equip learners with the skills to tackle the challenges faced by businesses in maintaining regulatory adherence and managing risk exposure. Compliance and Risk Management Diploma Level 5 Curriculum Module 01: Introduction to Compliance Module 02: Five Basic Elements of Compliance Module 03: Compliance Management System (CMS) Module 04: Compliance Audit Module 05: Compliance and Ethics Module 06: Risk and Types of Risk Module 07: Introduction to Risk Management Module 08: Risk Management Process (See full curriculum) Who is this course for? Individuals seeking to enter or advance in the compliance and risk management field. Professionals aiming to enhance their knowledge of compliance systems and risk strategies. Beginners with an interest in regulatory frameworks and risk management. Individuals seeking career growth within regulated industries. Career Path Compliance Officer Risk Manager Compliance Auditor Risk Analyst Regulatory Affairs Specialist Corporate Governance Advisor

Public Healthcare Course Overview This course provides a comprehensive introduction to public healthcare, offering learners a deeper understanding of the policies, concepts, and challenges involved in providing healthcare services to the public. It explores key aspects of public health, including health promotion, the role of religion, and the foundational quality features of health coverage. By the end of the course, learners will be equipped with a strong theoretical foundation in public healthcare and its practical application. With a focus on global healthcare systems, this course prepares learners for roles in healthcare management, policy development, and public health advocacy. Course Description In this course, learners will delve into the core concepts of public healthcare, covering a broad spectrum of topics such as health policies, the definition of health, and the intersection of religion and healthcare. The course offers a detailed exploration of health promotion, public health concepts, and the quality features essential to effective healthcare coverage. Learners will gain insights into the barriers that hinder healthcare delivery and the strategies to overcome them. This learning experience will help learners develop a thorough understanding of the systems, challenges, and opportunities within public healthcare, equipping them with the knowledge to engage effectively in healthcare discussions, policy making, and strategic planning. Public Healthcare Curriculum Module 01: Definitions and Healthcare Policies Module 02: Concepts of Health Module 03: Religion and Health Module 04: Understanding the Role of Health Promotion Module 05: Concept of Public Health Module 06: Fundamental Quality Features of Health Coverage Module 07: Practical Barriers to Provision of Healthcare (See full curriculum) Who is this course for? Individuals seeking to understand public healthcare systems. Professionals aiming to enhance their career in healthcare policy, management, or advocacy. Beginners with an interest in healthcare and public health. Anyone seeking to contribute to the improvement of health services. Career Path Healthcare policy analyst Public health advisor Healthcare management professional Health promotion officer Public health researcher Policy maker in healthcare organisations

Marketing Principles Course Overview This course on Marketing Principles provides learners with a comprehensive understanding of core marketing concepts, strategies, and the integral role marketing plays within an organisation. Through a series of well-structured modules, participants will explore key areas including marketing analysis, planning, and execution. By the end of the course, learners will have a solid foundation in creating and implementing effective marketing strategies, understanding market dynamics, and evaluating marketing performance. The course equips learners with essential marketing knowledge, ideal for enhancing career opportunities in various sectors. Course Description The Marketing Principles course delves into the essential aspects of marketing, covering areas such as situational analysis, microenvironments, and the creation of effective marketing plans. Learners will explore how organisations identify opportunities, assess industry trends, and build marketing strategies that align with business goals. Key topics include analysing market conditions, developing marketing strategies, and executing plans efficiently. Throughout the course, learners will gain a deeper understanding of marketing's role within business structures, enabling them to confidently approach marketing challenges in any industry. By the course's conclusion, participants will have acquired key skills in strategic planning and analysis. Marketing Principles Curriculum Module 01: Marketing And The Firm Module 02: Situational Marketing Analysis Module 03: Microenvironments – Industry And Market Module 04: Formulating A Marketing Plan – Building Components Module 05: Executing The Marketing Plan (See full curriculum) Who is this course for? Individuals seeking to build a strong foundation in marketing. Professionals aiming to enhance their marketing knowledge and skills. Beginners with an interest in pursuing a career in marketing. Business owners and entrepreneurs looking to improve their marketing strategy. Career Path Marketing Manager – Oversee marketing campaigns and strategies. Marketing Analyst – Research market trends and consumer behaviours. Brand Manager – Develop and manage brand strategies. Sales and Marketing Executive – Focus on product promotion and customer outreach. Digital Marketing Specialist – Utilise online platforms to promote brands and services.

