Getting Started Effective management ensures quality patient care and organisational success in the rapidly evolving healthcare industry. The MSc Healthcare Management programme equips healthcare professionals with the necessary skills and knowledge for leadership and management roles. The MSc Healthcare Management programme offers a comprehensive learning experience that provides students with the knowledge, skills and emotional tools needed to meet the challenges of managing healthcare organisations. The MSc Healthcare Management programme provides healthcare professionals with a unique opportunity to excel in their careers and contribute to the ever-evolving field of healthcare management. This programme empowers students to become effective leaders by combining theoretical knowledge with practical application, driving positive change in healthcare organisations. Moreover, the programme enhances career prospects, offers specialisation in healthcare management, fosters networking opportunities and promotes practical application through real-world case studies. It prepares graduates for senior leadership roles, empowering them to make a meaningful impact in the healthcare industry. The programme comprises two phases; the first is the Qualifi Level 7 Diploma in Health and Social Care, awarded by Qualifi and delivered by the School of Business and Technology London. The second phase is the MSc Healthcare Management Top Up, awarded and delivered 100% online by Anglia Ruskin University. At Anglia Ruskin University, you will study through Canvas, a world-class online Learning Management System (LMS), accessed from your phone, pc or tablet at home or on the move. Canvas provides instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. After successfully completing your studies, you'll be invited to attend a graduation ceremony on campus at Anglia Ruskin University. If attending the ceremony in person is not possible, we'll arrange to send your certificate to you. School of Business and Technology London partners with Chestnut Education Group to promote this MSc Healthcare Management programme. About Awarding Body Anglia Ruskin University began in 1858 as the Cambridge School of Art founded by William Beaumont. It was then merged with the Cambridge shire College of Arts and Technology and the Essex Institute of Higher Education and was renamed Anglia Polytechnic. It was then given university status in 1992 and renamed Anglia Ruskin University in 2005. The university has campuses in the UK (Cambridge, Chelmsford, London and Peterborough), as well as they are partnered with institutions around the world including Berlin, Budapest, Trinidad, Singapore and Kuala Lumpur. Assessment Assignments and Project No examinations Entry Requirements Applicants should normally have a good first degree or equivalent and be working in or have recently worked within the arena of Management and Leadership in healthcare. If English is not your first language, you will be expected to demonstrate a certificated level of proficiency of at least IELTS 6.5 (Academic level) or equivalent English Language qualification, as recognised by Anglia Ruskin University. Progression Enrolling in the MSc Healthcare Management programme will give you comprehensive knowledge of health service management and leadership approaches. This programme will equip you with the skills to identify and develop corporate marketing strategies for health services and implement transformational change programmes. As a graduate, you will have various career paths available, including opportunities in public services or global non-governmental organisations. Furthermore, graduating from the programme doesn't have to mark the end of your educational journey. You may pursue a postgraduate research programme, such as the Professional Doctorate in Health and Social Care, to further advance your expertise in the field. Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. Structure Phase-1 - Qualifi Level 7 Diploma in Health and Social Care Programme Structure The QUALIFI Level 7 Diploma in Health and Social Care is made up of 120 credits, which equates to hours 1200 hours of TQT. All units will be internally assessed through written assignments. Unit HSC701: Health and Social Care Leadership Unit code: A/650/4192 Credit : 20 TQT : 200 This unit aims to offer learners a comprehensive grasp of leadership theories and styles, enabling them to critically assess the leadership role and choose and implement suitable leadership approaches. Unit HSC702: Managing People in Health and Social Care Unit code: D/650/4193 Credit : 20 TQT : 200 The objective of this unit is to empower the learner with the capability to comprehend the procedures associated with recruiting, managing, and nurturing individuals within the health and social care workplace. Unit HSC703: Managing Finance in the Health and Social Care Sector Unit code: F/650/4194 Credit : 20 TQT : 200 This unit addresses the essential knowledge and comprehension required for making financially informed decisions within health and social care organisations. Studying this unit while considering the local, national, and international legal