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Duration 5 Days 30 CPD hours This course is intended for The target audience for this textbook is all Oracle professionals, both business and systems professionals. Among the specific groups for whom this textbook will be helpful are: ? Business and non-IT professionals ? Application designers and database developers ? Business Intelligence (BI) analysts and consumers ? Database administrators ? Web server administrators Overview The first portion of this textbook considers the logical models upon which a relational database is based and the various configurations and environments in which you may work with the Oracle database. The next segment focuses on the actual SQL syntax for writing database queries. You will begin with the simplest of queries and then proceed onto moderately complex query scenarios. Finally, this textbook covers the DDL, DML and transaction control portions of the SQL language that allow one to create, maintain and manipulate application database objects and application data. This textbook takes a unique approach to SQL training in that it incorporates data modeling theory, relational database theory, graphical depictions of theoretical concepts and numerous examples of actual SQL syntax into one learning vehicle. Relational Databases & Data Models About Data Models About the Relational Model The Electronics Data Model About the Relational DBMS Selection & Setup of the Database Interface Considering Available Tools Selecting the Appropriate Tool Oracle Net Database Connections Oracle PAAS Database Connections Setup SQL Developer Setup SQL*Plus Setup Jdeveloper Using the Database Interface About Bind & Substitution Variables Using SQL Developer Using SQL*Plus Introduction to the SQL Language About the SQL Language Characteristics of SQL Introducing SQL Using Select SQL Rules The Select Statement The Select Statement Distinct/Unique Keyword Using Alias Names Restricting Results with the Where Clause About Logical Operators Equality Operator Boolean Operators REGEXP_LIKE() In Operator Sorting Data with the Order By Clause About the Order by Clause Multiple Column Sorts Specify the Sort Sequence About Null Values within Sorts Using Column Aliases Pseudo Columns, Functions & Top-N Queries Rowid Pseudo Column ORA_ROWSCN PSEUDO Column ROWNUM Pseudo Column About the Built-In Functions SYSDATE User & UID SESSIONTIMEZONE Function Using the Dual Table Row Limiting & Top-N Queries FETCH First x Rows Only Clause OFFSET x Rows Clause FETCH?PERCENT Clause The WITH TIES Option Joining Tables About Joins Inner Joins Reflexive Join Non-Key Join Outer Join Using the Set Operators About the Set Operators SQL Set Operator Examples UNION Example INTERECT Example MINUS Example UNION All Summary Functions Using Sub-Queries Finding Data with Sub-Queries Standard Sub-Queries Correlated Sub-Queries The EXISTS Operator Aggregating Data within Groups About Summary Groups Find Groups within the Tables Select Data From the Base Tables Select Groups from the Results Use DDL to Create & Manage Tables Create Table Statement Column Data Types Not Null Default Describe Alter Table Statement Drop Table Statement Table DDL Using SQL Developer Alter User Statement Alter Session Statement NLS_Language NLS_Date Use DML to Manipulate Data The Insert Statement The Delete Statement The Update Statement About Transactions Transaction Rollback Transaction Commit Transaction Savepoint The Set Transaction Statement Set Transaction Read Only Statement Rules