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Duration 4 Days 24 CPD hours This course is intended for The audience for this course is data professionals managing data and databases who want to learn about administering the data platform technologies that are available on Microsoft Azure. This course is also valuable for data architects and application developers who need to understand what technologies are available for the data platform with Azure and how to work with those technologies through applications. This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases. Prerequisites In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses: AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Prepare to maintain SQL databases on Azure Describe Microsoft Intelligent Data Platform roles Understand SQL Server in an Azure virtual machine Design Azure SQL Database for cloud-native applications Explore Azure SQL Database Managed Instance 2 - Deploy IaaS solutions with Azure SQL Explain IaaS options to deploy SQL Server in Azure Understand hybrid scenarios Explore performance and security Explain high availability and disaster recovery options 3 - Deploy PaaS solutions with Azure SQL Explain PaaS options for deploying SQL Server in Azure Explore single SQL database Deploy SQL database elastic pool Understand SQL database hyperscale Examine SQL managed instance Describe SQL Edge 4 - Evaluate strategies for migrating to Azure SQL Understand compatibility level Understand Azure preview features Describe Azure database migration options 5 - Migrate SQL workloads to Azure SQL databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL Database offline Migrate SQL Server to Azure SQL Database online Load and move data to Azure SQL Database 6 - Migrate SQL workloads to Azure Managed Instances Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed Instance Load and Move data to SQL Database Managed Instance 7 - Configure database authentication and authorization Describe Active Directory and Azure Active Directory Describe authentication and identities Describe Security Principals Describe database and object permissions Identify authentication and authorization failures 8 - Protect data in-transit and at rest Explore Transparent Data Encryption Configure server and database firewall rules Explain object encryption and secure enclaves Enable encrypted connections Describe SQL injection Understand Azure Key Vault 9 - Implement compliance controls for sensitive data Explore data classification Explore server and database audit Implement Dynamic Data Masking Implement Row Level security Understand Microsoft Defender for SQL Explore Azure SQL Database Ledger Implement Azure Purview 10 - Describe performance monitoring Describe performance monitoring tools Describe critical performance metrics Establish baseline metrics Explore extended events Describe Azure SQL Insights Explore Query Performance Insight 11 - Configure SQL Server resources for optimal performance Explain how to optimize Azure storage for SQL Server virtual machines Describe virtual machine resizing Optimize database storage Control SQL Server resources 12 - Configure databases for optimal performance Explore database maintenance checks Describe database scoped configuration options Describe automatic tuning Describe intelligent query processing 13 - Explore query performance optimization Understand query plans Explain estimated and actual query plans Describe dynamic management views and functions Explore Query Store Identify problematic query plans Describe blocking and locking 14 - Evaluate performance improvements Describe wait statistics Tune and maintain indexes Understand query hints 15 - Explore performance-based design Describe normalization Choose appropriate data types Design indexes 16 - Automate deployment of database resources Describe deployment models in Azure Automate deployment by using Azure Resource Manager templates and Bicep Automate deployment by using PowerShell Automate deployment by using Azure CLI 17 - Create and manage SQL Agent jobs Create a SQL Server maintenance plan Describe task status notifications 18 - Manage Azure PaaS tasks using automation Explore Elastic jobs Understand Azure Automation Build an automation runbook Automate database workflows by using Logic Apps Monitor automated tasks 19 - Describe high availability and disaster recovery strategies Describe recovery time objective and recovery point objective Explore high availability and disaster recovery options Describe Azure high availability and disaster recovery features for Azure Virtual Machines Describe high availability and disaster recovery options for PaaS deployments Explore an IaaS high availability and disaster recovery solution Describe hybrid solutions 20 - Explore IaaS and PaaS solutions for high availability and disaster recovery Describe failover clusters in Windows Server Configure Always-on availability groups Describe temporal tables in Azure SQL Database Describe active geo-replication for Azure SQL Database Explore auto-failover groups for Azure SQL Database and Azure SQL Managed Instance 21 - Back up and restore databases Back up and restore SQL Server running on Azure virtual machines Back up a SQL Server virtual machine Back up and restore a database using Azure SQL Database Additional course details: Nexus Humans DP-300T00: Administering Microsoft Azure SQL Solutions 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-300T00: Administering Microsoft Azure SQL Solutions 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 