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Venturing into the intricate labyrinth of risk and finance, our course, 'Actuary Certification: Navigating the Complex World of Risk and Finance' serves as your guiding beacon. Through this comprehensive journey, participants will unravel the multifaceted role of actuaries and their symbiotic relationship with their environment. Delve deep into the valuation of cash flows, deterministic models, and the life table's myriad intricacies. Embrace an in-depth understanding of life annuities, insurance structures, and the enthralling world of stochastic life contingencies. Furthermore, this course equips learners with the expertise to tackle taxation, inflation, and the nuances of premium calculation, ensuring a holistic approach to the actuarial realm. Learning Outcomes Understand the foundational principles and role of actuarial science in risk and finance. Analyse and interpret life tables, annuities, and insurance models. Apply stochastic methodologies to insurance and annuities. Evaluate the implications of taxation and inflation on financial models. Design and assess various risk models, focusing on uncertain payment and profit testing. Why buy this Actuary Certification: Navigating the Complex World of Risk and Finance? 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 Actuary Certification: Navigating the Complex World of Risk and Finance 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 Actuary Certification: Navigating the Complex World of Risk and Finance course for? This Actuary Certification: Navigating the Complex World of Risk and Finance does not require you to have any prior qualifications or experience. You can just enrol and start learning. Individuals keen to dive into the actuarial sector. Finance and risk management graduates aspiring for a deeper understanding. Professionals in the insurance sector aiming to upscale their knowledge. Mathematics enthusiasts wishing to channel their skills in a finance-oriented domain. Corporate strategists seeking to enhance risk management techniques. Prerequisites This Actuary Certification: Navigating the Complex World of Risk and Finance does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Actuary Certification: Navigating the Complex World of Risk and Finance 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 Actuarial Analyst: £30,000 - £50,000 Risk Management Specialist: £40,000 - £65,000 Insurance Underwriter: £25,000 - £50,000 Financial Planner: £35,000 - £60,000 Actuarial Consultant: £50,000 - £90,000 Portfolio Manager: £55,000 - £120,000 Course Curriculum Module 01: Introduction to Actuary Introduction to Actuary 00:12:00 Module 02: Actuaries and Their Environment Actuaries and Their Environment 00:14:00 Module 03: The Valuation of Cash Flows The Valuation of Cash Flows 00:12:00 Module 04: The Basic Deterministic Model The Basic Deterministic Model 00:11:00 Module 05: The Life Table The Life Table 00:11:00 Module 06: Life Annuities Life Annuities 00:14:00 Module 07: Life Insurance Life Insurance 00:12:00 Module 08: The Stochastic Life Contingencies Model The Stochastic Life Contingencies Model 00:11:00 Module 09: The Stochastic Approach to Insurance and Annuities The Stochastic Approach to Insurance and Annuities 00:11:00 Module 10: Taxation and Inflation Taxation and Inflation 00:08:00 Module 11: Probabilistic Models, Uncertain Payment and Profit Testing Probabilistic Models, Uncertain Payment and Profit Testing 00:08:00 Model 12: Individual Risk Models Individual Risk Models 00:07:00 Module 13: Principles of Premium Calculation Principles of Premium Calculation 00:10:00 Module 14: Multiple Decrement Theory Multiple Decrement Theory 00:09:00

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Embark on a transformative journey with 'Demystifying Depreciation Accounting: Financial Insights'. This course unravels the intricate world of depreciation accounting, offering a comprehensive understanding from its foundational concepts to its real-world applications. Dive deep into the depreciation model, explore enlightening case studies, and stay ahead with insights on emerging trends and future developments. By the end of this course, you'll possess a robust knowledge of depreciation reporting and compliance, positioning you at the forefront of financial expertise. Learning Outcomes Understand the fundamental principles of depreciation accounting. Analyse and interpret the depreciation model in-depth. Evaluate real-world scenarios through case studies. Master the nuances of depreciation reporting and compliance. Stay updated with the latest trends and anticipated shifts in depreciation accounting. Why buy this Demystifying Depreciation Accounting: Financial Insights? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the 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. