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Unlock the secrets of financial empowerment with our exclusive workshop on The Infinite Banking Concept: Privatizing Finance Strategies. This isn't just a course; it's your gateway to a financial paradigm shift. Picture a world where you control your financial destiny, and every financial move strategically aligns with your goals. In this transformative journey, we guide you through meticulously crafted modules that demystify the Infinite Banking Concept, empowering you to privatize your financial strategies. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access Begin by immersing yourself in the Introduction, laying the groundwork for a profound understanding. Establish a rock-solid foundation to fortify your financial future. Deconstruct the Infinite Banking Concept to reveal its intricate workings and unleash its power. Take the reins with the Implementation module, where you'll learn to apply this revolutionary concept to your financial landscape. Elevate your financial prowess with Advanced Techniques and Optimization Strategies, ensuring every move is strategic and calculated. Safeguard your financial future with Risk Mitigation and Optimal Practices, creating a roadmap for sustainable financial success. Join us on this journey, where financial freedom becomes not just a concept but a tangible reality. Course Curriculum Module 1: Infinite Banking Concept Introduction Module 2: Establishing a Solid Foundation Module 3: Infinite Banking Concept Deconstruction Module 4: Implementation of the Infinite Banking Concept Module 5: Advanced Techniques and Optimization Strategies Module 6: Risk Mitigation and Optimal Practices Learning Outcomes: Understand the essence of the Infinite Banking Concept through Introduction. Establish a robust foundation for effective financial strategizing and planning. Deconstruct the intricacies of the Infinite Banking Concept for comprehensive comprehension. Implement the Infinite Banking Concept to privatize and optimize personal finances. Explore advanced techniques, refining financial strategies for optimal effectiveness. Develop risk mitigation skills and adopt optimal practices in financial management. CPD 10 CPD hours / points Accredited by CPD Quality Standards The Infinite Banking Concept: Privatizing Finance Strategies 1:50:46 1: Module 1: Infinite Banking Concept Introduction 14:13 2: Module 2: Establishing a Solid Foundation 19:53 3: Module 3: Infinite Banking Concept Deconstruction 18:16 4: Module 4: Implementation of the Infinite Banking Concept 16:44 5: Module 5: Advanced Techniques and Optimization Strategies 21:00 6: Module 6: Risk Mitigation and Optimal Practices 18:40 7: CPD Certificate - Free 01:00 8: Leave A Review 01:00 Who is this course for? Individuals seeking financial independence and strategic wealth management knowledge. Entrepreneurs and business owners aiming to optimize personal and business finances. Finance enthusiasts interested in mastering the Infinite Banking Concept principles. Anyone looking to enhance financial literacy and take control of personal finances. Professionals in finance-related fields desiring a strategic financial planning skillset. Career path Financial Strategist Wealth Management Advisor Financial Analyst Investment Consultant Financial Planning Specialist Business Finance Manager Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Embark on an enlightening journey with our Cultural Anthropology course. Explore the depths of human societies, uncovering the intricacies of culture, language, economics, and more. Tailored for those fascinated by the diverse tapestry of human existence.

“Master the integration of AI in programming with our ‘ChatGPT for Programmers’ course. Discover how ChatGPT can revolutionize your coding skills and open new horizons in software development.”

