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Microsoft Active Directory course description A thorough understanding of this system is essential for anyone managing enterprise MS networks. Essential theory is complimented with a high level of hands on practice allowing delegates to observe the idiosyncrasies of Active Directory and Group Policy at first hand. Delegates learn the fundamental theory of AD and progress onto building a multi-domain network in the classroom. The course includes troubleshooting methods, and essential maintenance procedures. This course is designed to teach you the skills needed for day to day management of these technologies. What will you learn Install AD on multiple PCs. Use the tools to create and manage objects. Create appropriate group policies to restrict selected user's desktops and network access. Install DNS to support Active Directory without loosing Internet Connectivity. Maintain and troubleshoot AD problems Backup Active Directory. Microsoft Active Directory course details Who will benefit: Technical staff working with AD based networks. Prerequisites: Supporting Windows server. Duration 3 days Microsoft Active Directory course contents Introduction to Active Directory Network authentication methods, Active Directory defined, AD naming conventions, network management with AD, AD structures: Domains, Organisational Units, Forests & Trees, Sites, The Global Catalogue. Windows 2003 new features, installing AD. Hands on Installing an AD network. Windows overview Management methods Server management tools, installing the additional tools, Terminal Server: Administration mode, Administrator accounts in AD, Local Security Policy. Hands on Install the management tools, Management using Terminal Services. Creating & Managing Objects (a quick look) AD management tools, AD users and computers, Creating & managing OUs, User Accounts and groups, controlling access to AD objects, moving objects, Publishing resources, locating objects in AD, delegating authority. Hands on Creating a control OU structure and delegating authority. Introduction to Group Policies What are Group Policies? Where Group Policy data is stored, security, Group Policy flow. Hands on Implementing Group Policies Working with Group Policies Local security templates, administrative templates, scripts, folder redirection, software deployment. Hands on Scripts, redirecting the start menu, creating a secure, robust desktop environment. Implementing DNS DNS basics, troubleshooting, implementing DNS zones. Hands on Building a unified DNS solution. Maintaining and managing the AD database AD support tools, database internal structure, replication, replication tools, Single Operations Masters, tools for maintenance, maintenance techniques, Backing up AD, Directory Services restore mode, NTDSUtil, Authoritative & non-authoritative restoration, rebuilding. Hands on NTDSUtil.

Duration 4.5 Days 27 CPD hours This course is intended for This is an intermediate course intended for IBM i system administrators, data processing managers and other individuals who implement and manage security, backup and recovery, system software and problem determination. This course is not recommended for s Overview Describe and implement the components of IBM i security, such as user profile, group profile, authorization list, adopted authority and object / resource security Develop a security plan for your Power Systems with IBM i Describe the options to implement security auditing Develop a plan to audit security on your Power Systems with IBM i Describe the IBM i availability products and features and choose the option(s) that best fit your company requirements Describe how to backup and recover user, IBM and full system data on your Power Systems with IBM i Develop a backup and recovery plan for your Power Systems with IBM i Describe the system diagnostics and problem determination procedures available on your Power Systems with IBM i Learn how to plan for, implement, and manage the ongoing operations of an IBM i. Class administration and introductions . IBM i overview and concepts . Management central overview . Security concepts and overview . System values . User security . Resource security . Security auditing . Designing security . IBM i availability overview . Disk management . Backup and recovery strategy using Save/Restore . Journal management . Commitment control overview . Backup and recovery planning . Problem determination . Overview of Systems Director Navigator for i . Introduction to BRMS .