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Demystifying Depreciation Accounting: Financial Insights for? Finance and accounting students seeking a deeper understanding of depreciation. Business owners aiming to enhance their financial literacy. Accountants looking to refresh or expand their knowledge. Financial analysts aiming to strengthen their analytical skills. Professionals transitioning into finance or accounting roles. Career path Financial Accountant: £40,000 - £55,000 Management Accountant: £45,000 - £60,000 Financial Analyst: £35,000 - £50,000 Finance Manager: £50,000 - £70,000 Compliance Officer: £30,000 - £45,000 Financial Consultant: £45,000 - £65,000 Prerequisites This Demystifying Depreciation Accounting: Financial Insights does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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. Course Curriculum Module 1: Introduction to Depreciation Accounting Introduction to Depreciation Accounting 00:20:00 Module 2: Accounting for Depreciation Accounting for Depreciation 00:22:00 Module 3: Deep Dive into the Depreciation Model Deep Dive into the Depreciation Model 00:14:00 Module 4: Case Studies and Real-World Applications Case Studies and Real-World Applications 00:11:00 Module 5: Depreciation Reporting and Compliance Depreciation Reporting and Compliance 00:13:00 Module 6: Emerging Trends and Future Developments Emerging Trends and Future Developments 00:18:00

Duration 3 Days 18 CPD hours This course is intended for Delegates attending this course must have successfully achieved the ITIL 4 Foundation Qualification; your certificate must be presented as documentary evidence to gain admission to this course. Ideally candidates should have at least two years professional experience working in IT Service Management. The ITIL 4 HVIT Qualification would most likely suit the following delegates: Individuals continuing of their journey in service management ITSM managers and aspiring ITSM managers IT managers and practitioners involved in digital services or working in digital transformation projects, working within or towards high velocity environments Existing ITIL qualification holders wishing to develop their knowledge The above list is a suggestion only. Delegates may take as few or as many Intermediate qualifications as they require, and to suit their needs. Overview This course has been created to help IT service management practitioners working in organizations that are becoming more digitally enabled. The practitioners are familiar with traditional IT service management concepts, and now want to be able to discuss ?digital? with more confidence, to develop practical competences, and to be valued contributors in the digital domain. They want to improve how they and their co-workers: Help get customers? jobs done ? helping customers become who they seek to become Keep raising the bar ? taking things to a significantly higher level Trust and are trusted ? as professional knowledge workers in a healthy workplace Accept ambiguity and uncertainty - not scared of not knowing an answer Commit to continual learning ? all as part of their daily work The scope of the course is the primary activities in the digital value chain. In other words, what the practitioner does and which resources they use across the lifecycle of digital products, in order to: Make the right digital investments Realize and deliver digital products and services quickly Provide digital products and services that are highly resilient to disruption Ensure that the service consumer realizes value from the digital products and services Assure conformance of activities with governance, risk and compliance requirements. Understand and know how to use the key principles and methods of Organizational Change Management to direction, planning and improvement Understand and know how to use the key principles and methods of measurement and reporting in directing, planning and improvement Understand and know how to direct, plan and improve value streams and practices ITIL 4 is a framework for quality IT service management (ITSM) through proven best practice, providing practical and flexible guidance to support your organization on its journey to digital transformation while empowering your IT teams to continue to play a crucial role in the wider business strategy. This course highlights the ways in which digital organizations and digital operating models function in high-velocity environments, including the use of working practices such as Agile and Lean, and technical practices and technologies such as Cloud, Automation, and Automatic Testing. This class includes an exam voucher. Prerequisites ITIL© 4 Foundation 1 - THE NATURE OF HIGH-VELOCITY IN A DIGITAL WORLD Overview of the key ITIL 4 high-velocity terminology Understand when the transformation to high velocity IT is desirable and feasible Understand the five objectives associated with digital products ? to achieve: Valuable investments ? strategically innovative and effective application of IT Fast development - quick realization and delivery of IT services and IT-related products Resilient operations - highly resilient IT services and IT-related products Co-created value - effective interaction between service provider and consumer Assured conformance - to governance, risk and compliance (GRC) requirements. 