Dealing with Angry or Rude Customers   Course Description   Copyright Ross Maynard 2021   Course Description If you work in customer service in any way, then, from time to time, you are going to have to deal with angry or rude customers. This course will help you manage those stressful situations and support the customer as best you can. Anger is a normal and relatively common emotion caused by a perceived hurt or provocation. In some cases a customer’s anger or rude behaviour may be driven by the failings of your organisation or its products and services. In other cases, the problem may be outside your control but you still have to deal with the impact. In this course we look at anger in a customer service situation and how to deal with it. We review the nature and causes of anger; we look at how poor customer service can cause anger and what you can do to prepare your organisation to deal with anger. We cover the warning signs for anger and present a 12 step approach to dealing with an angry customer. We cover questions and short scripts that can help you start a discussion with an angry customer, and we consider why customers might be rude. Finally we look at managing the stress of dealing with an angry customer and finish the course with a review of the key learning points. I hope you find the course helpful.   Key Learning Points  On completion of the course, delegates will be able to: Understand the nature and causes of anger as an emotion. Consider their objectives when dealing with an angry customer. Help prepare their organisation for dealing with angry customers. Identify appropriate customer service metrics Work through a series of steps to deal with an angry customer. Use questions and short scripts to try to help a customer bring their anger under control . Consider why a customer might be rude, and how to deal with that rudeness. Understand how to manage the stress of dealing with angry or rude customers.     Curriculum L1: Anger as an Emotion L2: Your Objectives when Dealing with Anger L3: Poor Customer Service L4: Preparing your Organisation  L5: Warning Signs and What Not to Do L6: The 12 Steps to Dealing with Anger L7: Example Scripts for Angry Customers L8: Dealing with Rude Customers L9: Dealing with Stress, and Key Learning Points     Pre-Course Requirements There are no pre-course requirements     Additional Resources Copy of customer behaviour policy     Course Tutor Your tutor is Ross Maynard. Ross is a Fellow of the Chartered Institute of Management Accountants in the UK and has 30 years’ experience as a process improvement consultant specialising in business processes and organisation development. Ross is also a professional author of online training courses. Ross lives in Scotland with his wife, daughter and Cocker Spaniel

Duration 3 Days 18 CPD hours This course is intended for Service providers who are designing or using VMware SD-WAN solutions or managing SD-WAN networks for customers Service providers looking to deliver a managed hybrid WAN with MPLS service Service providers transforming their MPLS networks for direct access to cloud services and increased network agility Overview By the end of the course, you should be able to meet the following objectives: Describe how VMware SASE™ solves security challenges for distributed enterprises Identify where VMware SD-WAN fits in the VMware SASE framework Describe the process for validating the installation of VMware SD-WAN Orchestrator and Gateway in a service provider environment Describe the features for monitoring and maintaining a VMware SD-WAN installation Evaluate the security features and certificate operations for managing a VMware SD-WAN installation Describe VMware SD-WAN Edge licensing and license types Describe the features of VMware Edge Network Intelligence™ Recognize VMware SD-WAN network monitoring tools for generating reports, events, and alerts Recognize the remote diagnostic actions available on VMware SD-WAN Orchestrator Troubleshoot VMware SD-WAN Orchestrator and Gateway common issues This three-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in operating and troubleshooting the VMware SD-WAN? environment for service providers.In this course, you focus on deploying and managing VMware SD-WAN for a service provider, including troubleshooting common issues. Course Introduction Introductions and course logistics Course objectives VMware SD-WAN Installation for Service Providers Describe security challenges for distributed enterprises Describe the VMware SASE solution for securing distributed enterprises Describe VMware deployment models for service providers Explain how VMware SD-WAN can help to transform MPLS networks to service-ready networks Identify resource requirements for installing VMware SD-WAN Orchestrator and Gateways Describe the procedure for installing VMware SD-WAN Orchestrator Describe the process for provisioning VMware SD-WAN Orchestrator Identify the external