Training Course More energy companies today are setting ambitious net-zero targets and are expected to pour billions into the voluntary carbon offset market by the end of this decade. To get to net zero emissions, companies will need to balance emissions with nature and technology-based offsets. Markets are the best tool for connecting carbon sources and sinks. Many countries will not have enough supply inside their borders and will need to co-operate with those who have extra greenhouse gas removal potential. The energy industry is in search of effective climate tools as pressure mounts from investors and consumers for more progress on fighting rising emissions. Corporations fighting to cut their carbon footprint have for years focused on internal reduction measures. Many are now adding to that effort by turning to carbon credits, a process made easier as verification and registration tools mature. One particular category of carbon offsets leads the way: high-quality, nature-based carbon credits. These represent the largest category of carbon credit projects in the voluntary carbon market, comprising nearly half of credits issued. Public concern about this practice focused on the additionality, leakage, and integrity of carbon offsets that are created through reforestation, land preservation, carbon capture and other projects. Lack of standardization and government regulation has also increased uncertainty for all participants in carbon markets, creating risks for developers of credit-generating projects and offset purchasers. Demand for higher-quality offsets will value projects that were subjected to due diligence and rely upon reputable third-party verification. Companies purchasing offsets generated by permanent and quantifiable projects will therefore be in the best position moving forward. In this highly interactive training course, your course instructor will guide you through the latest developments and best procurement practices to successfully operate in the voluntary carbon market. Training Objectives At the end of this course, the participants will be able to: Discover the current state of the carbon economy Gain insights into the voluntary carbon market Learn about the different type carbon credits available Examine how companies can reach net zero target by using carbon offsets Uncover best practices in carbon credit procurement strategy Learn the pricing dynamics carbon credits Examine how to identify and ensure high quality credits Obtain key learning from flawed carbon offset projects Target Audience This course is intended for: Energy transition team leaders Carbon credit procurement professionals ESG strategy team leaders Finance and accounting professionals Low carbon business analysts or economists Corporate business sustainability professionals Legal, compliance and regulatory professionals Carbon trading professionals Course Level Intermediate Trainer Your expert course leader is a skilled and accomplished professional with over 25 years of extensive C-level experience in the energy markets worldwide. He has a strong expertise in all the aspects of (energy) commodity markets, international sales, marketing of services, derivatives trading, staff training and risk management within dynamic and high-pressure environments. He received a Master's degree in Law from the University of Utrecht in 1987. He started his career at the NLKKAS, the Clearing House of the Commodity Futures Exchange in Amsterdam. After working for the NLKKAS for five years, he was appointed as Member of the Management Board of the Agricultural Futures Exchange (ATA) in Amsterdam at the age of 31. While working for the Clearing House and exchange, he became an expert in all the aspects of trading and risk management of commodities. In 1997, he founded his own specialist-consulting firm that provides strategic advice about (energy) commodity markets, trading and risk management. He has advised government agencies such as the European Commission, investment banks, major utilities and commodity trading companies and various energy exchanges and market places in Europe, CEE countries, North America and Asia. Some of the issues he has advised on are the development and implementation of a Risk Management Framework, investment strategies, trading and hedging strategies, initiation of Power Exchanges (APX) and other trading platforms, the set-up of (OTC) Clearing facilities, and feasibility and market studies like for the Oil, LNG and the Carbon Market. The latest additions are (Corporate) PPAs and Artificial Intelligence for energy firms. He has given numerous seminars, workshops and (in-house) training sessions about both the physical and financial trading and risk management of commodity and carbon products. The courses have been given to companies all over the world, in countries like Japan, Singapore, Thailand, United Kingdom, Germany, Poland, Slovenia, Czech Republic, Malaysia, China, India, Belgium and the Netherlands. He has published several articles in specialist magazines such as Commodities Now and Energy Risk and he is the co-author of a book called A Guide to Emissions Trading: Risk Management and Business Implications published by Risk Books in 2004. 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 post training support and fees applicable Accreditions And Affliations