Information Management Course Overview This Information Management course provides a comprehensive understanding of the principles and practices essential for effectively managing information in today’s data-driven world. It covers core topics such as strategic planning, databases, management information systems, and the auditing of information systems. The course is designed to enhance learners' understanding of how information can be efficiently organised, secured, and utilised for decision-making within organisations. Upon completion, learners will be equipped with the skills to manage data, ensure compliance with data protection laws, and address ethical and social issues surrounding information management. This course is ideal for individuals looking to advance their knowledge in information management and pursue a career in this dynamic field. Course Description The Information Management course explores critical aspects of managing data and information systems, offering in-depth insights into the processes and tools used in modern organisations. The course covers a broad range of topics, including developing information management strategies, understanding and implementing databases, and examining management information systems (MIS) for efficient decision-making. Learners will also gain knowledge of auditing information systems to ensure accuracy, integrity, and security. The ethical, legal, and social considerations of data protection and information governance are also discussed. Throughout the course, learners will engage with key theories and practices, preparing them to apply their knowledge to various industries, ensuring organisations meet legal requirements and maximise the value of their information assets. Information Management Curriculum Module 01: Introduction to Information Management Module 02: Information Management Strategy Module 03: Databases and Information Management Module 04: Management Information Systems (MIS) Module 05: Auditing Information Systems Module 06: Ethical and Social Issues and Data Protection (See full curriculum) Who is this course for? Individuals seeking to understand the principles of information management. Professionals aiming to enhance their knowledge of information governance and security. Beginners with an interest in data management and organisational systems. Anyone looking to develop skills for improving organisational efficiency and compliance. Career Path Data Analyst Information Manager Records Manager IT Compliance Officer Data Protection Officer Information Systems Auditor

Microsoft Office 2016 Complete Course Course Overview: The "Microsoft Office 2016 Complete Course" is designed to provide learners with comprehensive knowledge and essential skills in the core Microsoft Office applications. This course offers in-depth coverage of Microsoft Word, Excel, PowerPoint, Outlook, and Access, enabling participants to confidently use these programs in professional environments. By the end of the course, learners will be equipped to create, manage, and analyse documents, spreadsheets, presentations, emails, and databases with proficiency. This course is an invaluable resource for those looking to enhance their productivity and improve their digital skills, making them more competitive in the job market. Course Description: The "Microsoft Office 2016 Complete Course" delves into the key functionalities of Microsoft Office, with modules dedicated to each major application. Learners will explore the features of Word for document creation and editing, Excel for data analysis and management, PowerPoint for effective presentations, Outlook for email and calendar management, and Access for database handling. Each module is structured to help learners understand the software’s core functions and how to apply them in real-world scenarios. Upon completion, learners will have developed a strong foundation in using Office 2016, boosting their ability to operate efficiently and effectively in modern workplaces. This course is suitable for individuals seeking to increase their office productivity and streamline their daily tasks. Microsoft Office 2016 Complete Course Curriculum: Module 01: Microsoft Word 2016 Module 02: Microsoft Excel 2016 Module 03: Microsoft PowerPoint 2016 Module 04: Microsoft Outlook 2016 Module 05: Microsoft Access 2016 (See full curriculum) Who is this course for? Individuals seeking to improve their office productivity skills. Professionals aiming to advance in roles requiring Microsoft Office proficiency. Beginners with an interest in data management, communication, and office software. Those wishing to enhance their CV and increase career opportunities in administrative and support roles. Career Path: Office Administrator Executive Assistant Data Analyst Personal Assistant Administrative Support Specialist Project Coordinator

KYC, AML, & GDPR Training Course Overview This KYC, AML, and GDPR Training course offers a comprehensive introduction to the regulatory frameworks governing financial institutions and businesses. Learners will gain in-depth knowledge of Know Your Customer (KYC) protocols, Anti-Money Laundering (AML) procedures, and GDPR compliance, understanding their importance in maintaining legal and ethical business operations. The course equips professionals with the necessary skills to navigate the regulatory landscape, safeguard businesses against financial crime, and ensure compliance with data privacy laws. By the end of the course, learners will be well-prepared to apply their knowledge in real-world business environments, contributing to secure and compliant operations. Course Description This course delves into the key principles of KYC, AML, and GDPR, exploring their relevance across different industries. Learners will understand the processes involved in customer due diligence, how to identify and prevent money laundering, and how businesses must comply with data privacy regulations. The course provides a structured learning experience, focusing on the practical application of compliance measures, exploring case studies, and providing insights into current and future trends in the industry. Upon completion, participants will possess the expertise to implement these regulations within their organisations, mitigate risks, and contribute to a culture of compliance. KYC, AML, & GDPR Training Curriculum Module 01: Introduction to KYC Module 02: Customer Due Diligence Module 03: AML (Anti-Money Laundering) Module 04: KYC, AML, and Data Privacy Regulations for Business Operations in the United Kingdom Module 05: Regulations to be Complied by Industries Module 06: Methods for Carrying out KYC and AML and the Future of KYC Compliance (See full curriculum) Who is this course for? Individuals seeking to understand financial regulations and compliance. Professionals aiming to develop their knowledge of KYC, AML, and GDPR in their career. Beginners with an interest in the financial services or regulatory compliance industry. Business owners or managers who want to ensure their organisation’s compliance. Career Path Compliance Officer Anti-Money Laundering Specialist KYC Analyst Data Protection Officer Regulatory Compliance Consultant Risk Management Professional