Understanding the Data Models The Company Data Model The Electronics Data Model About the SQL-99 Standard SQL-92 & SQL-99 Cross Joins Natural Joins Inner Joins Implicit Inner Join Outer Joins Anti Joins Named Sub-Queries Enhancing Groups with Rollup & Cube Using Rollup The Grouping() Function Using Cube SQL Functions: Character Handling What are the SQL Functions? String Formatting Functions UPPER(), LOWER() Example INITCAP() Example Character Codes Functions CHR((), ASCII() Examples PAD & TRIM Functions RPAD() Example RTRIM() Example TRIM() Example String Manipulation Functions DECODE () Example SUBSTR() Example INSTR() Example TRANSLATE() Example REPLACE() Example String Comparison Functions LEAST() Example Phonetic Search Function SOUNDEX() Example SQL Functions: Numeric Handling About the Numeric Data Functions GREATEST() Example ABS() Example ROUND() Example TRUNC() Example SIGN() Example TO_NUMBER() Example & Data ype Conversions NULL VALUES FUNCTIONS NVL() & NVL2() Function NVL() Example (Character) NVL() Example (Numeric Loss of Data) NVL() Example (Numeric Output) NVL2() Example COALESCE() Function NULLIF() Function SQL Functions: Date Handling Date Formatting Functions TO_CHAR() & TO_DATE() Format Patterns TO_CHAR() Examples TO_DATE() Examples EXTRACT() Example Date Arithmetic Functions MONTHS_BETWEEN() Example ADD_MONTHS() Example LAST_DAY() Example NEXT_DAY() Example TRUNC(), ROUND() Dates Example NEW_ TIME() Example About V$TIMEZONE_NAMES CAST() FUNCTION & TIME ZONES Database Objects: About Database Objects About Database Objects About Schemas Making Object References Database Objects: Relational Views About Relations Views The Create View Statement Why Use Views? Accessing Views with DML Maintaining View Definitions Alter View Drop View DDL Using SQL Developer Database Objects: Indexes About Indexes Create & Drop Index Statements Indexes & Performance Data Dictionary Storage Database Objects: Creating Other Objects About Sequences Referencing NEXTVAL Referencing CURRVAL Within the DEFAULT Clause Alter Sequence & Drop Sequence ALTER SEQUENCE DROP SEQUENCE About Identity Columns CREATE TABLE?GENERATED AS IDENTITY ALTER TABLE?GENERATED AS IDENTITY Start With Limit Value ALTER TABLE...DROP IDENTITY About Synonyms CREATE & DROP SYNONYM Statements CREATE SYNONYM DROP SYNONYM Public Vs Private Synonyms CREATE SCHEMA AUTHORIZATION Database Objects: Object Management Using DDL The RENAME Statement TABLESPACE Placement CREATE TABLE?TABLESPACE The Comment Statement The TRUNCATE TABLE Statement Database Objects: Security About Object Security Grant Object Privileges Revoke Object Privileges Object Privileges & SQL Developer Data Integrity Using Constraints About Constraints NOT NULL Constraint NOT NULL Example CHECK Constraint UNIQUE Constraint PRIMARY KEY Constraint REFERENCES Constraint ON DELETE CASCADE Example ON DELETE SET NULL Example Constraints on Existing Tables Constraints & SQL Developer Managing Constraint Definitions RENAMING & DROPPING Constraints ENABLING & DISABLING Constraints DEFERRED Constraint Enforcement SET CONSTRAINTS Handling Constraint Exceptions Constraints with Views DATA Dictionary Storage The Data Dictionary Structure More About the Data Dictionary OBJECT-SPECIFIC Dictionary Views USER_UPDATABLE_COLUMNS The Dictionary Structure METADATA & SQL Developer Additional course details: Nexus Humans Oracle 12c SQL Fundamentals 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 Oracle 12c SQL Fundamentals 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.

