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The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

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Hone your operational leadership skills and ensure a streamlined business process to increase productivity. Gain mastery of Negotiation Techniques, Supply Chain Management.

In this course, you will learn how to author machine learning models in Python without the aid of frameworks or libraries from scratch. Discover the process of loading data, evaluating models, and implementing machine learning algorithms.

Getting Started The ILM Level 2 Award in Effective Mentoring Skills course is designed for individuals who are seeking to acquire comprehensive knowledge and practical skills to effectively mentor others in various settings. Whether it's within an organisation, the voluntary sector, or community groups, this course aims to equip you with the necessary expertise to support and guide others in their career development and educational pursuits. By delving into the particulars of mentoring, you will gain the insight and tools needed to make a meaningful impact within your respective spheres of influence. Key Benefits For Learners Gain a comprehensive insight into the role and nature of mentoring, including its impact on professional development and organisational success. Acquire and apply advanced mentoring skills to critically evaluate personal performance, while utilising key listening and questioning techniques to facilitate meaningful and impactful interactions. Develop a thorough understanding of how to strategically organise mentoring activities and meticulously plan and execute effective mentoring sessions that drive tangible results. Engage in reflective practices to assess personal performance, define objectives, monitor progress, and identify necessary actions for continuous improvement and success. For Organisations Enables employees to acquire the necessary skills and knowledge to become effective mentors within their respective roles. Fosters a culture of mentoring within the organisation by introducing key skills and techniques essential for successful mentoring. Key Highlights This qualification is intended for learners who wish to start a career in mentoring in an organizational context. It is also ideal for existing coaches and mentors. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximise future opportunities. Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exam With the School of Business and Technology London, you can complete the qualification at your own pace choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide you with comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways The ILM Level 2 Award in Effective Mentoring Skills course can open many career pathways including, but not limited to: Training Manager, with an estimated average salary of £30,163 per annum Academic Mentor, with an estimated average salary of £33,156 per annum Business Mentor, with an estimated average salary of £37,216 per annum About Awarding Body Institute of Leadership & Management (ILM) is a professional body that helps people worldwide improve their leadership capabilities and advance their careers. All ILM qualifications are awarded by The City and Guilds of London Institute, founded in 1878 and incorporated into the Royal Charter. ILM qualifications are regulated and approved by Ofqual, the governing body for qualifications in the UK. What is included? Learn 100% online at your own pace Dedicated support from expert tutors Dedicated Support Desk Portal: You can raise queries, request tutor support and ask for a call back whenever you need guidance and assistance. Elevate Knowledge: Your tutors will provide formative assessment feedback for each module, helping you improve your achievements throughout the program Schedule online personal tutor meetings whenever you want, which will help you get the most out of your studies and provide guidance, support and encouragement 6 months support period 24-hour access to the online learning platform 'MyLearnDirect' Schedule live online classes for each module at your convenience. (Blended learning only) Quality learning resources and study guides developed by ILM-approved tutors. All assessment materials are conveniently accessible through the online learning