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Are you looking to enhance your Credit Control skills? If yes, then you have come to the right place. Our comprehensive course on Credit Control will assist you in producing the best possible outcome by mastering the Credit Control skills. The Credit Control course is for those who want to be successful. In the Credit Control course, you will learn the essential knowledge needed to become well versed in Credit Control. Our Credit Control course starts with the basics of Credit Control and gradually progresses towards advanced topics. Therefore, each lesson of this Credit Control course is intuitive and easy to understand. Curriculum Breakdown of the Credit Control Course Module 01: Introduction To Credit Control Module 02: Credit Management Module 03: Risk Assessment and Credit Scoring Module 04: Debt Management Module 05: Customer Communication Module 06: Credit Control Compliance Module 07: Financial Analysis And Reporting Module 08: Credit Control Tools And Technologies Why would you choose the Credit Control course: Lifetime access to Credit Control course materials Full tutor support is available from Monday to Friday with the Credit Control course Gain a complete understanding of Credit Control course Accessible, informative Credit Control learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Credit Control course Study Credit Control in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Credit Control course CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Credit Control course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Credit Control. Requirements To enrol in this Credit Control course, all you need is a basic understanding of the English Language and an internet connection. Career path The Credit Control course will enhance your knowledge and improve your confidence. Credit Controller: £20,000 to £35,000 per year Collections Specialist: £22,000 to £40,000 per year Accounts Receivable Clerk: £18,000 to £30,000 per year Credit Analyst: £25,000 to £45,000 per year Financial Controller: £40,000 to £70,000 per year Credit Manager: £30,000 to £60,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

Overview This comprehensive course on Computer Science: Graph Theory Algorithms will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Computer Science: Graph Theory Algorithms comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Computer Science: Graph Theory Algorithms. It is available to all students, of all academic backgrounds. Requirements Our Computer Science: Graph Theory Algorithms is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 17 sections • 44 lectures • 08:37:00 total length •Promo: 00:03:00 •Introduction: 00:14:00 •Common Problem: 00:10:00 •Depth First Search: 00:11:00 •Breadth First Search: 00:08:00 •Breadth First Search Shortest Path on a Grid: 00:17:00 •Storage and Representation of Trees: 00:10:00 •Beginner Tree Algorithms: 00:10:00 •Rooting Tree: 00:05:00 •Center(s) of a Tree: 00:06:00 •Isomorphisms in Trees: 00:11:00 •Isomorphisms in Trees Source Code: 00:10:00 •Lowest Common Ancestor: 00:17:00 •Topological Sort: 00:14:00 •Shortest and Longest Paths on DAGs: 00:10:00 •Khan's Algorithm: 00:13:00 •Dijkstra's Shortest Path Algorithm: 00:25:00 •Dijkstra's Shortest Path Algorithm Source Code: 00:09:00 •Bellman-Ford Algorithm: 00:15:00 •Floyd-Warshall Algorithm: 00:16:00 •Floyd-Warshall Algorithm Source Code: 00:09:00 •Algorithm to Find Bridges and Articulation Points: 00:20:00 •Algorithm to Find Bridges and Articulation Points Source Code: 00:09:00 •Tarjan's Algorithm for Finding Strongly Connected Components: 00:17:00 •Tarjan's Algorithm for Finding Strongly Connected Components Source Code: 00:07:00 •Travelling Salesman Problem (TSP) with Dynamic Programming: 00:21:00 •Travelling Salesman Problem (TSP) with Dynamic Programming Source Code: 00:14:00 •Existence of Eulerian Paths and Circuit: 00:10:00 •Finding Eulerian Paths and Circuits: 00:16:00 •Eulerian Paths Source Code: 00:08:00 •Prim's Minimum Spanning Tree Algorithm (Lazy Version): 00:15:00 •Prim's Minimum Spanning Tree Algorithm ( Eager Version): 00:15:00 •Prim's Minimum Spanning Tree Algorithm Source Code ( Eager Version): 00:09:00 •Max Flow Ford-Fulkerson Method: 00:13:00 •Max Flow Ford-Fulkerson Method Source Code: 00:17:00 •Network Flow: Unweighted Bipartite Graph Matching: 00:11:00 •Network Flow: Mice and Owls: 00:08:00 •Network Flow: Elementary Math: 00:11:00 •Network Flow: Edmond-Karp Algorithm: 00:06:00 •Network Flow: Edmond-Karp Algorithm Source Code: 00:10:00 •Network Flow: Capacity Scaling: 00:10:00 •Network Flow: Capacity Scaling Source Code: 00:06:00 •Network Flow: Dinic's Algorithm: 00:12:00 •Network Flow: Dinic's Algorithm Source Code: 00:09:00

Overview This comprehensive course on Sexual Harassment Awareness Training will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Sexual Harassment Awareness Training  comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Sexual Harassment Awareness Training. It is available to all students, of all academic backgrounds. Requirements Our Sexual Harassment Awareness Training is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 8 sections • 8 lectures • 01:16:00 total length •What is Sexual Harassment?: 00:10:00 •Sexual Harassment in the workplace: 00:12:00 •The law and sexual Harassment: 00:08:00 •Addressing Sexual Harassment: 00:10:00 •Prevent Sexual Harassment at work: 00:10:00 •Policies and procedures: 00:08:00 •How to Deal with Sexual Harassment in the Workplace: 00:08:00 •Mediation and the Aftermath: 00:10:00

Overview This comprehensive course on Testing using SOAP UI will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Testing using SOAP UI comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Testing using SOAP UI. It is available to all students, of all academic backgrounds. Requirements Our Testing using SOAP UI is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 2 sections • 9 lectures • 04:07:00 total length •Module 01: Introduction to SOAP UI: 00:15:00 •Module 02: Installation instructions for SOAP UI: 00:22:00 •Module 03: Various Components in SOAP UI: 00:30:00 •Module 04: WSDL Testing in SOAP UI: 00:44:00 •Module 05: Load Testing in SOAP UI: 00:34:00 •Module 06: Security Testing in SOAP UI: 00:34:00 •Module 07: REST Testing in SOAP U: 00:42:00 •Module 08: Functional Testing in SOAP UI: 00:26:00 •Assignment - Testing using SOAP UI: 00:00:00

Overview Make a massive difference to someone's quality of life and boost your potential in an exciting new career path. This innovative course is designed to train anyone to become an effective and qualified Life Coach, helping people to achieve their personal goals. The Coaching & Mentoringcourse will teach you much more than just people management. You will learn to develop excellent communication skills, understand neuro-linguistic programming, read body language, provide motivation and emotional support, and recognise success. Alongside this, you will be taught how to seize business opportunities with this skill, and thrive in a growing industry. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment in this Coaching & Mentoring. It is available to all students, of all academic backgrounds. Requirements Our Coaching & Mentoring 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 1 sections • 8 lectures • 04:33:00 total length •Module 1: Introduction to Coaching and Mentoring: 00:28:00 •Module 2: Coaching and Mentoring: Objectives & Processes: 00:33:00 •Module 3: Ethical Aspects of Coaching and Mentoring: 00:35:00 •Module 4: Coaching and Mentoring Models: 01:01:00 •Module 5: Effective Communication Skills: 00:28:00 •Module 6: Personal Skills: 00:27:00 •Module 7: Management Skills: 00:26:00 •Module 8: Functional Skills: 00:35:00

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:04:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:06:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Overview This comprehensive course on Graphic Design Using Canva will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Graphic Design Using Canva comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Graphic Design Using Canva. It is available to all students, of all academic backgrounds. Requirements Our Graphic Design Using Canva is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 6 sections • 17 lectures • 03:24:00 total length •Introduction to Adobe Colour: 00:03:00 •Adobe Colour Lesson 2: 00:03:00 •Adobe Colour Lesson 3: 00:05:00 •How to Use Canva: 00:45:00 •How to design a logo on Canva: 00:11:00 •Canva text-to-Image AI for NFT: 00:10:00 •Poster designs on Canva: 00:13:00 •How to Use Canva templates: 00:14:00 •Snapseed: 00:14:00 •Double Exposure: 00:16:00 •Exposure Adjustments: 00:06:00 •Colour Splash Part-1: 00:15:00 •Colour Splash Part-2: 00:17:00 •Create Flyer Designs on Canva: 00:28:00 •How to Work with Layers in Canva App: 00:02:00 •Creating a 3D Mockup Design with your Phone: 00:02:00 •Assignment - Graphic Design Using Canva: 00:00:00

Overview This comprehensive course on Data Science with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science with Python comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 3 sections • 6 lectures • 01:15:00 total length •Module 01: Introduction to Python Data Science: 00:03:00 •Module 02: Environment Setup: 00:10:00 •Module 01: Numpy package for calculations: 00:16:00 •Module 02: Panda package for Data cleaning: 00:19:00 •Module 01: Matplotlib Data Visualization Part 1: 00:16:00 •Module 02: Matplotlib Data Visualization Part 2: 00:11:00

Overview This comprehensive course on Decision Making and Critical Thinking will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Decision Making and Critical Thinking comes with accredited certification which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is this course for? There is no experience or previous qualifications required for enrolment on this Decision Making and Critical Thinking. It is available to all students, of all academic backgrounds. Requirements Our Decision Making and Critical Thinking 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 10 lectures • 03:22:00 total length •Introduction to Critical Thinking: 00:21:00 •Critical Thinking and the Judgment of Claims: 00:18:00 •Benefits and Barriers of Critical Thinking: 00:32:00 •Importance of Critical Thinking: 00:16:00 •Recognising a Critical Thinker: 00:22:00 •What Are the Critical Thinking Steps?: 00:17:00 •Critical Thinking Strategies: 00:25:00 •Problem-Solving Through Critical Thinking: 00:25:00 •Decision Making with Critical Thinking: 00:26:00 •Assignment - Decision Making and Critical Thinking: 00:00:00