frameworks and adhering to best practices related to finance is crucial. Unit HSC703: Managing Finance in the Health and Social Care Sector Unit code: F/650/4194 Credit : 20 TQT : 200 This unit addresses the essential knowledge and comprehension required for making financially informed decisions within health and social care organisations. Studying this unit while considering the local, national, and international legal frameworks and adhering to best practices related to finance is crucial. Unit HSC704: Health and Social Care Strategies and Policies Unit code: H/650/4195 Credit : 20 TQT : 200 This unit aims to delve into global health and social care policies and examine current political, social, and cultural factors influencing healthcare policy and strategy in both national and international contexts. Unit HSC705: Leading Change in Health and Social Care Unit code: J/650/4196 Credit : 20 TQT : 200 This unit aims to enhance learners' comprehension of people management within organisations, encompassing aspects such as recruitment, HR processes, performance management, rewards and recognition, and training and development. Unit HSC706: Research Methods for Healthcare Professionals Unit code: K/650/4197 Credit : 20 TQT : 200 This unit aims to cultivate learners' research skills, encompassing diverse research approaches, formulating research proposals, strategically planning research endeavours, data analysis and interpretation, and understanding the link between research and evidence-based practice. Phase-2 - MSc Healthcare Management Top Up Programme Structure Postgraduate Research Design Major Project (Dissertation) Delivery Methods The programme comprises two phases; the first is the Qualifi Level 7 Diploma in Health and Social Care, awarded by Qualifi and delivered by the School of Business and Technology London. The School of Business and Technology London offers flexible learning methods, including online and blended learning, allowing students to choose the mode of study that suits their preferences and schedules. The program is self-paced and facilitated through an advanced Learning Management System. Students can easily interact with tutors through the SBTL Support Desk Portal System for course material discussions, guidance, assistance, and assessment feedback on assignments. School of Business and Technology London provides exceptional support and infrastructure for online and blended learning. Students benefit from dedicated tutors who guide and support them throughout their learning journey, ensuring a high level of assistance. The second phase is the MSc Healthcare Management Top Up, awarded and delivered 100% online by Anglia Ruskin University. At Anglia Ruskin University, you will study through Canvas, a world-class online Learning Management System (LMS), accessed from your phone, pc or tablet at home or on the move. Canvas provides instant access to study materials, forums, and support from tutors and classmates, as well as enabling easy submission of your assignments. After successfully completing your studies, you'll be invited to attend a graduation ceremony on campus at Anglia Ruskin University. If attending the ceremony in person is not possible, we'll arrange to send your certificate to you. School of Business and Technology London partners with Chestnut Education Group to promote this MSc Healthcare Management programme. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.
Duration 5 Days 30 CPD hours This course is intended for Data Warehouse Administrator Database Administrators Support Engineer Technical Administrator Technical Consultant Overview Use Oracle Flashback Technologies to recover from human error Use Recovery Manager (RMAN) to create backups and perform recovery operations Use the Data Recovery Advisor to diagnose and repair failures Plan effective backup and recovery procedures Describe the Oracle Database architecture components related to backup and recovery operations Perform an encrypted database backup and restore Perform tablespace point-in-time recovery Configure the database for recoverability Describe Cloud Tooling for Backup and Recovery Describe Oracle Database backup methods and recovery operations that can be used to resolve database failure In this Oracle Database 12c R2: Backup and Recovery Workshop, students learn how to perform backup and recovery based on the related Oracle Database architecture components. Various backup, failure, restore, and recovery scenarios are provided so that students learn to evaluate their own recovery requirements and develop an appropriate strategy for backup and recovery procedures. This course includes an interactive workshop, with scenarios that provide participants with opportunities to diagnose and recover from several failure situations. Introduction Curriculum Context Assess your recovery requirements Categories of failures Oracle backup and recovery solutions Oracle Maximum Availability Architecture Oracle Secure Backup Benefits of using Oracle Data Guard Basic Workshop Architecture Getting Started Core Concepts of the Oracle Database, critical for Backup and Recovery Oracle DBA Tools for Backup and Recovery Connecting