About this Virtual Instructor Led Training (VILT)  Electrification of the transportation sector will impact the power system in several ways. Besides the additional load, local impact on the grid needs to be managed by the grid operators. Simultaneously charging of many electric vehicles (EVs) might exceed the limits in specific locations. On the other hand, EVs can provide flexibility and other ancillary services that will help grid operators. This 3 half-day VILT course will provide a complete overview of integrating electric vehicles (EVs) into the power grid. It will cover the whole value chain from grid operations to the car battery. This includes the control room, possible grid reinforcement, demand side management and power electronics. This course will demonstrate the impact on the grid and solutions for a safe & cost-effective grid plan and operation, with examples of successful integration of EVs. The course will also provide vital knowledge about technology used for EVs such as power electronics, demand side management, communication and batteries. In this context, the focus will be on power electronics as it has the highest impact on the grid. The grid planning tool, pandapower, is introduced as an open source tool for power system modelling. The set-up of the training course allows for discussion and questions. Questions can be formulated by the participants upfront or during the training. This course is delivered in partnership with Fraunhofer IEE. Training Objectives At the end of this course, the participants will: Understand the charging options for EVs and its impact on the grid and batteries Identify system services for EVs with regards to voltage quality at the point of common coupling Discover what are the 'grid friendly' and grid supporting functions in EVs Uncover the different applications, standards and data researched on EVs Examine the application of a grid planning tool (pandapower) for power system modelling Be able to develop code snippets with pandapower Apply and execute a code example for power system modelling with pandapower Target Audience EV and grid project developers and administrators Power grid operators and planners EPC organisations involved in grid development EV/ battery manufacturers and designers EV transport planners and designers Government regulators and policy makers Training Methods The VILT will be delivered online in 3 half-day sessions comprising 4 hours per day, with 2 x 10 minutes breaks per day, including time for lectures, discussion, quizzes and short interactive exercises. Additionally, some self-study will be requested. Participants are invited but not obliged to bring a short presentation (10 mins max) on a practical problem they encountered in their work. This will then be explained and discussed during the VILT. A short test or quiz will be held at the end of every session/day. Trainer Our first course expert is Head of Department Converters and Electrical Drive Systems at Fraunhofer IEE and Professor for Electromobility and Electrical Infrastructure at Bonn-Rhein-Sieg University of Applied Sciences. He received his engineering degree in automation in 2008 by the THM Technische Hochschule Mittelhessen (FH Giessen-Friedberg). Afterwards he studied power engineering at University of Kassel and received his diploma certificate in 2010. In 2016 he received the Ph.D. (Dr.-Ing.) from the University of Hannover. The title of his dissertation is Optimized multifunctional bi-directional charger for electric vehicles. He has been a researcher at the Fraunhofer IEE in Kassel since 2010 and deals with power converters for electric vehicles, photovoltaics and wind energy. His current research interests include the bidirectional inductive power transfer, battery charger and inverter as well as new power electronic components such as SiC MOSFETs and chokes. Additionally, our key expert is Chairman of the IEEE Joint IAS/PELS/IES German Chapter and a member of the International Scientific Committee of the EPE Association. Our second course expert is deputy head of energy storage department at Fraunhofer IEE. Prior to this he was the Director of Grid Integration department at SMA Solar Technology AG, one of the world's largest manufacturers of PV power converters. Before joining SMA, our course expert was manager of the Front Office System Planning at Amprion GmbH (formerly RWE TSO), one of the four German transmission system operators. He holds a degree of electrical engineering of the University of Kassel, Germany. In 2003 he finished his Ph.D. (Dr.-Ing.) on the topic of wind power forecasting at the 'Institute of Solar Energy Supply Technology' (now Fraunhofer IEE) in Kassel. In 2004 he started his career at RWE TSO with main focus on wind power integration and congestion management. Our course expert is chairman of the IEC SC 8A 'Grid Integration of Large-capacity Renewable Energy (RE) Generation' and has published several papers about grid integration of renewable energy source and forecasting systems on books, magazines, international conferences and workshops. Our third course expert is Research Associate at Fraunhofer IEE. He is actively working on different projects related to the integration of electric vehicle charging into the electric distribution grid. The focus of this work concerns time series based simulations for grid planning and operation in order to investigate the effect of a future rollout of electric vehicles and charging infrastructure on economics e.g. costs for grid reinforcement. He completed his master degree (MSc.) in Business Administration and Engineering: Electrical Power Engineering at RWTH Aachen University, Germany. Our trainers are experts from Fraunhofer Institute for Energy Economics and Energy System Technology (Fraunhofer, IEE), Germany. The Fraunhofer IEE researches for the national and international transformation of energy supply systems POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure 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 DP-203T00 Data Engineering on Microsoft Azure 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.