About this Training Course Liquefied Natural Gas (LNG) has provided intercontinental mobility to natural gas, which now provides about 25% of the global primary energy. Being the cleanest fossil fuel, natural gas/LNG consumption is forecasted to grow in all future scenarios. With the entry of various players, including Trading companies, the LNG value chain is becoming increasingly complex, and a solid understanding of its economics and management of its interfaces have become crucial to identify and assess investment opportunities and risks. Recent market disturbances caused by COVID-19, Oil & Gas price instabilities - coupled with the political (Ukraine/Russia) challenges - make a deep understanding of LNG Value Chain Logistics and Economics even more essential to ensure the security of energy supplies sustainably and profitably. This intermediate level 3 full-day course starts with a concise introduction to the LNG business. Thereafter, the elements of the LNG value chain are described, and their individual economics analysed. A Business Activity Model along the value chain will be developed and discussed in depth, covering the following key processes: 'Buy Gas - Transport Gas - Liquefy Gas - Sell LNG/Products - Ship LNG - Regasify LNG' The integrated chain economics will then be developed and quantified. A hands-on group workshop/exercise developing the economic case of a full-sized Liquefaction project will be carried out, considering the forecasted cash flows throughout the project life, the location of the plant, its markets, project sensitivities and profitability assessment. Participants will be provided with Excel based tools/models (LNG Liquefaction project development Net Present Value (NPV) analyses, Shipping Freight Calculations and Economics) to work through the exercises and also for their future personal use. Training Objectives After the completion of this course, participants will be able to: Understand how the LNG Value Chain operates, bound by the relevant Contracts and Agreements. Learn the basic economic parameters (operating, capital costs, financing, profitability) of each major element of the value chain. Appreciate the complexity of the value chain, and the associated opportunities and risks. Develop quantitative project evaluation skills. Explore options to maximise profitability in a given LNG value chain. Discuss best practices on how to manage, steer and govern these activities. Target Audience Technical, Operational, Shipping, Commercial, Project and Governance professionals who are already active in a specific section of the LNG Value Chain will directly benefit in developing a wider and deeper perspective on how the LNG Value Chain operations and can be optimised. Managers (Technical, Financial, Legal and Governance) less familiar with the specifics of the LNG Industry will also benefit from attending this VILT course, as they will obtain the required background to be able to set sharper targets, suitable performance indicators, and governance and performance assessment guidelines for units engaged in the chain. The course is most relevant for professionals engaged in the LNG industry at: National and International Oil & Gas/Energy Companies LNG Importers/Exporters/Traders/Shippers Government & Regulatory Agencies Finance Institutions It will also apply to the following audience: Business Development Managers Corporate Planning Professionals Project Developers Supply Planners & Scheduling Professionals Regulators Tax & Finance Advisors Compliance Officers Equity Analyst and Bankers Joint Venture Representatives, Board Directors Negotiators and Contracting Staff Trading Professionals Course Level Intermediate Trainer Your expert course leader is an Oil & Gas/LNG professional with more than 35 years of international experience, majority of which was gained at Shell International Joint Ventures engaged in Oil Refining, Supply / Trading, Gas Supply and LNG Businesses in the Netherlands, France, Thailand, Dominican Republic and Nigeria. Since 2004, he has had several roles in the management of the LNG Value Chain including the Commercial Operational Management of Nigeria LNG (NLNG). He played an active role in the start-up and integration of LNG trains 4, 5 and 6 with NLNG becoming the 3rd largest LNG producer in the world in 2007. Commercial operations spanned 4 Gas Supply, 11 LNG Sales & Purchase Agreements, ad-hoc LPG and Condensate Sales and LNG Ship Chartering contracts. Under his supervision, more than 2,000 LNG cargoes were exported. He was part of the organizational transformation of the company from a Project-based set-up to a Production / Commercial based structure and implemented an 'Integrated Planning and Scheduling Department' in which he optimized the value chain (Buy-Gas - Liquify Gas to LNG - Sell - Ship LNG). Staff competence management was one of his focus areas during this period. He was also the NLNG representative on JV Technical, Commercial, Shipping Committees where he interfaced with Government & Regulatory authorities. In 2014, he was appointed as Shell Shareholder representative to NLNG and became a Non-Executive Board member to NLNG companies, including Bonny Gas Transport (BGT) managing 24 LNG Ships. During this period, he was involved in the Economic and Technical steering of the Shipping Fleet and Liquefaction Plant Rejuvenation projects and a further capacity expansion of liquefaction plant which resulted in the achievement of NLNG train 7 project FID in 2019. Since 2016, he has been active as an independent consultant. He co-authored 2 patents and more than 30 published papers/presentations. He holds a PhD from Delft University of Technology in the Netherlands and a MSc and BSc in Chemical Engineering from the University of Birmingham, UK. 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 post training support and fees applicable Accreditions And Affliations

