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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?

This course starts with the basics of Recurrent Neural Networks (RNNs) with Python and then teaches you how to build them by taking you through various exercises and projects. You will be able to test your skills by completing two exciting projects: creating an automatic book writer and a stock price prediction application.

IASSC lean six sigma green belt course. Online, 24/7 access to content and exam. Fee includes learning content, live webinars, tutor support, and official IASSC exam.

IASSC lean six sigma black belt course. Online, 24/7 access to content and exam. Fee includes learning content, live webinars, tutor support, and official IASSC exam.

Lean Six Sigma Black Belt Certification Program This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

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Course Curriculum HR Management - Updated Version Module 01: Introduction to Human Resource 00:17:00 Module 02: Employee Recruitment and Selection Procedure 00:32:00 Module 03: Employee Training and Development Process 00:22:00 Module 04: Performance Appraisal Management 00:19:00 Module 05: Employee Relations 00:14:00 Module 06: Motivation and Counselling 00:19:00 Module 07: Ensuring Health and safety at the Workplace 00:17:00 Module 08 : Employee Termination 00:15:00 Module 09: Employer Record and Statistics 00:11:00 Module 10: Essential UK Employment Law 00:26:00 HR Management - Old Version Module 01: Human Resource Management Human Resource Management 01:00:00 Module 02: HR Planning, Recruitment and Selection HR Planning, Recruitment and Selection 01:00:00 Module 03: Induction, Training and Development Induction, Training and Development 00:45:00 Module 04: HR Department's Responsibilities HR Department's Responsibilities 00:45:00 Module 05: The UK Recruitment Legislations Guide The UK Recruitment Legislations Guide 00:20:00 Module 06: Organizational Culture Organisational Culture 00:45:00 Module 07: Motivation, Counseling, Resignations and Retirement Motivation, Counseling, Resignations and Retirement 01:00:00 Module 08: Performance Appraisal & Remuneration Policy Performance Appraisal 00:45:00 Remuneration Policy 00:15:00 Module 09: Records and Statistics Records and Statistics 00:30:00 Module 10: Industrial Relations Industrial Relations 00:15:00 Module 11: The UK Recruitment Industry Statistics The UK Recruitment Industry Statistics 00:25:00 Payroll Management Course Module 01: Payroll System in the UK Payroll System in the UK 01:05:00 Module 02: Payroll Basics Payroll Basics 00:10:00 Module 03: Company Settings Company Settings 00:08:00 Module 04: Legislation Settings Legislation Settings 00:07:00 Module 05: Pension Scheme Basics Pension Scheme Basics 00:06:00 Module 06: Pay Elements Pay Elements 00:14:00 Module 07: The Processing Date The Processing Date 00:07:00 Module 08: Adding Existing Employees Adding Existing Employees 00:08:00 Module 09: Adding New Employees Adding New Employees 00:12:00 Module 10: Payroll Processing Basics Payroll Processing Basics 00:11:00 Module 11: Entering Payments Entering Payments 00:12:00 Module 12: Pre-Update Reports Pre-Update Reports 00:09:00 Module 13: Updating Records Updating Records 00:09:00 Module 14: e-Submissions Basics e-Submissions Basics 00:09:00 Module 15: Process Payroll (November) Process Payroll (November) 00:16:00 Module 16: Employee Records and Reports Employee Records and Reports 00:13:00 Module 17: Editing Employee Records Editing Employee Records 00:07:00 Module 18: Process Payroll (December) Process Payroll (December) 00:12:00 Module 19: Resetting Payments Resetting Payments 00:05:00 Module 20: Quick SSP Quick SSP 00:09:00 Module 21: An Employee Leaves An Employee Leaves 00:13:00 Module 22: Final Payroll Run Final Payroll Run 00:07:00 Module 23: Reports and Historical Data Reports and Historical Data 00:08:00 Module 24: Year-End Procedures Year-End Procedures 00:09:00