platform 'MyLearnDirect' Induction: We offer online and flexible learning induction to help you settle in and prepare for your online studies ILM Membership - You will receive 12 months of the Institute of Leadership & Management membership, bringing access to a wealth of resources to support your leadership development. ILM Digital credentials - Validate your skills and share achievements anywhere, anytime using Digital Credentials 25% off membership with EMCC UK for all ILM learners studying for a coaching and mentoring qualification. Assessment For each module you study, you will complete a written assignment of 1500-2000 words and submit it online at your MyLearnDirect learning portal. The submitted assignments will be assessed by your ILM-approved tutor. Entry Requirements The ILM Level 2 Award in Effective Mentoring Skills course is designed for individuals who wish to understand mentoring and develop their mentoring skills to effectively mentor others. To be eligible for this course, you must: Be 18 years of age and over Have some work experience as a mentor or related role Possess the ability to complete the Level 2 course Our friendly admissions advisors will provide the best advice, considering your needs and goals.  Why gain a ILM Qualification? The ILM Level 2 Award in Effective Mentoring Skills course is designed for individuals who wish to understand mentoring and develop their mentoring skills to effectively mentor others. The course is designed to provide in-depth knowledge and practical skills in the field of mentoring. It consists of two comprehensive modules: "Understanding Mentoring" and "Developing Mentoring Skills." These modules cover a wide range of topics including the principles of effective mentoring, communication techniques, goal setting, feedback methods, and strategies for building successful mentoring relationships. By completing the course, you will gain a thorough understanding of mentoring and develop the necessary skills to become successful mentors. Successful completion of the course could lead you to progression to a range of qualifications including: • ILM Level 3 Certificate in Effective Coaching and Mentoring • ILM Level 3 Award or Certificate in Leadership & Management ILM graduates achieve remarkable things: An impressive 70,000 people take ILM qualifications every year, with 93% of employers agreeing that their managers improved after completion. Through the collaboration with European Mentoring and Coaching Council UK (EMCC UK), both existing ILM coaching and mentoring learners and those newly qualified coaches/mentors will have access to the membership of the Council at a discounted price (25% off EMCC UK annual membership fee), plus up-to-date guidance, thought leading support via joint webinars and CPD events. An ILM level 3 learners would be an affiliate EMCC UK member. Whilst an ILM level 5 leaners would fall into the associate membership and ILM level 7 learners would either qualify for the associate or professional membership. ILM learners who successfully become an EMCC UK member will have access to their resources. ILM learners will also receive documents including competency frameworks as well as a range of free resources including access to the International Journal, free e-books, discounted publications and research papers. ILM Membership - All ILM learners receive a minimum of 12 months membership of the Institute of Leadership & Management, bringing access to a wealth of resources to support their leadership development ILM Digital credentials - Validate skills and share achievements anywhere, anytime using Digital Credentials 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. UNIT1- Understanding Mentoring Reference No : 8584-200 Credit : 2 || TQT : 20 LEARNING OUTCOME 1. Understand the role of the mentor and the benefits of mentoring. 2. Understand what makes a mentor effective in their role. 3. Understand how to organise mentoring. UNIT2- Developing Mentoring Skills Reference No : 8584-201 Credit : 3 || TQT : 30 LEARNING OUTCOME 1. Be able to commence mentoring sessions to develop an individual. 2. Be able to undertake 3 hours of effective mentoring. 3. Be able to review their own performance as a mentor. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. 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.

Our ISO 9001:2015 QMS Clauses Awareness course is a comprehensive program covering all ten clauses of the standard.

Embarking on the "New Manager Course" is imperative in the contemporary world, where effective leadership is the linchpin of organizational success. This course equips aspiring managers with vital skills such as communication, performance management, and adaptive leadership styles. In a job market with a 15% surge in demand for skilled new manager, acquiring these competencies is not just beneficial but essential. The average annual salary for new manager in the UK, hovering around £45,000, makes this Management for New Manager course a gateway to lucrative opportunities. With modules focusing on self-care, problem-solving, and embracing change, the New Manager Course addresses contemporary challenges. Graduates emerge well-prepared to navigate uncertainties and contribute significantly to the evolving landscape of modern management. Don't miss the chance to elevate your career and step into the world of new manager, where competence is key. Key Features This Management for New Manager Course Includes: This Management for New Manager Course is CPD Certified. Free Certificate Developed by Specialist Lifetime Access Course Curriculum Management for New Manager Module 01: Effective Management: An Overview Module 02: Building Effective Communication and Relationships Module 03: Performance Management and Goal Setting Module 04: Effective Delegation and Time Management Module 05: Leadership Adaptability and Styles Module 06: Conflict Resolution and Team Building Module 07: Managerial Self-Care and Personal Development Module 08: Embracing Change and Uncertainty Module 09: Problem-Solving Strategies Module 10: The Art of Coaching Module 11: Toolkit for New Managers Learning Outcomes: After completing this Management for New Manager Course, you will be able to: Enhance understanding of effective management principles for new manager. Develop robust communication and relationship-building skills crucial for management roles. Master goal setting, performance management, delegation, and time management techniques. Explore various leadership styles and cultivate adaptability in leadership approaches. Acquire strategies for team building, conflict resolution, and fostering collaboration. Implement personal development practices and self-care routines to sustain effectiveness. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Management for New Manager course is accessible to anyone eager to learn more about this topic. Through this course, you'll gain a solid understanding of Management for New Manager. Moreover, this course is ideal for: Aspiring or newly appointed managers seeking foundational management skills. Professionals transitioning into managerial roles for the first time. Individuals aiming to excel in leadership positions within their organisations. Graduates or mid-career professionals stepping into managerial responsibilities. Team members identified for managerial advancement and skill development. Requirements There are no requirements needed to enrol into this Management for New Manager course. We welcome individuals from all backgrounds and levels of experience to enrol into this Management for New Manager course. Career path After finishing this Management for New Manager course you will have multiple job opportunities waiting for you. Some of the following Job sectors of Management for New Manager are: Project Coordinator - £25K to 35K/year. Sales Manager - £30K to 50K/year. Operations Supervisor - £26K to 40K/year. HR Advisor - £24K to 38K/year. Retail Store Manager - £22K to 40K/year. Certificates Digital certificate Digital certificate - Included Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Course overview If you wish to receive more hotel bookings, focus on revenue management. The Fundamentals of Revenue Management course will guide you through implementing revenue management strategies and techniques to grow your hotel business.  Effective revenue management helps to understand the market, predict customer demands and implement better pricing strategies. Through The Fundamentals of Revenue Management course, you will get equipped with the fundamental skills to boost hotel revenues. It will educate you on the key performance indicator in hotel revenue management. You will learn the process of forecasting and pricing strategies of hotel revenue management. In addition, you will learn how to build an effective overbooking strategy to increase profitability.  Take all the necessary steps to promote your hotel by enrolling right away! Learning outcomes Understand the fundamentals of hotel revenue management Learn about revenue management key performance indicators Learn about the profitable distribution strategy Strengthen your knowledge of pricing in revenue management Learn the overbooking practices for profitability Learn the best practices to promote your hotel Who is this course for Aspiring professionals interested in learning the revenue management strategies to boost hotel sales can take this The Fundamentals of Revenue Management course. The in-demand skills gained from this training will provide excellent opportunities for a career in the hotel industry.  Entry Requirement This course is available to all learners of all academic backgrounds. Learners should be aged 16 or over. Good understanding of English language, numeracy and ICT skills are required to take this course. Certification After you have successfully completed the course, you will obtain an Accredited Certificate of Achievement. And, you will also receive a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy for £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why Choose Us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos and materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; United Kingdom & internationally recognized accredited qualification; Access to course content on mobile, tablet and desktop from anywhere, anytime; Substantial career advancement opportunities; 24/7 student support via email. Career Path The Fundamentals of Revenue Management Course provides essential skills that will make you more effective in your role. It would be beneficial for any related profession in the industry, such as: Hotel Manager Reservations and Revenue Manager Hotel General Manager Business Development Manager Hotel Owner The Fundamentals of Revenue Management Module 1. Fundamentals of Hotel Revenue Management 00:18:00 Module 2. Importance of Revenue Management 00:24:00 Module 3. Key Performance Indicator in Revenue Management 00:20:00 Module 4. Forecasting of Hotel Revenue Management 00:23:00 Module 5. Pricing of Hotel Revenue Management 00:24:00 Module 6. Profitable Distribution Strategy 00:19:00 Module 7. Overbooking Practices in Hotel Revenue Management 00:13:00 Module 8. How to Promote your Hotel 00:18:00 Module 9. Customer and Other Essential Factors 00:15:00 Module 10. The Future of Hotel Revenue Management in UK 00:24:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Facilities management professionals are responsible for services that support business. Their roles can cover management of a wide range of areas including health and safety, risk management, business continuity, procurement, sustainability, space planning, energy, property and asset management. They are typically responsible for activities such as catering, cleaning, building maintenance, environmental services, security and reception. The Level 5 qualifications will provide the skills needed to complete complex tasks and take on responsibility for planning and delivering solutions while developing your specialised knowledge of the profession. It is for you if you are at a middle or senior management level and responsible for more complex functions, or if you are aspiring to these roles and looking to stretch and develop.