2 - ITIL OPERATING MODEL ? DIGITAL PRODUCT LIFECYCLE Understand how high velocity IT relates to: The four dimensions of service management The ITIL service value system The service value chain The digital product lifecycle 3 - FUNDAMENTAL CONCEPTS FOR DELIVERING HVIT Understand the following concepts: Ethics Safety culture Toyota Kata Lean / Agile / Resilient / Continuous Service-dominant logic Design thinking Complexity thinking Use the principles, models and concepts to contribute to: Help get customers? jobs done Trust and be trusted Commit to performance Deal with uncertainty Improve by being inquisitive 4 - ACHIEVING VALUE WITH DIGITAL PRODUCTS Know how the service provider ensures valuable investments are achieved. Know how to use the following practices to contribute to achieving valuable investments: Portfolio management Relationship management Know how the service provider ensures fast deployment is achieved Know how to use the following practices to contribute to achieving fast deployment: Architecture management Business analysis Deployment management Service validation and testing Software development and management Know how the service provider ensures resilient operations are achieved Know how to use the following practices to contribute to achieving resilient operations: Availability management Capacity and performance management Monitoring and event management Problem management Service continuity management Infrastructure and platform management Know how the service provider ensures co-created value is achieved Know how to use the following practices to contribute to achieving co-created value with the service consumer: Relationship management Service design Service desk Know how the service provider ensures assured conformance is achieved Know how to use the following practices to contribute to achieving assured conformance: Information security management Risk management

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

Managing Multiple Projects: On-Demand Succeeding in today's competitive marketplace often requires cycle time reduction - reducing the duration of projects and getting results faster. This workshop will address managing multiple projects within the context of program or product management. Are your projects taking longer and longer to complete? Are results less than optimal because of time pressures on resources? Would you like to increase project 'throughout'? Succeeding in today's competitive marketplace often requires cycle time reduction - reducing the duration of projects and getting results faster. This workshop will address managing multiple projects within the context of program or product management. Planning and managing individual projects is challenging. When introducing the real-life limitation of resources and other outside influences into the multi-project environment, those challenges are magnified, and new challenges are introduced. This interactive workshop will position you for immediate action. The goal of this course is to equip you with the necessary knowledge, skills, and techniques so that you can effectively and productively manage multiple projects. What you Will Learn You'll learn how to: Manage stakeholder relationships and expectations Prioritize and sequence multiple projects Manage time and stress within a multiple project environment Effectively manage logical dependencies among projects Optimize the use of resources across multiple projects using concepts from Critical Chain methods Manage risk and communications in a multiple project environment Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Portfolio, program, and project management principles The multiple project environment The MMP Process Model Developing the Multiple Project List Multiple project portfolio management Project selection Project categories and types The multiple project list Multiple Project Logical Dependencies Project dependencies Types of multiple project portfolios Categories of logical dependencies across multiple projects Project priorities in the multiple project schedule Multiple Project Resource Management Multiple project resources and resource management concepts Multiple project resource loading Resource pool and resource database Multiple project resource issues and outsourcing Critical chain resource management, including drum resources and multi-tasking Managing Risk Across Multiple Projects Multiple project risk management process Identifying, assessing, and responding to multiple project risks Critical chain and multiple project risks Risk interrelationship management methods Creating and Executing the Multiple Project Plan The multiple project plan Multiple project scheduling Multiple project budgeting Executing and maintaining the multiple project plan Controlling in the multiple project environment Tools in multiple project management Multiple Project Communications Effective communication in the multiple project environment Common communication barriers Multiple project communications plan Resolving multiple project conflicts Summary and Next Steps What did we learn, and how can we implement this in our work environments?