MySQL Performance & Tuning training course description This MySQL Performance & Tuning course is designed for Database Administrators, Application Developers and Technical Consultants who need to monitor and tune the performance of MySQL servers and databases. The course provides practical experience in monitoring and tuning MySQL servers and databases. Note: This MySQL Performance & Tuning course does not cover clustering (other than at overview level), replication or non-standard storage engines such as Falcon and PBXT. What will you learn Develop a monitoring and tuning plan Use server configuration and status variables. Identify and improve problem queries. Make efficient use of indexes. Monitor and size memory caches and locks. Tune the MyISAM and InnoDB storage engine. Evaluate the use of partitioning for performance. MySQL Performance & Tuning training course details Who will benefit: Anyone who wishes to monitor and tune MySQL performance. Prerequisites: Delegates must have a working knowledge of MySQL Database Administration Duration 3 days MySQL Performance & Tuning training course contents Introduction to performance tuning Tuning overview, Resolving performance issues, Recommended approach to tuning, Items to evaluate, Where to look, Planning a monitoring routine, Building a new database for performance, Tuning an existing database, Setting suitable goals. MySQL performance tuning tools Administration tools, the information schema, performance-related SHOW commands, benchmarking tools, the MySQL performance schema, MonYog. Hands on Obtaining performance information. Schema design Normalisation, de-normalisation, naming conventions, load generation, stress testing and benchmarking tools, selecting data types, data types, character sets, choosing storage engines. Hands on effects of design on performance. Statement tuning Overview of statement tuning, identifying problem queries, the optimizer, explain, explain extended. Hands on identifying problem queries and using explain. Indexes Index overview, Types of index, Index tuning, Indexes and joins. Hands on Indexes and performance. Server configuration and monitoring Server configuration variables, server status variables, table cache, multi-threading, connection issues, query cache. Hands on setting and interpreting server variables and caching. Locking Types of locking, locking and storage engines, effects of locking on performance. Hands on locking and performance. The InnoDB engine Transactions, crash recovery, locking, monitoring InnoDB, caches and buffers, configuring data files, configuring the log files. Hands on InnoDB configuration and performance. Other storage engines MyISAM engine, merge engine, archive engine, memory engine, blackhole engine, CSV engine, the Spider engine, the ColumnStore engine, the MyRocks engine, mixing sorage engines. Hands on storage engine performance. Overview of clustering and performance Advantages of performance, advantages of clustering, performance issues and clustering, the NDBCluster engine, the Galera cluster, the Percona XtraDB cluster, MySQL InnoDB cluster, the federated engine, the federatedX engine, overview of other high availability techniques. NOSQL and Mencached overview. Dumping and loading data SQL statements versus delimited data, parameters affecting dump performance, parameters affecting load performance. Hands on dump and load performance. Partitioned tables Partitioned tables concepts, range partitioning, hash partitioning, key partitioning, list partitioning, composite partitioning or subpartitioning, partition pruning. Hands on partitioned table performance.

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for software developers, testers, and architects who design and develop software in various programming languages and platforms, including desktop, web, cloud, and mobile, and who want to improve their ability to deliver software that is of high quality, particularly regarding security and privacy. This course is also designed for students who are seeking the CertNexus Cyber Secure Coder (CSC) Exam CSC-210 certification Overview In this course, you will employ best practices in software development to develop secure software.You will: Identify the need for security in your software projects. Eliminate vulnerabilities within software. Use a Security by Design approach to design a secure architecture for your software. Implement common protections to protect users and data. Apply various testing methods to find and correct security defects in your software. Maintain deployed software to ensure ongoing security... The stakes for software security are very high, and yet many development teams deal with software security only after the code has been developed and the software is being prepared for delivery. As with any aspect of software quality, to ensure successful implementation, security and privacy issues should be managed throughout the entire software development lifecycle. This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects. You will learn general strategies for dealing with security defects and misconfiguration, how to design software to deal with the human element in security, and how to incorporate security into all phases of development. Identifying the Need for Security in Your Software Projects Identify Security Requirements and Expectations Identify Factors That Undermine Software Security Find Vulnerabilities in