About this Virtual Instructor Led Training (VILT) This 4 half-day Virtual Instructor Led Training (VILT) course presents the principles and best practices of portfolio management in the upstream (E&P) oil and gas industry. The VILT course is equally valuable for small independents, large integrated international companies and national oil companies. The VILT course consists of presentations, case studies, illustrative practical exercises and syndicate discussions. Particular emphasis is given to pragmatic portfolio management approaches and solutions which can be implemented swiftly without recourse to major investments in planning and portfolio management software. The VILT course will draw on examples from your expert course leader's 35+ years' experience in the oil and gas industry as an explorationist, upstream vice-president and management consultant. The VILT course handout will comprise softcopy slides used in the presentation and a softcopy workbook for the exercises. Participants will gain proficiency in portfolio management techniques, understand how and why to undertake this activity and be able to apply key concepts directly in the business of their teams / divisions. The VILT course will be presented over 4 half-days, using Microsoft Teams or Zoom and a proprietary set of VILT tools. Participants will be asked to complete a pre course questionnaire (PCQ) addressing their objectives and experience, and attend a session to familiarise themselves with VILT tools before course commencement.     Training Objectives To present the tools, concepts and principles of portfolio management To define the quantitative metrics which are used to describe projects in a portfolio To understand the benefits of portfolio management at different stages of the upstream business: in strategy development, opportunity screening, business development, drilling prospects, conducting appraisal of discoveries and developing fields To put portfolio management in the organisational context by describing the role of the portfolio management team and examining how value assurance (quality control) is best conducted on portfolio data for projects and assets To demonstrate how portfolio management contributes to improved business performance By the end of the VILT course, participants will understand: Key concepts and principles of portfolio management How to design a simple portfolio database and describe complex projects in a small number of objective metrics How to segment the portfolio into meaningful units How to use portfolio data in making business choices and decisions at the strategic and tactical levels The extent to which it is meaningful and reasonable to make comparisons across different portfolio segments How the portfolio management team can support the wider business in decision-making Target Audience This VILT course is specially designed for exploration and development geoscientists, E&P economists and finance staff, and E&P managers. Both technical and non-technical staff will benefit from the concepts presented. Companies are encouraged to send participants from different functions and seniority levels to gain great benefits especially those which would like to implement the concepts presented in this VILT course. Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 4 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. The VILT course will be presented in an interactive workshop format that allows for discussion. Course Duration: 4 half-day sessions, 4 hours per session (16 hours in total). Trainer Your expert course leader draws on more than 35 years of experience managing, reviewing and directing projects in all aspects of the exploration business: from exploration business development (new ventures), through prospect maturation and drilling, to the appraisal of discoveries. He has more than 30 years' experience with Shell International, followed by 10 years consulting to NOCs in Asia Pacific, Africa and South America and independent oil companies in the United Kingdom, continental Europe and North America. Other than delivering industry training, he has worked on projects for oil & gas companies of all sizes, including independents, national oil companies and (super)-majors, private equity firms, hedge funds and investment banks, and leading management consulting firms. He is an alumnus of Cambridge University. He has M.A and Ph.D. degrees in geology and is a Fellow of the Geological Society of London as well as a respected speaker on management panels at international conferences. Professional Experience Management consultancy & executive education: Advice to investment banks, businesses and major consulting firms. Specialist expertise in upstream oil & gas, with in depth experience in exploration strategy, portfolio valuation and risk assessment. Leadership: Managed and led teams and departments ranging from 3 - 60 in size. Provided technical leadership to a cadre of 800 explorationists in Shell worldwide. Member of the 12-person VP team leading global exploration in Shell, a $3 bln p.a. business and recognised as the most effective and successful among its industry peers. Accountability & decision-making: Accountable for bottom-line results: in a range of successful exploration ventures with budgets ranging from $10's million to $100's million. Made, or contributed to, complex business decisions / investments, taking into account strategic, technical, commercial, organisational and political considerations. Corporate governance: Served as non-executive director on the Boards of the South Rub al Khali Company (oversight of gas exploration studies and drilling in Saudi Arabia) and SEAPOS B.V. (exploration deep-water drilling and facilities management). Technical & operations: Skilled in exploration opportunity evaluation, the technical de risking of prospects, portfolio analysis and managing the interface between exploration and well engineering activities. Unparalleled knowledge of the oil and gas basins of the world, and of different operating regimes and contractual structures, ranging from Alaska, Gulf of Mexico and Brazil, through to the Middle East, former Soviet Union, Far East and Australia. Safety: Following an unsatisfactory audit, became accountable for safety performance in Shell's exploration new ventures. Through personal advocacy and leadership of a small team, delivered pragmatic and effective HSE systems, tools and staff training / engagement and a dramatically improved safety record. R&D: Experience in the 3 key roles in R&D: scientific researcher, research manager, and 'customer' for R&D products. After re-defining Shell's exploration R&D strategy, led the re-structuring of the R&D organization, its interface with 'the business' and approaches to deployment and commercialization. Strategy: Accomplished at formulating competitive strategies in business, R&D and technology deployment, translating them into actionable tactics and results. Defined the exploration strategy of PDO (a Shell subsidiary in Oman) and latterly of Shell's global exploration programme. Professional education, behavioural/motivational coaching: Experienced in organisational re-design, change management, leadership education and talent development. Commercial skills: Personally negotiated drilling compensation claims, educational contracts and E&P contracts, with values of $5 million to $100+ million. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

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Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is an IT, facilities or data centre operations professional working in and around the data centre and having the responsibility to achieve and improve high-availability and manageability of the data centre. Overview After completion of the course the participant will be able to:? Understand the design life cycle of data centres and the stages involved? Discuss the data centre requirements in great level of detail with vendors, suppliers and contractors to ensure that these requirements are met? Validate design plans, quotes and offers proposed by vendors/contractors? Understand redundancy levels for both the data centre design/setup and maintenance? Understand the various building considerations such as bullet proofing, mitigation of seismic activity, fire ratings and thermal stability? Understand how to install a raised floor that meets requirements, avoiding misalignment, level differences and leakage? Understand how to read a Single Line Electrical Diagram to identify and avoid the most common design issues? Choose the correct UPS and parallel configuration, learn and avoid classic parallel installation mistakes? Understand how to calculate battery banks, validate offered configurations to ensure they meet requirements? Understand what distance to keep to avoid EMF issues for human safety and equipment disturbances? Understand the fundamental cooling setup, CFM, Delta-T and other important factors? Understand contamination factors and limitations? Understand full details of fire suppression options, how to calculate gas content and verify installations? Understand how to measure data centre energy efficiency and how to improve it The course will bring participants to the level of a suitable sparring partner with suppliers. They will be able to verify offers provided by vendors for correctness, effectiveness and efficiency. Data Centre Design/Life Cycle Overview Overview of the phases of a data centre life cycle Planning, re-alignment and continuous improvement Standards and Rating Level Definitions Rating level history Difference between Uptime and TIA-942 Rating level definitions Redundancy options (N+1), 2N, 2(N+1) Concurrent Maintainability/Compartmentalisation Example configurations Substation and feed requirements Maintenance options Operational processes guidelines/standards Skill development Building Considerations Building location considerations Floor and hanging loads requirements Fire rating for walls and glass Blast protection Bullet proofing Forced entry protection Advanced Raised Floor & Suspended Ceiling Raised floor installation guidelines Techniques to install a proper and leveled raised access floor Common mistakes Choosing the right tiles and their locations Seismic-mitigating floor constructions Choosing the correct suspended ceiling Advanced