Diploma in Sustainable Energy Level 5 Course Overview The Diploma in Sustainable Energy Level 5 offers a comprehensive understanding of renewable energy technologies, their application, and their role in shaping a sustainable future. This course delves into key energy sources such as solar, wind, bioenergy, and geothermal, providing learners with a solid foundation in sustainable energy practices. Learners will explore global and regional environmental impacts, and the future of renewable energy in the UK, making this course ideal for those aiming to influence energy policy, sustainability practices, or pursue careers in energy management and environmental sciences. Course Description This course covers a wide range of sustainable energy topics, including the fundamentals of solar, wind, tidal, and geothermal energy. It provides an in-depth exploration of each energy source, with a focus on both technological aspects and their broader environmental implications. Learners will gain a strong understanding of renewable energy's role in sustainable development, the impact of energy policies, and the challenges and opportunities within the UK’s energy sector. Upon completion, students will be well-equipped to contribute to the growing demand for sustainable energy solutions and pursue various roles in energy and environmental sectors. Diploma in Sustainable Energy Level 5 Curriculum Module 01: An Introduction to Sustainable Energy Module 02: Solar Energy: Thermal Module 03: Solar Energy: Photovoltaics Module 04: Wind Energy Module 05: Bioenergy Module 06: Geothermal Energy Module 07: Tidal Energy Module 08: Environmental Impacts: A Global and Regional Assessment Module 09: Renewable Energy and Sustainable Development Module 10: The Future of Renewable Energy in the UK into the 2020s and Beyond (See full curriculum) Who is this course for? Individuals seeking to understand renewable energy technologies. Professionals aiming to expand their expertise in sustainable energy solutions. Beginners with an interest in environmental sustainability and energy management. Environmental consultants or policy makers looking to enhance their knowledge of sustainable energy practices. Career Path Renewable Energy Consultant Energy Policy Analyst Sustainable Energy Project Manager Environmental Sustainability Specialist Renewable Energy Technologist Energy Efficiency Consultant

Functional Skills - IT Course Overview: The "Functional Skills - IT" course is designed to provide learners with a comprehensive understanding of essential IT concepts and skills. It covers a wide range of topics, from the basic components of information technology to more advanced areas such as networking, security, and cloud computing. This course is ideal for individuals seeking to enhance their IT skills for personal or professional development. Learners will gain a strong foundation in IT principles, which will support them in various workplace environments and allow them to apply their knowledge to real-world scenarios. Course Description: This course covers fundamental IT concepts, including the core components of information technology, hardware, software applications, and operating systems. Learners will explore topics such as networking, security, database management, and virtualisation. The course also includes an in-depth look at enterprise-level IT systems, traffic flow, and storage solutions. By the end of the course, learners will have a solid understanding of how IT systems are designed, implemented, and managed. They will gain the skills necessary to work effectively in diverse IT roles, enabling them to confidently support organisational IT needs. Functional Skills - IT Curriculum: Module 01: Introduction Module 02: Information Technology Module 03: Components of IT Module 04: Hardware Module 05: Operating System Module 06: Application/Software Module 07: Networking Module 08: Security Module 09: Traffic Flow & Enterprise Level IT Components Module 10: Storage Module 11: Database Module 12: Virtualisation & Cloud Module 13: Management & Other IT Jobs (See full curriculum) Who is this course for? Individuals seeking to develop a strong understanding of IT principles. Professionals aiming to enhance their technical skills for career progression. Beginners with an interest in information technology and related fields. Those looking to pursue a career in IT management, networking, or support roles. Career Path IT Support Technician Network Administrator Systems Analyst IT Manager Cloud Solutions Specialist Database Administrator IT Consultant Cybersecurity Specialist