Your Software Gather Intelligence on Vulnerabilities and Exploits Handling Vulnerabilities Handle Vulnerabilities Due to Software Defects and Misconfiguration Handle Vulnerabilities Due to Human Factors Handle Vulnerabilities Due to Process Shortcomings Designing for Security Apply General Principles for Secure Design Design Software to Counter Specific Threats Developing Secure Code Follow Best Practices for Secure Coding Prevent Platform Vulnerabilities Prevent Privacy Vulnerabilities Implementing Common Protections Limit Access Using Login and User Roles Protect Data in Transit and At Rest Implement Error Handling and Logging Protect Sensitive Data and Functions Protect Database Access Testing Software Security Perform Security Testing Analyze Code to find Security Problems Use Automated Testing Tools to Find Security Problems Maintaining Security in Deployed Software Monitor and Log Applications to Support Security Maintain Security after Deployment

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 3 Days 18 CPD hours This course is intended for The primary audience for this course is people who are moving into a database role, or whose role has expanded to include database technologies. Developers that deliver content from SQL Server databases will also benefit from this material. Overview After completing this course, you will be able to: Describe key database concepts in the context of SQL Server Describe database languages used in SQL Server Describe data modelling techniques Describe normalization and denormalization techniques Describe relationship types and effects in database design Describe the effects of database design on performance Describe commonly used database objects This course is provided as an introductory class for anyone getting started with databases. It will be useful to programmers and other IT professionals whose job roles are expanding into database management. Students will learn fundamental database concepts through demonstrations and hands-on labs on a SQL Server instance. This material updates and replaces course Microsoft course 10985 which was previously published under the same title. Module 1: Introduction to databases Introduction to Relational Databases Other Databases and Storage Data Analysis SQL Server Database Languages Module 2: Data Modeling Data Modelling Designing a Database Relationship Modeling Module 3: Normalization Fundamentals of Normalization Normal Form Denormalization Module 4: Relationships Introduction to Relationships Planning Referential Integrity Module 5: Performance Indexing Query Performance Concurrency Module 6: Database Objects Tables Views Stored Procedures, Triggers and Functions

Duration 3 Days 18 CPD hours This course is intended for This course is intended for IT professionals who are experienced in general Windows Server and Windows Client administration. Students should have a foundational knowledge of Windows PowerShell, which they can obtain by taking course 10961C: Automating Administration with Windows PowerShell. In addition, this course provides scripting guidance for Microsoft Azure administrators and developers who support development environments and deployment processes. Overview After completing this course, you will be able to: Create advanced functions. Use Microsoft .NET Framework and REST API in Windows PowerShell. Handle script errors. Use XML, JSON, and custom formatted data. Manage Microsoft Azure resources Analyze and debug scripts Understand Windows PowerShell workflow. This course teaches students how to automate administrative tasks using PowerShell. Students will learn crucial scripting skills such as creating advanced functions, writing controller scripts, and handling script errors. Candidates will learn how to use PowerShell when working with Microsoft Azure, SQL Server, Active Directory, IIS, Windows PowerShell Workflow, .NET resources, the REST API and XML, CSV & JSON formatted data files.This course replaces retired Microsoft course 10962. Module 1: Creating advanced functions Lesson 1: Converting a command into an advanced function Lesson 2: Creating a script module Lesson 3: Defining parameter attributes and input validation Lesson 4: Writing functions that accept pipeline input Lesson 5: Producing complex pipeline output Lesson 6: Using comment-based Help Lesson 7: Using Whatif and Confirm parameters Module 2: Using Microsoft .NET Framework and REST API in Windows PowerShell Lesson 1: Using .NET Framework in PowerShell Lesson 2: Using REST API in PowerShell Module 3: Writing controller scripts Lesson 1: Understanding controller scripts Lesson 2: Writing controller scripts with a user interface Lesson 3: Writing controller scripts that create reports Module 4: Handling script errors Lesson 1: Understanding error handling Lesson 2: Handling errors in a script Module 5: Using XML, JSON, and custom-formatted data Lesson 1: Working with XML formatted data Lesson 2: Working with JSON formatted data Lesson 3: Working with custom-formatted data Module 6: Enhancing server management with Desired State Configuration and Just Enough Administration Lesson 1: Implementing Desired State Configuration Lesson 2: Implementing Just Enough Administration Module 7: Analyzing and debugging scripts Lesson 1: Debugging in Windows PowerShell Lesson 2: Analyzing and debugging an existing script Module 8: Understanding Windows PowerShell Workflow Lesson 1: Understanding Windows PowerShell Workflows Lesson 2: Running Windows PowerShell Workflows

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution