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Whether you’re a board member or just curious about corporate governance, this AGRC certificate is for you! Learn what it takes for any firm to build and maintain a robust, dependable, and responsible corporate governance backbone with this self-paced, online certificate delivered by LGCA. The concept of corporate governance has featured regularly in discussions, both within the professional and academic community, since the 1990s and has become even more prominent following significant cases of corporate failure that had adverse effects on the global interconnected economy. Additionally, the Certificate places emphasis on how internal control mechanisms need to be designed and underlines how helpful the three lines of defence model may be. The certificate also covers the importance of maintaining strong and productive relations within the Board, ones that are based on trust and which allow for effective meetings and interaction to be achieved. Lastly, emphasis is placed on the modern concepts of Corporate Social Responsibility (CSR), Environmental Social Governance (ESG), and Sustainability, and how the Board needs to respond to these trends as they gain increased relevance and importance for the corporate world. Overall, the knowledge obtained by undertaking this Certificate is an invaluable asset for professionals looking to enhance their career prospects in Corporate Governance. The link between poor corporate governance practices and the excessive taking of risks that led to the downfall or bail-out of important financial institutions necessitated a discussion on how to strengthen corporate governance and protect the economy against similar cases in the future. Effectively, new regulatory requirements have been established, while existing codes of governance have been revised. Such efforts aim to focus on requirements that should be fulfilled by an organisation’s management body and enhance three areas of governance: remuneration, risk management, and internal control. In this programme, participants will review key definitions of corporate governance and the benefits associated with the implementation of good corporate governance practices. More specifically, participants will look in greater detail at the Board of Directors, covering the duties and responsibilities of Directors, the composition of the Board, the role of key post-holders, the many Board committees and how they are structured, and how a Board’s performance can be evaluated. Study method Online, self-paced Course format What's this? Reading material - PDF/e-book, slides, article/plain text Duration 15 hours Access to content 365 days Certification Certificate in Corporate Governance CPD 15 CPD hours / points Certificates AGRC Certificate in Corporate Governance - Free Additional info Exam(s) / assessment(s) is included in price Description The AGRC Certificate in Corporate Governance provides participants with a thorough understanding of a topic that has gained increasing significance and attention amongst corporations, regulators, and researchers. At the same, the Certificate offers guidance as to how corporations can best prepare in creating solid governance structures that will help them deal with the myriad of modern-day corporate challenges and risks. Syllabus: Introduction to Corporate Governance Definition of Corporate Governance Ethics and Governance Key Relevant Governance Theories Agency Theory Stakeholder Theory The Benefits of Corporate Governance Board of Directors Duties and Responsibilities of Directors Specific Requirements for Financial Institutions Board Appointments and Composition Independent and Non-Executive Directors (INEDs) The Importance of Diversity in a Board Committee Structure Board Committees Committee Structure Audit Committee Risk Committee Nominations Committee Remuneration Committees Key Post-Holders in a Board Chair of the Board Senior Independent Director (SID) CEO (Ex-Officio Board Member) Evaluation & Continuous Development Knowledge of Industry and OrganisationInternal Control Mechanisms Internal Controls and Risk Management Three-Lines of Defence model Intra-Board Relations Effective Meetings CSR, ESG and Sustainability Definitions of Relevant Terms Corporate Social Responsibility (CSR) Environmental Social Governance (ESG) Sustainability The Business Case for CSR, ESG, and Sustainability ESG, Sustainability, and the Role of the Board Format • Register at any time for this online, open Certificate • Study in your own time and at your own pace (you have up to 3 months to complete) • Assessed by online multiple-choice exam What is included • 15 hours of self-paced online interactive learning including analysis of 7 practical case studies • 1-year free AGRC membership • Online Exam and AGRC Certificate Who is this course for? This course is ideal for anyone wishing to be introduced to the main regulatory provisions in financial services and trends in corporate governance. Professionals carrying out the roles of directors, members of the Board, senior managers, lawyers, company secretaries, compliance and risk officers, and consultants may benefit from this course. It is also suitable for professionals pursuing regulatory CPDs in financial regulation. Requirements No previous knowledge or experience is required, although it is assumed that participants have good knowledge of English and sound educational background. Certificates AGRC Certificate in Corporate Governance Digital certificate - Included The certificate is issued upon successful passing of the final exam.

Creating Your Organization's Business Agility Strategy Optimally, your organization's business strategy and business agility strategy are completely coupled together, one seamlessly supporting the other. Practically, what many organizations experience today is a tug-of-war between their business strategy and this thing called 'business agility.' Or, a lack of business agility strategy altogether, leaving the business strategy more susceptible, and even fragile, when unforeseen changes inevitably occur. We need a way to think about business agility, coupled with business strategy, so that we can live into the reality of harnessing change for good. This session will expose you to a recently published body of work, Domains of Business Agility, which serves as a model for creating business agility strategy. Think of it as a skeleton, or a thinking tool. Used this way, the model allows leaders to answer the question, 'How much business agility do we need in various parts of our organization as a seamless support to our overall business strategy?' In this session, Lyssa Adkins, author of Coaching Agile Teams and Agile/Leadership Coach, leads you through the key steps for creating such a business agility/business strategy. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs.

Creating Your Organization's Business Agility Strategy Optimally, your organization's business strategy and business agility strategy are completely coupled together, one seamlessly supporting the other. Practically, what many organizations experience today is a tug-of-war between their business strategy and this thing called 'business agility.' Or, a lack of business agility strategy altogether, leaving the business strategy more susceptible, and even fragile, when unforeseen changes inevitably occur. We need a way to think about business agility, coupled with business strategy, so that we can live into the reality of harnessing change for good. This session will expose you to a recently published body of work, Domains of Business Agility, which serves as a model for creating business agility strategy. Think of it as a skeleton, or a thinking tool. Used this way, the model allows leaders to answer the question, 'How much business agility do we need in various parts of our organization as a seamless support to our overall business strategy?' In this session, Lyssa Adkins, author of Coaching Agile Teams and Agile/Leadership Coach, leads you through the key steps for creating such a business agility/business strategy. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs.

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

This course focuses on understanding all the basic theory and programming skills required as a data scientist, featuring 35+ practical case studies covering common business problems faced by them. This course seeks to fill all those gaps in knowledge that scare off beginners and simultaneously apply your knowledge of data science and deep learning to real-world business problems.

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Peer coaching is a cost-effective way to provide quality employee development to high-potential and emerging leaders. Learn about the behaviours that will ensure you are a great peer coach. You will understand why questions play an important role for effective coaching and how to use the correct questioning sequence for an effective coaching session. Learn the behaviours and steps under your control for achieving the end goal. Learning Objectives Explain the benefits of peer coaching, Implement behaviors of effective peer coaches, Apply the GROW model for sequencing questions in a coaching session Target Audience Managers, Team Leaders, Young Professionals, Sales Professionals, Customer Service Teams

Are you interested in sharing knowledge with others and gaining insightful conclusions from data? This online Power BI course is your comprehensive and in-depth introduction to this powerful software if you've ever been curious about the fascinating, artistic field of data analysis and visualisation. Microsoft Power BI has the potential to be your most effective tool. It comes with all of the features found in MS Excel, as well as many more. Power BI has a wide range of features and functionalities. By obtaining this Power BI training, you'll learn to make the most of all of Microsoft Power BI's features and produce insightful tables, graphs, and reports. Along with this Power BI course, you also receive a number of additional practical and supplemental courses in a package that will assist you in becoming an expert in the field of business and IT. With the supplementary business management course, you will acquire the technical abilities and business knowledge needed to put your skills to use in the industry. Working with various platform data, algorithms, and data structures all are part of the job description of a data analyst. As the course includes Data Structure and Graph theory algorithm courses, this package will aid in your skill improvement as a data analyst. These courses in this bundle will advance your Power BI proficiency and allow you to perform more reasonable experimentation with this Power BI tool. Along with this Power BI course, you will get 10 premium courses, an original hardcopy, 11 PDF Certificates (Main Course + Additional Courses) Student ID card as gifts. This Power BI Bundle Consists of the following Premium courses: Course 01: Complete Microsoft Power BI 2021 Course 02: Data Structures Complete Course Course 03: Computer Science: Graph Theory Algorithms Course 04: Introduction to Data Analysis Course 05: Business Analysis Level 3 Course 06: Strategic Business Management Course 07: Enterprise Risk: Identification and Mitigation Level 2 Course 08: GDPR Data Protection Level 5 Course 09: Functional Skills IT Course 10: Decision Making and Critical Thinking Course 11: Time Management With the help of this excellent package, you can develop a professional career in the IT sector while also increasing your own personal growth. To summarise your learning objectives of this bundle: you will be able to, Identify the Power BI components and workflows you need to know Create a data model in Power BI Translate data into graphics using Power BI features Understand different types of data structures and algorithms Perform data analysis and measure the performance of your model Acquire business knowledge about the IT industry Gain time management skills for working as a professional in the corporate sector Your new data visualisation abilities can be used in almost any field of study or employment, including data science, finance, and even graphic design. This can lead to a wide range of professional prospects. So enrol in this course right away to jumpstart your career. Benefits you'll get choosing Apex Learning: Pay once and get lifetime access to 11 CPD courses Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID for the course included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules of course designed by expert instructors Learn about course at your ease - anytime, from anywhere Study the course from your computer, tablet or mobile device CPD accredited course - improve the chance of gaining professional skills Curriculum: Course 01: Complete Microsoft Power BI 2021 Introduction Preparing our Project Data Transformation - The Query Editor Data Transformation - Advanced Creating a Data Model Data Visualization Power BI & Python Storytelling with Data DAX - The Essentials DAX - The CALCULATE function Power BI Service - Power BI Cloud Row-Level Security More data sources Next steps to improve & stay up to date How will I get my Certificate? After successfully completing the Power BI course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) PS The delivery charge inside the UK is £3.99, and the international students have to pay £9.99. CPD 115 CPD hours / points Accredited by CPD Quality Standards Who is this course for? There are no strict requirements, and any experienced computer user is expected to be able to finish the project. This bundle will also be beneficial for, Students from all academic disciplines Students interested in powerful data analysis techniques Anyone in business who wants to transform data into information Users of Excel who want to advance their reporting and analysis Requirements This Power BI course has been designed to be fully compatible with tablets and smartphones. Career path These different credentials will add value to your resume and give you access to a wide range of industries, including, but not limited to, Data analysis IT industry Business and management Freelance worker Entrepreneur Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Complete Microsoft Power BI) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Discover the power of data science and machine learning with Python! Learn essential techniques, algorithms, and tools to analyze data, build predictive models, and unlock insights. Dive into hands-on projects, from data manipulation to advanced machine learning applications. Elevate your skills and unleash the potential of Python for data-driven decision-making.

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