service dependencies for VMware SD-WAN Orchestrator Recognize disaster recovery options for SD-WAN Orchestrator Describe the disaster recovery workflow for VMware SD-WAN Orchestrator Identify the requirements for installing VMware SD-WAN Gateway instances Describe the procedure for installing VMware SD-WAN Gateway instances Describe the procedure for installing VMware SD-WAN Gateway instances on ESXi hosts identify Data Plane Development Kit support for gateway performance Describe the VMware SD-WAN Gateway deployment modes for service providers Configure a VMware SD-WAN Gateway for a service provider Assign a VMware SD-WAN Gateway for a service provider VMware SD-WAN Monitoring and Maintenance Describe VMware SD-WAN Orchestrator system health-monitoring features Describe VMware SD-WAN Orchestrator process-monitoring features Describe VMware SD-WAN Orchestrator storage-monitoring features Describe VMware SD-WAN Orchestrator database-monitoring features Describe the VMware SD-WAN Orchestrator upgrade process Describe the VMware SD-WAN Orchestrator backup and data archival processes Describe the VMware SD-WAN Orchestrator process to expand database disks Describe the VMware SD-WAN Orchestrator system metrics for monitoring Describe how systems metrics are collected for monitoring VMware SD-WAN Orchestrator Describe VMware SD-WAN Gateway additions and removals Describe the VMware SD-WAN Gateway upgrade process Describe the VMware SD-WAN Gateway validation process VMware SD-WAN Security and Edge Licensing Describe the VMware SD-WAN PKI security infrastructure Recognize VMware SD-WAN PKI authentication modes Describe VMware SD-WAN certificate operations Describe the VMware SD-WAN PKI certificate authentication configuration Describe the VMware SD-WAN PKI configuration process Compare operator and partner logins Describe the VMware SD-WAN self-signed certificate authority process Describe VMware SD-WAN certificate authority renewal and revocation Describe the VMware SD-WAN intermediate certificate authority Describe the VMware SD-WAN certificate chain of trust Describe the VMware SD-WAN Edge licensing and license types Assign and view the VMware SD-WAN Edge licenses and reports VMware SD-WAN Reporting and Diagnostics Describe the VMware SD-WAN network monitoring tools Describe the VMware SD-WAN network visibility options and controls Identify the VMware SD-WAN Orchestrator reporting features Describe and analyze VMware SD-WAN Orchestrator events View enterprise reports by operator, partner, and administrator View historical network insights and real-time reports on path visibility Describe common VMware SD-WAN alerts Describe the VMware SD-WAN heart mechanism for alerts Configure VMware SD-WAN alerts Analyze common VMware SD-WAN alerts Use standard networking tools for monitoring VMware SD-WAN Describe remote diagnostic actions available on VMware SD-WAN Orchestrator Use the remote diagnostics tools on VMware SD-WAN Orchestrator Generate remote diagnostics bundles and packet captures VMware SD-WAN Orchestrator and Gateway Troubleshooting Recognize the basic sanity checks to troubleshoot VMware SD-WAN Orchestrator Create diagnostic bundles to enable support to troubleshoot VMware SD-WAN Orchestrator Recognize the basic checks to troubleshoot VMware SD-WAN Orchestrator Troubleshoot common VMware SD-WAN Orchestrator performance issues Describe the tools available to troubleshoot VMware SD-WAN Gateway Analyze sample outputs for debugging a VMware SD-WAN Gateway issue Use Data Plane Development Kit to improve VMware SD-WAN Gateway performance VMware SD-WAN Orchestrator and Gateway Commands Recognize when and how to use VMware SD-WAN Orchestrator database-monitoring commands Recognize when and how to use the VMware SD-WAN Gateway process-monitoring commands

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Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for Data Warehouse AdministratorDatabase Administrators Overview Use the Oracle Database tuning methodology appropriate to the available toolsUtilize database advisors to proactively tune an Oracle Database InstanceUse the tools based on the Automatic Workload Repository to tune the databaseDiagnose and tune common SQL related performance problemsDiagnose and tune common Instance related performance problemsUse Enterprise Manager performance-related pages to monitor an Oracle DatabaseGain an understanding of the Oracle Database Cloud Service In the Oracle Database 12c: Performance Management and Tuning course, learn about the performance analysis and tuning tasks expected of a DBA: proactive management through built-in performance analysis features and tools, diagnosis and tuning of the Oracle Database instance components, and diagnosis and tuning of SQL-related performance issues. In this course, you will be introduced to Oracle Database Cloud Service. Introduction Course Objectives Course Organization Course Agenda Topics Not Included in