to Oracle Recovery Manager (RMAN) Configuring for Recoverablility RMAN commands Configuring and managing persistent settings Using the Fast Recovery Area (FRA) Control File Redo Log File Archiving Logs Using the RMAN Recovery Catalog Creating and Configuring the Recovery Catalog Managing Target Database Records in the Recovery Catalog Using RMAN Stored Scripts Maintaining and Protecting the Recovery Catalog Virtual Private Catalogs Backup Strategies and Terminology Backup Solutions Overview and Terminology Balancing Backup and Restore Requirements Backing Up Read-Only Tablespaces Data Warehouse Backup and Recovery: Best Practices Additional Backup Terminology Performing Backups RMAN Backup Types Incrementally Updated Backups Fast Incremental Backup Block Change Tracking Oracle-Suggested Backup Reporting on Backups Managing Backups Improving Your Backups Compressing Backups Using a Media Manager Backup and Restore for Very Large Files Creating RMAN Multi-section Backups, Proxy Copies, Duplexed Backup Sets and Backups of Backup Sets Creating and Managing Archival Backups Backing Up Recovery Files Backing Up the Control File to a Trace File Cataloging Additional Backup Files Using RMAN-Encrypted Backups Creating RMAN-Encrypted Backups Using Transparent-Mode Encryption Using Password-Mode Encryption Using Dual-Mode Encryption Diagnosing Failures Reducing Problem Diagnosis Time Automatic Diagnostic Repository Data Recovery Advisor Handling Block Corruption Restore and Recovery Concepts Restoring and Recovering Instance Failure and Instance/Crash Recovery Media Failure Complete Recovery (Overview) Point-in-Time Recovery (Overview) Recovery with the RESETLOGS Option Performing Recovery, Part I RMAN Recovery in NOARCHIVELOG Mode Performing Complete Recovery (of critical and noncritical data files) Restoring ASM Disk Groups Recovery with Image Files Performing Point-in-Time (PITR) or Incomplete Recovery Performing Recovery, Part II Recovery of Server Parameter File, Control File (One and All) Redo Log File Loss and Recovery Password Authentication File Re-creation Index, Read-Only Tablespace, and Temp file Recovery Restoring the Database to a New Host Disaster Recovery Restoring RMAN Encrypted Backups RMAN and Oracle Secure Backup Oracle Secure Backup Overview and Interface Options RMAN and OSB: Overview and Basic Process Flow Starting with Oracle Secure Backup Configuring Oracle Secure Backup for RMAN RMAN Backup and Restore Operations Oracle Secure Backup Jobs Displaying OSB log files and transcripts for RMAN activities Using Flashback Technologies Flashback Technology: Overview and Setup Using Flashback Technology to Query Data Flashback Table Flashback Transaction (Query and Back out) Flashback Drop and the Recycle Bin Flashback Data Archive Using Flashback Database Flashback Database Architecture Configuring Flashback Database Performing Flashback Database Best Practices for Flashback Database Transporting Data Transporting Data Across Platforms Transporting Data with Backup Sets Database Transport: Using Data Files Performing Point-in-Time Recovery When to use TSPITR TSPITR Architecture Performing RMAN TS Point-in-time Recovery Recovering Tables from Backups Duplicating a Database Using a Duplicate Database Duplicating Database with 'push' and 'pull' techniques Choosing Database Duplication Techniques Creating a Backup-up Based Duplicate Database Understanding the RMAN Duplication Operation RMAN Troubleshooting and Tuning Interpreting RMAN Message Output Tuning Principles Diagnosing Performance Bottlenecks RMAN Multiplexing Restore and Recovery Performance Best Practices Cloud Tooling for Backup and Recovery Backup Destinations Customize Backup Configuration On-Demand Backup and Recovery Oracle Backup Cloud Service Installing the Backup Module Backup and Recovery Workshop Workshop Structure and Approach Business Requirements for Database Availability and Procedures Diagnosing the Failures
Learn everything you need to know to be fully competent with Mac iOS. This syllabus takes you around the basics and then on another deep dive into all the elements. Discover things you never knew and speed up your experience using Mac iOS. Module 1: Introduction to Mac iOS and Hardware • Understanding the Mac ecosystem • Overview of Mac hardware components • Navigating the Mac interface Module 2: Mac Operating System (macOS) • Exploring the macOS interface • Customizing system preferences • File management and organization on macOS Module 3: Essential Mac Apps • Using Safari for web browsing • Effective web searching using search engines • Email management with Apple Mail • Calendar and task management with Apple Calendar Module 4: Software Installation and Updates • Installing and updating software applications • Managing and uninstalling programs • App Store and app installations Module 5: Productivity and Collaboration • Using iCloud for cloud-based storage and collaboration • Working with Notes, Reminders, and Messages • Collaborative document editing with iWork Module 6: Multimedia and Creativity • Basic image editing with Photos and Preview • Music creation with GarageBand • Creating multimedia presentations with Keynote Module 7: Troubleshooting and Maintenance • Identifying and resolving common Mac issues • Using Activity Monitor for performance monitoring • Maintenance tasks for macOS Module 8: Mac Security and Privacy • Overview of Mac security features • Online safety and privacy best practices • Protecting personal data and devices Module 9: Advanced Mac Features • Customizing the Dock and Menu Bar • Using Siri for voice commands and search • Continuity features for seamless device integration Module 10: Using AI and Chat GPT • Introduction to AI and Chat GPT technology • Exploring AI-powered features on Mac • Using Chat GPT for productivity and assistance Module 11: Browsing and Search Engines • Effective use of web browsers on macOS • Utilizing search engines for research • Online safety and privacy while browsing Module 12: Cybersecurity • Understanding cybersecurity threats • Protecting against malware and phishing attacks • Secure online practices and password management Module 13: Software Installation and Factory Reset • Installing and updating software applications • Factory resetting a Mac device • Data backup and recovery during resets Module 14: Final Projects and Assessment • Culminating projects showcasing Mac iOS skills • Practical exams assessing Mac software knowledge and skills • Preparing for industry-recognized certifications (optional) Please note that the duration and depth of each module can vary depending on the level of expertise required and the specific needs of the learners. Additionally, it's important to adapt the curriculum to the learners' proficiency levels, whether they are A Level/GCSE students or adult learners with different experience levels.
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
Overview Thrive in your workplace by gaining essential leadership & management skills through our all-inclusive Leadership & Management Diploma course. This comprehensive program is designed to equip you with the knowledge and expertise necessary to become a qualified leader, proficient in effective management practices. You will explore the fundamental differences between leadership and management, understand their significance, and learn how to navigate the complexities of organizational dynamics. Throughout the Leadership & Management Diploma course, you will delve into crucial topics such as conflict management and the various responsibilities that come with effective leadership & management. By engaging with practical scenarios and real-world applications, you'll develop advanced interpersonal communication skills that enable you to align your strategies and address management challenges swiftly and effectively. Enhance your career prospects by enrolling in the Leadership & Management Diploma today! This Leadership & Management Diploma course will provide you with the tools to excel in any leadership role and make a significant impact within your organization. Don't miss the opportunity to elevate your career in leadership & management. Key Features of the Course: FREE Leadership & Management Diploma CPD-accredited certificate Get a free student ID card with Leadership & Management Diploma training (£10 applicable for international delivery) Lifetime access to the Leadership & Management Diploma course materials The Leadership & Management Diploma program comes with 24/7 tutor support Get instant access to this Leadership & Management Diploma course Learn Leadership & Management Diploma training from anywhere in the world The Leadership & Management Diploma training is affordable and simple to understand The Leadership & Management Diploma training is entirely online How will I get my certificate? You may have to take a quiz or a written test online during or after the Leadership & Management Diploma 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 Leadership & Management Diploma. It is available to all students, of all academic backgrounds. Requirements Our Leadership & Management Diploma is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 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 With the Leadership & Management Diploma, you can explore a variety of rewarding career opportunities, including: Team Leader: £25,000 - £40,000 Project Manager: £30,000 - £50,000 Operations Manager: £35,000 - £60,000 Department Manager: £30,000 - £55,000 HR Manager: £35,000 - £60,000 General Manager: £40,000 - £70,000 Course Curriculum 1 sections • 20 lectures • 08:39:00 total length •Understanding Management and Leadership: 00:40:00 •Leadership Theories: 00:25:00 •Improving Management and Leadership Performance: 00:15:00 •High Performance Teams: 00:32:00 •Motivating Employees: 00:26:00 •Organisational Skills: 00:26:00 •Talent Management: 00:37:00 •Succession Planning: 00:24:00 •Business Process Management: 00:28:00 •Communication Skills: 00:27:00 •Negotiation Techniques: 00:15:00 •Managing Meetings and Giving Feedback: 00:21:00 •Managing Change: 00:22:00 •Time Management: 00:37:00 •Stress Management: 00:15:00 •Emotional Intelligence in Leadership: 00:32:00 •Managing Conflict: 00:14:00 •Dealing with Office Politics: 00:34:00 •Risk Management: 00:35:00 •Corporate Responsibility and Ethics: 00:14:00