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Root Cause Analysis (RCA) is used to analyse the root causes of focus events with both positive and negative outcomes, but it is most commonly used for the analysis of failures and incidents. Causes for such events can be varied in nature, including design processes and techniques, organizational characteristics, human aspects and external events. RCA can be used for investigating the causes of non-conformances in quality (and other) management systems as well as for failure analysis, for example in maintenance or equipment testing.

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

💼 Invoice Clerk Training Course Overview: Mastering Efficiency in Financial Operations Are you eager to embark on a career in financial administration and enhance your organizational skills? Look no further than our comprehensive 'Invoice Clerk Training' course. Tailored to equip you with the essential knowledge and skills, this course is your key to becoming a proficient and detail-oriented invoice clerk. 📑 Module 1: Introduction to Invoice Clerk Training Dive into the world of invoice processing with a comprehensive introduction to the roles and responsibilities of an invoice clerk. Understand the significance of accurate financial record-keeping and the pivotal role you play in ensuring the financial health of an organization. 📊 Module 2: Basic Accounting Principles Build a solid foundation in accounting principles essential for effective invoice management. Learn the fundamentals of debits and credits, financial statements, and the overall accounting framework that forms the backbone of successful financial operations. 💻 Module 3: Invoice Processing Become a master of efficiency in handling invoices from creation to reconciliation. Explore best practices in invoice validation, coding, and approval processes. Gain hands-on experience with various invoice processing systems and tools, ensuring accuracy and compliance with financial regulations. 📞 Module 4: Communication and Customer Service Elevate your interpersonal skills to enhance communication and customer service in the financial realm. Understand the importance of clear communication with vendors, internal teams, and other stakeholders. Develop strategies for effective issue resolution, creating a positive and collaborative environment. 🕰️ Module 5: Time Management and Organization Maximize your productivity and effectiveness as an invoice clerk with advanced time management and organizational techniques. Learn to prioritize tasks, manage deadlines, and create systems that streamline workflow, ensuring you meet the demands of a dynamic financial landscape. 🎓 Why Choose Our Invoice Clerk Training Course? Practical Application: Hands-on exercises and simulations for real-world experience. Industry-Relevant Content: Stay updated with the latest trends and technologies in financial administration. Expert Guidance: Learn from seasoned professionals with extensive experience in invoice management. Career Advancement: Open doors to exciting opportunities in finance and accounting. 📈 Enroll Now and Master the Art of Invoice Management! Don't miss the chance to propel your career forward as a skilled and efficient invoice clerk. Our Invoice Clerk Training course is your gateway to success in the world of financial administration. Enroll now and unlock the skills that will set you apart in this dynamic and rewarding field! Course Curriculum Module 1_ Introduction to Invoice Clerk Training. Introduction to Invoice Clerk Training. 00:00 Module 2_ Basic Accounting Principles. Basic Accounting Principles. 00:00 Module 3_ Invoice Processing. Invoice Processing. 00:00 Module 4_ Communication and Customer Service. Communication and Customer Service. 00:00 Module 5_ Time Management and Organization. Time Management and Organization. 00:00

This course covers all the basics to more advanced features and dives into all the little details about Hasura. Hasura provides a platform to create your GraphQL backends easier and faster than you ever thought possible without writing a single line of code!

Explore the intricacies of Dialectical Behaviour Therapy (DBT) in our comprehensive course. From foundational principles to practical applications, gain expertise in mindfulness, emotion regulation, interpersonal effectiveness, and distress tolerance skills. Learn to implement DBT ethically in diverse clinical settings and with specific populations. Elevate your therapeutic practice with evidence-based strategies. Join us for a transformative learning experience.

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Duco Digital Training's course in BCS Requirements Engineering Practitioner develops your skills in the understanding and application of elicitation, analysis and management of business analysis requirements.

🚀 Unlock Your Business Potential with 'Strategic Market Profiling: Identifying Your Ideal Audience' Online Course! 🚀   Are you tired of aimlessly marketing to everyone and anyone, hoping to hit the right audience? It's time to take control of your business's destiny with our groundbreaking online course: 'Strategic Market Profiling.'   🎓 MODULE 1: Introduction Dive into the fundamentals of Strategic Market Profiling. Understand why identifying your ideal audience is the key to unlocking unparalleled success in your business. Learn the secrets of market segmentation and how it can transform your marketing strategy. 🎯 MODULE 2: Importance of Your Target Market Discover the profound impact a well-defined target market can have on your business. Uncover the hidden opportunities and advantages that come with narrowing your focus. Learn from real-world case studies and success stories that showcase the power of a targeted approach. 🔍 MODULE 3: Target Market Framework Get hands-on with the Target Market Framework, a step-by-step guide to crafting a profile that speaks directly to your ideal audience. Learn how to gather and analyze crucial data, creating a roadmap that ensures your marketing efforts hit the bullseye every time. 🛠️ MODULE 4: Workshop Apply your newfound knowledge in our interactive workshop. Walk away with a comprehensive target market profile for your business. Receive personalized feedback and insights from industry experts. This is where theory meets practice, setting you on the path to marketing mastery.   🌟 What You'll Gain: ✅ In-depth understanding of market profiling ✅ Ability to identify and analyze your ideal audience ✅ Tailored strategies for targeted marketing ✅ Practical skills through hands-on workshops ✅ Access to a community of like-minded professionals   🚨 Don't let your marketing efforts go to waste! Enroll now and revolutionize the way you approach your audience. Seize the opportunity to elevate your business to new heights!   🎓 Invest in your success today! Click the link to enroll now: [Enroll Now] 🎓   Course Curriculum Module 1- Introduction Target Market Essentials 00:00 Module 2- Importance of Your Target Market Why is Your Target Market So Important 00:00 Module 3- Target Market Framework Define Your Target Market 00:00 Step 1 - Define Standard Attributes - Demographics 00:00 Step 1 (con't) - Define Standard Attributes - More Demographics 00:00 Step 1 (con't) - Define Standard Attributes - Psychographics 00:00 Step 2 - Develop Custom Attributes 00:00 Step 3 - Validation 00:00 Step 4 - Adjust Your Strategy 00:00 Module 4- Workshop Workshop - Devleoping Your Target Market 00:00

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

Microsoft Excel 2016 Advanced is one of our best selling and most popular course. This course is suitable for anyone aspiring to or already working in Microsoft Excel and looks at skills needed to improve Microsoft Excel. By taking this course you will gain the necessary skills to perform effectively in this field. The Microsoft Excel 2016 Advanced is organised into 6 modules and includes everything you need to become successful in this profession. To make this course more accessible for you, we have designed it for both part-time and full-time students. You can study at your own pace or become an expert in just 8hours! If you require support, our experienced tutors are always available to help you throughout the comprehensive syllabus of this course and answer all your queries through email. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Course Content Automating Worksheet Functionality Update Workbook Properties 00:15:00 Activity-Update Workbook Properties 00:05:00 Create and Edit a Macro 00:15:00 Activity-Create and Edit a Macro 00:05:00 Apply Conditional Formatting 00:30:00 Activity-Apply Conditional Formatting 00:05:00 Add Data Validation Criteria 00:15:00 Activity-Add Data Validation Criteriaty 00:05:00 Auditing Worksheets Trace Cells 00:15:00 Activity-Trace Cells 00:05:00 Troubleshoot Invalid Data and Formula Errors 00:15:00 Activity-Troubleshoot Invalid Data and Formula Errors 00:05:00 Watch and Evaluate Formulas 00:15:00 Activity-Watch and Evaluate Formulas 00:05:00 Create a Data List Outline 00:15:00 Activity-Create a Data List Outline 00:05:00 Analyzing and Presenting Data Create Sparklines 00:15:00 Activity_Create Sparklines 00:05:00 Create Scenarios 00:15:00 Activity-Create Scenarios 00:05:00 Perform a What-If Analysis 00:15:00 Activity-Perform a What-If Analysis 00:05:00 Perform a Statistical Analysis with the Analysis ToolPak 00:15:00 Activity-Perform a Statistical Analysis with the Analysis ToolPak 00:05:00 Create Interactive Data with Power View 00:15:00 Activity-Create Interactive Data with Power View 00:05:00 Working with Multiple Workbooks Consolidate Data 00:15:00 Activity-Consolidate Data 00:05:00 Link Cells in Different Workbooks 00:15:00 Activity-Link Cells in Different Workbooks 00:05:00 Merge Workbooks 00:15:00 Activity-Merge Workbooks 00:05:00 Exporting Excel Data Export Excel Data 00:15:00 Activity-Export Excel Data 00:05:00 Import a Delimited Text File 00:14:00 Activity- Import a Delimited Text File 00:05:00 Integrate Excel Data with the Web 00:15:00 Activity-Integrate Excel Data with the Web 00:05:00 Create a Web Query 00:15:00 Activity-Create a Web Query 00:05:00 Importing and Exporting XML Data Import and Export XML Data 00:15:00 Activity-Import and Export XML Data 00:05:00 Activities Activities and Exercise Files - Microsoft Excel 2016 Advanced 00:00:00 Mock Exam Mock Exam- Microsoft Excel 2016 Advanced 00:20:00 Final Exam Final Exam- Microsoft Excel 2016 Advanced 00:20:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.