the Course Who Tunes? What Does the DBA Tune? How to Tune Tuning Methodology Basic Tuning Diagnostics Performance Tuning Diagnostics Performance Tuning Tools Tuning Objectives Top Timed Events DB Time CPU and Wait Time Tuning Dimensions Time Model Dynamic Performance Views Using Automatic Workload Repository Automatic Workload Repository Overview Automatic Workload Repository Data Enterprise Manager Cloud Control and AWR Snapshots Reports Compare Periods Defining the Scope of Performance Issues Defining the Problem Limiting the Scope Setting the Priority Top SQL Reports Common Tuning Problems Tuning During the Life Cycle ADDM Tuning Session Performance Versus Business Requirements Using Metrics and Alerts Metrics and Alerts Overview Limitation of Base Statistics Benefits of Metrics Viewing Metric History Information Viewing Histograms Server-Generated Alerts Setting Thresholds Metrics and Alerts Views Using Baselines Comparative Performance Analysis with AWR Baselines Automatic Workload Repository Baselines Moving Window Baseline Baselines in Performance Page Settings Baseline Templates AWR Baseslines Creating AWR Baselines Managing Baselines with PL/SQL Using AWR-Based Tools Automatic Maintenance Tasks ADDM Performance Monitoring Using Compare Periods ADDM Active Session History New or Enhanced Automatic Workload Repository Views Emergency Monitoring Real-time ADDM Real-Time Database Operation Monitoring Overview Use Cases Defining a Database Operation Scope of a Composite Database Operation Database Operation Concepts Identifying a Database Operation Enabling Monitoring of Database Operations Identifying, Starting, and Completing a Database Operation Monitoring Applications What is a Service? Service Attributes Service Types Creating Services Managing Services in a Single-Instance Environment Where are Services Used? Using Services with Client Applications Services and Pluggable Databases Identifying Problem SQL Statements SQL Statement Processing Phases Role of the Oracle Optimizer Identifying Bad SQL Top SQL Reports SQL Monitoring What is an Execution Plan? Methods for Viewing Execution Plans Uses of Execution Plans Influencing the Optimizer Functions of the Query Optimizer Selectivity Cardinality and Cost Changing Optimizer Behavior Optimizer Statistics Extended Statistics Controlling the Behavior of the Optimizer with Parameters Enabling Query Optimizer Features Reducing the Cost of SQL Operations Reducing the Cost Index Maintenance SQL Access Advisor Table Maintenance for Performance Table Reorganization Methods Space Management Extent Management Data Storage Using SQL Performance Analyzer Real Application Testing: Overview Real Application Testing: Use Cases SQL Performance Analyzer: Process Capturing the SQL Workload Creating a SQL Performance Analyzer Task SQL Performance Analyzer: Tasks Parameter Change SQL Performance Analyzer Task Page SQL Performance Management Maintaining SQL Performance Maintaining Optimizer Statistics Automated Maintenance Tasks Statistic Gathering Options Setting Statistic Preferences Restore Statistics Deferred Statistics Publishing Automatic SQL Tuning Using Database Replay Using Database Replay The Big Picture System Architecture Capture Considerations Replay Considerations: Preparation Replay Considerations Replay Options Replay Analysis Tuning the Shared Pool Shared Pool Architecture Shared Pool Operation The Library Cache Latch and Mutex Diagnostic Tools for Tuning the Shared Pool Avoiding Hard Parses Reducing the Cost of Soft Parses Sizing the Shared Pool Tuning the Buffer Cache Oracle Database Architecture: Buffer Cache Buffer Cache: Highlights Database Buffers Buffer Hash Table for Lookups Working Sets Buffer Cache Tuning Goals and Techniques Buffer Cache Performance Symptoms Buffer Cache Performance Solutions Tuning PGA and Temporary Space SQL Memory Usage Performance Impact Automatic PGA Memory SQL Memory Manager Configuring Automatic PGA Memory Setting PGA_AGGREGATE_TARGET Initially Limiting the size of the Program Global Area (PGA) SQL Memory Usage Automatic Memory Oracle Database Architecture Dynamic SGA Granule Memory Advisories Manually Adding Granules to Components Increasing the Size of an SGA Component Automatic Shared Memory Management: Overview SGA Sizing Parameters: Overview Performance Tuning Summary with Waits Commonly Observed Wait Events Additional Statistics Top 10 Mistakes Found in Customer Systems Symptoms Oracle Database Cloud Service: Overview Database as a Service Architecture, Features and Tooling Software Editions: Included Database Options and Management Packs Accessing the Oracle Database Cloud Service Console Automated Database Provisioning Managing the Compute Node Associated With a Database Deployment Managing Network Access to Database as a Service Scaling a Database Deployment Performance Management in the Database Cloud Environment Performance Monitoring and Tuning What Can be Tuned in a DBCS Environment?