Use Cases for Business Analysis The use case is a method for documenting the interactions between the user of a system and the system itself. Use cases have been in the software development lexicon for over twenty years, ever since it was introduced by Ivar Jacobson in the late 1980s. They were originally intended as aids to software design in object-oriented approaches. However, the method is now used throughout the Solution Development Life Cycle from elicitation through to specifying test cases, and is even applied to software development that is not object oriented. This course identifies how business analysts can apply use cases to the processes of defining the problem domain through elicitation, analyzing the problem, defining the solution, and confirming the validity and usability of the solution. What you will Learn You'll learn how to: Apply the use case method to define the problem domain and discover the conditions that need improvement in a business process Employ use cases in the analysis of requirements and information to create a solution to the business problem Translate use cases into requirements Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Overview of use case modeling What is a use case model? The 'how and why' of use cases When to perform use case modeling Where use cases fit into the solution life cycle Use cases in the problem domain Use cases in the solution domain Use case strengths and weaknesses Use case variations Use case driven development Use case lexicon Use cases Actors and roles Associations Goals Boundaries Use cases though the life cycle Use cases in the life cycle Managing requirements with use cases The life cycle is use case driven Elicitation with Use Cases Overview of the basic mechanics and vocabulary of use cases Apply methods of use case elicitation to define the problem domain, or 'as is' process Use case diagrams Why diagram? Partitioning the domain Use case diagramming guidelines How to employ use case diagrams in elicitation Guidelines for use case elicitation sessions Eliciting the problem domain Use case descriptions Use case generic description template Alternative templates Elements Pre and post conditions Main Success Scenario The conversation Alternate paths Exception paths Writing good use case descriptions Eliciting the detailed workflow with use case descriptions Additional information about use cases Analyzing Requirements with Use Cases Use case analysis on existing requirements Confirming and validating requirements with use cases Confirming and validating information with use cases Defining the actors and use cases in a set of requirements Creating the scenarios Essential (requirements) use case Use case level of detail Use Case Analysis Techniques Generalization and Specialization When to use generalization or specialization Generalization and specialization of actors Generalization and specialization of use cases Examples Associating generalizations Subtleties and guidelines Use Case Extensions The <> association The <> association Applying the extensions Incorporating extension points into use case descriptions Why use these extensions? Extensions or separate use cases Guidelines for extensions Applying use case extensions Patterns and anomalies o Redundant actors Linking hierarchies Granularity issues Non-user interface use cases Quality considerations Use case modeling errors to avoid Evaluating use case descriptions Use case quality checklist Relationship between Use Cases and Business Requirements Creating a Requirements Specification from Use Cases Flowing the conversation into requirements Mapping to functional specifications Adding non-functional requirements Relating use cases to other artifacts Wire diagrams and user interface specifications Tying use cases to test cases and scenarios Project plans and project schedules Relationship between Use Cases and Functional Specifications System use cases Reviewing business use cases Balancing use cases Use case realizations Expanding and explaining complexity Activity diagrams State Machine diagrams Sequence diagrams Activity Diagrams Applying what we know Extension points Use case chaining Identifying decision points Use Case Good Practices The documentation trail for use cases Use case re-use Use case checklist Summary What did we learn, and how can we implement this in our work environment?

Use deep learning, Computer Vision, and machine learning techniques to build an autonomous car with Python

Highlights of the Course Course Type: Online Learning Duration: 11 Hours 11 Minutes Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about retail analytics and management Understand the core competencies and principles of retail analytics and management Explore the various areas of retail analytics and management Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert retail manager Retail Analytics In Microsoft Excel Course Master the skills you need to propel your career forward in Microsoft excel. This course will equip you with the essential knowledge and skillset that will make you a confident office admin and take your career to the next level. This comprehensive retail analytics in Microsoft excel course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this retail analytics in Microsoft excel course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective Microsoft excel practice and equip you with the essential skills, confidence and competence to assist you in the Microsoft excel industry. You'll gain a solid understanding of the core competencies required to drive a successful career in Microsoft excel. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for office admin or for people who are aspiring to specialize in Microsoft excel. Enroll in this retail analytics in Microsoft excel course today and take the next step towards your personal and professional goals. Earn industry-recognized credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive retail analytics in Microsoft excel course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this Microsoft excel can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This retail analytics in Microsoft excel course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This retail analytics in Microsoft excel course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This retail analytics in Microsoft excel course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Course Introduction Introduction 00:03:00 Part 1: Forecasting Basics of Forecasting 00:05:00 Creating Linear Model with Trendlines 00:08:00 1.1 Getting Data Ready For Regression Model Gathering Business Knowledge 00:03:00 Data Exploration 00:03:00 The Data and the Data Dictionary 00:07:00 Univariate analysis and EDD 00:03:00 Discriptive Data Analytics in Excel 00:10:00 Outlier Treatment 00:04:00 Identifying and Treating Outliers in Excel 00:04:00 Missing Value Imputation 00:03:00 Identifying and Treating missing values in Excel 00:04:00 Variable Transformation in Excel 00:03:00 Dummy variable creation: Handling qualitative data 00:04:00 Dummy Variable Creation in Excel 00:07:00 Correlation Analysis 00:09:00 Creating Correlation Matrix in Excel 00:08:00 1.2 Forecasting Using Regression Model The Problem Statement 00:01:00 Basic Equations and Ordinary Least Squares (OLS) method 00:08:00 Assessing accuracy of predicted coefficients 00:14:00 Assessing Model Accuracy: RSE and R squared 00:07:00 Creating Simple Linear Regression model 00:02:00 Multiple Linear Regression 00:05:00 The F - statistic 00:08:00 Interpreting results of Categorical variables 00:05:00 Creating Multiple Linear Regression model 00:07:00 1.3 Handling Special Events Like Holiday Sales Forecasting in presence of special events 00:02:00 Excel: Running Linear Regression using Solver 00:08:00 Excel: Including the impact of Special Events 00:22:00 1.4 Identifying Seasonality & Trend for Forecasting Models to identify Trend & Seasonality 00:06:00 Excel: Additive model to identify Trend & Seasonality 00:09:00 Excel: Multiplicative model to identify Trend & Seasonality 00:06:00 Market Basket Analysis Market Basket and Lift - Introduction 00:08:00 Named Ranges - Excel 00:10:00 Indirect Function - Excel 00:05:00 2-way lift calculation in Excel 00:11:00 2-way lift calculation - Dynamic 00:07:00 2-way lift data table creation 00:07:00 3-way lift calculation 00:19:00 Store Layout optimization using Lift values 00:15:00 RFM (Recency, Frequency, Monetary) Analysis RFM (recency, frequency, monetary) Analysis 00:08:00 RFM Analysis in Excel- Part 1 00:16:00 RFM Analysis in Excel- Part 2 00:12:00 Part 2: Pricing Part 2: Pricing Steps of setting a Pricing policy 00:03:00 Different Pricing Objectives 00:07:00 2.1 Estimating Demand Estimating Demand 00:07:00 Forms of Demand Curve 00:02:00 Excel: Estimating Linear Demand Curve 00:08:00 Excel: Estimating Power Demand curve with Elasticity 00:05:00 Excel: Estimating Power Demand Curve with points 00:03:00 Subjective Demand curve 00:01:00 Excel: Estimating Subjective Demand Curve 00:02:00 2.3 Evaluating Pricing Strategies Price Bundling 00:07:00 Types of Bundling 00:08:00 The Bundling Problem 00:04:00 Excel: Solving Bundling problem Part 1 00:14:00 Excel: Solving Bundling problem Part 2 00:08:00 Non-Linear Pricing Strategies 00:03:00 Excel: Solving Bundling problem (Price Reversal) 00:08:00 3.1 Lifetime Customer Value Lifetime Customer Value - Key concepts 00:09:00 Lifetime Customer Value - Excel model 00:11:00 3.2 Variations And Sensitivity Analysis Sensitivity Analysis in Excel 00:07:00 Variations in finding customer value 00:07:00 Appendix 1: Excel Crash Course Basics 00:08:00 Worksheet Basics 00:16:00 Entering values and Formulas 00:07:00 Data Handling Basics - Cut, Copy and Paste 00:14:00 Saving and Printing - Basics 00:09:00 Basic Formula Operations 00:13:00 Mathematical Formulas 00:19:00 Textual Formulas 00:17:00 Logical Formulas 00:11:00 Date-Time Formulas 00:07:00 Lookup Formulas ( V Lookup, Hlookup, Index-Match ) 00:08:00 Data Tools 00:19:00 Formatting data and tables 00:18:00 Pivot Tables 00:08:00 Advance Excel- Solver, Data tables 00:15:00 Assessment Assessment - Retail Analytics In Microsoft Excel 00:10:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

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