Power Power infrastructure layout; Formulas which you should know for the data centre Single Line Electrical diagrams; how to read to ensure key components are present for protection Over current protection devices (MCB/MCCB/VCB/ACB/Fuses) definitions and what to use where Earth Leakage devices (RCB/RCD/ELCB/GFCI/ALCI/RCBO), definitions and what to use where Sizing of protective components Lightning strikes and surge protection devices (TVSS/SPD), how they operate, where to use and how to install Power cabling and cable run considerations PDU/DB setup and minimum requirements Generators; Generator types: Standy/Prime/Continuous Component make up and functions Fuel storage and calculation Paralleling of gen-sets Generator room/area requirements UPS Systems; Required specifications for UPS systems How to read data sheets and select the correct UPS Requirements for parallel configurations and avoid pitfalls such as single point of failures How parallel installation should be done, classic mistakes made by installers and how to avoid these Harmonic Filters; Active/Passive filters and their application Battery Banks; Battery bank terminology Designing battery banks, how to calculate, and double check the battery bank to be installed Battery charging pitfalls and ensuring the right charger is being installed and used Using parallel battery banks; how to properly install them, limitations and risks when using batteries in parallel How to test batteries correctly and make decisions on cell/block or string replacement Battery casing choices; ABS, V0, V1, V2 Alternative energy storage; flywheel, re-usable cell, compressed air UPS, etc. Advanced Electro Magnetic Fields Sources of EMF Difference between single, three phase and bus-bar EMF Options available to measure EMF and how to interpret the results from single-axes and composite measurements Guidance on safe distance for equipment and humans Calculation of EMF attenuation factor for shielding material permeability and saturation factors Advanced Cooling Important definitions; dry-bulb, wet-bulb, dew-point, RH, sensible and latent heat Psychometric chart and ASHRAE recommendations Environmental class definitions and thermal specifications Temperature/humidity measurements guideline Heat dissipation methods Altitude impact on temperature intake to ICT equipment Floor plan setup for effective cooling Differences in tile surface and supporting structure and the air-flow performance impact Rack door construction and the flow performance impact Equipment Delta-T and its impact Optimising air flow Thermal units conversions Calculations for air volume displacement (CFM/CMH) Cooling capacity calculations Air-conditioning selection De- / humidifying options Air conditioning efficiency SHR impact on cost saving Efficiency indicator New cooling principle and techniques (Submerged, VSD/VRF/ECF/water- and air side economisers) Redundancy guidelines for air-conditioners avoiding classic misconceptions and mistakes for meeting ANSI/TIA-942 compliant designs Installation requirements Connections to fire panel and EPO Commissioning of air conditioners Set points and calibration CFD (Computational Fluid Dynamics) Advanced Fire Protection The fire triangle and elements to stop a fire Detection systems in detail (VESDA, VIEW, smoke sensors) Considerations for installation of sensors Proper testing of smoke sensors Water based systems i.e. deluge, wet-pipe, dry-pipe, pre-action and why most of them don't work and how to detect this Details on Inert and Halocarbon systems and how to select the correct system for your data centre How to calculate the gas content ensuring the appropriate level is installed to suppress the fire including safety considerations Other requirements for gas systems such as release times, hold times, pipe install requirements and other important factors Requirements for the fire detection panel Installation verification, methods, what to check and how New advanced fire suppression technologies Design and Install Scalable Networking Cabling System ANSI/TIA942 cabling structure topology ToR, EoR Design Intelligent patching systems Installation best practice such as routing, bending radius, separation from power, containment fill ratio, fiber link loss calculator, bonding and grounding requirement Standard for telecommunications labeling and administration Environmental Specifications and Contamination Control Acoustic noise effects, regulations, specifications and limits Data centre contaminations and classifications Measurements, standards and limits Preventive measures and avoidance Data Centre Efficiency Business drivers to go Green High-availability or Green? Green guidelines and standards How to measure it and what are acceptable numbers compared to the general industry PUE classes defined by Green Grid and issues with PUE Techniques for saving energy in all parts of the data centre i.e. application/system level, cooling, power distribution Mock ExamEXAM: Certified Data Centre Specialist

Duration 3 Days 18 CPD hours This course is intended for This intermediate course is for experienced SQL end users, application programmers, database administrators, and user support staff who need more advanced knowledge of SQL. Overview Discuss basic relational database concepts Use some of the OLAP features of DB2, such as GROUPing and RANKing functions Create tables, views and indexes Use referential integrity, check constraints and triggers Use outer joins, and join tables to themselves Use CASE expressions, and the CAST function Identify the impact of Summary Tables, Materialized Query Tables, and temporary tables Use complex subqueries Use a greater number of scalar SQL functions Use advanced SQL constructs, such as recursive SQL and table expressions Define User-Defined Distinct Types and User-Defined Functions Avoid several of the most common causes for poorly-performing SQL This course teaches you how to make use of advanced SQL techniques to access DB2 databases in different environments. This course is appropriate for customers working in all DB2 environments, specifically for z/OS, Linux, UNIX, and Windows. Introduction Identify the purpose of the clauses in the SELECT statement Describe the key differences among the IBM DB2 platforms Describe and use some of the OLAP features of DB2, such as GROUPING functions like CUBE and ROLLUP, and the RANK, DENSE_RANK and ROW_NUMBER functions Create Objects Code statements to: Create tables and views, Alter tables, Create indexes, Implement referential integrity (RI), and Define triggers and check constraints Identify impacts and advantages of referential integrity, including impacts of delete rules Identify considerations when using triggers and check constraints Define and make use of INSTEAD OF triggers Join Retrieve data from more than one table via inner and outer joins Use outer joins (LEFT, RIGHT, FULL) Use ANTI JOINS Join a table to itself Use UNION and UNION ALL Use EXCEPT and INTERCEPT CASE, CAST, Summary Tables, and Materialized Query Tables Identify when CASE expressions can be used Code CASE expressions in SELECT list and in the WHERE clause Identify when CAST specifications can be used Identify the advantages of using Summary (Materialized Query) Tables and Temporary tables Identify the advantages of using Materialized Query Tables (MQTs) Identify when and how to use Temporary tables Using Subqueries Code subqueries using the ALL, ANY/SOME, and EXISTS keywords Code correlated subqueries Choose the proper type of subquery to use in each case Scalar Functions Extend your knowledge of scalar functions which: Manipulate arithmetic data, Manipulate date values, and Manipulate character data Examples of scalar functions that are addressed in this course: SUBSTR POSSTR COALESCE/VALUE DECIMAL ROUND DIGITS CHAR DATE/TIME Table Expressions and Recursive SQL Identify reasons for using table expressions and recursive SQL Use nested and common table expressions Identify the difference between views and table expressions Code recursive SQL Control the depth of recursion when coding recursive SQL UDTs/UDFs and Performance Describe the concepts behind User-Defined Types, User-Defined Functions and Stored Procedures Predict when queries will use indexes to get better performance Identify concepts of predicate processing State introductory concepts about index structure State general best practices advice Additional course details: Nexus Humans CE131 IBM DB2 SQL Workshop for Experienced Users 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 CE131 IBM DB2 SQL Workshop for Experienced Users 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 3 Days 18 CPD hours This course is intended for Application consultants Overview In this course, participants use and customize functions in delivery processing. In this course, students learn the customizing settings of delivery documents and the set-up of corresponding functions. Idea and Function of the Delivery Document Explaining the Concept and Structure of the Delivery Document Basic Organizational Units for the Delivery Process Maintaining the Organizational Units for Delivery Processes Controlling Deliveries Controlling Delivery Documents The Goods Issue Process Based on the Delivery Adjusting Automatic Determination of Relevant Fields for Outbound Delivery Creation Adjusting Delivery and Transportation Scheduling Processing Outbound Deliveries Using the Outbound Delivery Monitor Processes and Functions based on the Delivery Picking Outbound Deliveries Packing Materials Handling Goods Issues Using Special Functions in Deliveries Further Application Areas of the Delivery Document Transferring Stock Between Plants Performing Goods Receipts Using Deliveries Specified Delivery Scenario Setting Up a Specified Delivery Scenario

Duration 2 Days 12 CPD hours This course is intended for New users of IBM SPSS Statistics Users who want to refresh their knowledge about IBM SPSS Statistics Anyone who is considering purchasing IBM SPSS Statistics Overview Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables. Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders Additional course details: Nexus Humans 0G53BG IBM SPSS Statistics Essentials (V26) 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 0G53BG IBM SPSS Statistics Essentials (V26) 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.