Duration 3 Days 18 CPD hours This course is intended for This intermediate-level hands-on course is geared for experienced Administrators, Analysts, Architects, Data Scientists, Database Administrators and Implementers Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: Administer ODI resources and setup security with ODI Apply ODI Topology concepts for data integration Describe ODI Model concepts Describe architecture of Oracle Data Integrator Design ODI Mappings, Procedures, Packages, and Load Plans to perform ELT data transformations Explore, audit data, and enforce data quality with ODI Implement Changed Data Capture with ODI Oracle Data Integrator is a comprehensive data integration platform that covers all data integration requirements from high-volume, high-performance batch loads, to event-driven integration processes and SOA-enabled data services. Oracle Data Integrator's Extract, Load, Transform (E-LT) architecture leverages disparate RDBMS engines to process and transform the data - the approach that optimizes performance, scalability and lowers overall solution costs. Throughout this course participants will explore how to centralize data across databases, performing integration, designing ODI Mappings, and setting up ODI security. In addition, Oracle Data Integrator can interact with the various tools of the Hadoop ecosystem, allowing administrators and data scientists to farm out map-reduce operations from established relational databases to Hadoop. They can also read back into the relational world the results of complex Big Data analysis for further processing. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: Administer ODI resources and setup security with ODI Apply ODI Topology concepts for data integration Describe ODI Model concepts Describe architecture of Oracle Data Integrator Design ODI Mappings, Procedures, Packages, and Load Plans to perform ELT data transformations Explore, audit data, and enforce data quality with ODI Implement Changed Data Capture with ODI Introduction to Integration and Administration Oracle Data Integrator: Introduction Oracle Data Integrator Repositories Administering ODI Repositories Create and connect to the Master Repository Export and import the Master Repository Create, connect, and set a password to the Work Repository ODI Topology Concepts ODI Topology: Overview Data Servers and Physical Schemas Defining Topology Agents in Topology Planning a Topology Describing the Physical and Logical Architecture Topology Navigator Creating Physical Architecture Creating Logical Architecture Setting Up a New ODI Project ODI Projects Using Folders Understanding Knowledge Modules Exporting and Importing Objects Using Markers Oracle Data Integrator Model Concepts Understanding the Relational Model Understanding Reverse-Engineering Creating Models Organizing ODI Models and Creating ODI Datastores Organizing Models Creating Datastores Constraints in ODI Creating Keys and References Creating Conditions Exploring Your Data Constructing Business Rules ODI Mapping Concepts ODI Mappings Expressions, Join, Filter, Lookup, Sets, and Others Behind the Rules Staging Area and Execution Location Understanding Knowledge Modules Mappings: Overview Designing Mappings Multiple Sources and Joins Filtering Data Overview of the Flow in ODI Mapping Selecting a Staging Area Configuring Expressions Execution Location Selecting a Knowledge Module Mappings: Monitoring and Troubleshooting Monitoring Mappings Working with Errors Designing Mappings: Advanced Topics 1 Working with Business Rules Using Variables Datasets and Sets Using Sequences Designing Mappings: Advanced Topics 2 Partitioning Configuring Reusable Mappings Using User Functions Substitution Methods Modifying Knowledge Modules Using ODI Procedures Procedures: Overview Creating a Blank Procedure Adding Commands Adding Options Running a Procedure Using ODI Packages Packages: Overview Executing a Package Review of Package Steps Model, Submodel, and Datastore Steps Variable Steps Controlling the Execution Path Step-by-Step Debugger Starting a Debug Session New Functions Menu Bar Icons Managing ODI Scenarios Scenarios Managing Scenarios Preparing for Deployment Using Load Plans What are load plans? Load plan editor Load plan step sequence Defining restart behavior Enforcing Data Quality with ODI Data Quality Business Rules for Data Quality Enforcing Data Quality with ODI Working with Changed Data Capture CDC with ODI CDC implementations with ODI CDC implementation techniques Journalizing Results of CDC Advanced ODI Administration Setting Up ODI Security Managing ODI Reports ODI Integration with Java

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Hands-on Predicitive Analytics with Python (TTPS4879) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.