Duration 3 Days 18 CPD hours This three-day instructor-led course is aimed at modern device management professionals looking to manage their enterprise devices using Microsoft Intune. This course will cover Enrolment, Application Management, Endpoint Security and Windows Autopilot as well as Azure Active Directory Conditional Access and Identity Protection. The delegates will learn how to enroll devices, deploy applications and manage them to maximize user productivity and device security. 1: Introduction to Microsoft Intune Mobile Device Management Microsoft Intune Azure Active Directory AAD Identity Protection AAD Conditional Access 2: Microsoft Intune Device Management Enrolling Devices Device Compliance Device Profiles Device Updates 3: Microsoft Intune Application Management Application Management Deploying Applications Application Configuration Managing Applications Policy Sets and Guided Scenarios 4: Microsoft Intune Endpoint Security Security Baselines and tasks Antivirus Disk Encryption Firewall Atack Surface reduction Endpoint detection and response Account Protection 5: Deploying Windows with Windows Autopilot Windows Autopilot overview Preparing for Windows Autopilot deployment Deploying Windows 11 using Windows Autopilot 6: Microsoft Intune Additional and Premium Features Remote Help Tunnel for Mobile Application Management Endpoint Privilege Management Advanced Endpoint Analytics Additional course details: Nexus Humans 55399 Implementing and Managing Microsoft Intune 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 55399 Implementing and Managing Microsoft Intune 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 This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools. Overview After completing this course, students will be able to: - Identify independent and dependent variables and measurement levels in their own analytical work scenarios. - Identify variables of interest in relational database tables. - Choose a data aggregation level and data set design appropriate for the intended analysis and tool. - Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others. - Create stored procedures, views, and functions to modularize data retrieval code. This course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. 1 - INTRODUCTION TO TSQL FOR BUSINESS INTELLIGENCE Two Approaches to SQL Programming TSQL Data Retrieval in an Analytics / Business Intelligence Environment The Database Engine SQL Server Management Studio and the CarDeal Sample Database Identifying Variables in Tables SQL is a Declarative Language Introduction to the SELECT Query Lab 1: Introduction to TSQL for Business Intelligence 2 - TURNING TABLE COLUMNS INTO VARIABLES FOR ANALYSIS: SELECT LIST EXPRESSIONS, WHERE, AND ORDER BY Turning Columns into Variables for Analysis Column Expressions, Data Types, and Built-in Functions Column aliases Data type conversions Built-in Scalar Functions Table Aliases The WHERE clause ORDER BY Lab 1: Write queries 3 - COMBINING COLUMNS FROM MULTIPLE TABLES INTO A SINGLE DATASET: THE JOIN OPERATORS Primary Keys, Foreign Keys, and Joins Understanding Joins, Part 1: CROSS JOIN and the Full Cartesian Product Understanding Joins, Part 2: The INNER JOIN Understanding Joins, Part 3: The OUTER JOINS Understanding Joins, Part 4: Joining more than two tables Understanding Joins, Part 5: Combining INNER and OUTER JOINs Combining JOIN Operations with WHERE and ORDER BY Lab 1: Write SELECT queries 4 - CREATING AN APPROPRIATE AGGREGATION LEVEL USING GROUP BY Identifying required aggregation level and granularity Aggregate Functions GROUP BY HAVING Order of operations in SELECT queries Lab 1: Write queries 5 - SUBQUERIES, DERIVED TABLES AND COMMON TABLE EXPRESSIONS Non-correlated and correlated subqueries Derived tables Common table expressions Lab 1: Write queries 6 - ENCAPSULATING DATA RETRIEVAL LOGIC Views Table-valued functions Stored procedures Creating objects for read-access users Creating database accounts for analytical client tools Lab 1: Encapsulating Data Retrieval Logic 7 - GETTING YOUR DATASET TO THE CLIENT Connecting to SQL Server and Submitting Queries from Client Tools Connecting and running SELECT queries from: Excel PowerBI RStudio Exporting datasets to files using Results pane from SSMS The bcp utility The Import/Export Wizard Lab 1: Getting Your Dataset to the Client Additional course details: Nexus Humans 55232 Writing Analytical Queries for Business Intelligence 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 55232 Writing Analytical Queries for Business Intelligence 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 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

Teachers will become familiar with the software, aiding each learner access to their college dashboard as a designer, so they can complete a heat loss report and other heating design elements. Furthermore each learner will have access to send surveys from the heat engineer app (Apple or Android) which once sent will be received within the college dashboard. Where teachers can assess the survey.

Duration 3 Days 18 CPD hours This course is intended for The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Prerequisites Understanding core data concepts. Knowledge of working with relational data in the cloud. Knowledge of working with non-relational data in the cloud. Knowledge of data analysis and visualization concepts. DP-900T00 Microsoft Azure Data Fundamentals is recommended 1 - Discover data analysis Overview of data analysis Roles in data Tasks of a data analyst 2 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 3 - Get data in Power BI Get data from files Get data from relational data sources Create dynamic reports with parameters Get data from a NoSQL database Get data from online services Select a storage mode Get data from Azure Analysis Services Fix performance issues Resolve data import errors 4 - Clean, transform, and load data in Power BI Shape the initial data Simplify the data structure Evaluate and change column data types Combine multiple tables into a single table Profile data in Power BI Use Advanced Editor to modify M code 5 - Design a semantic model in Power BI Work with tables Create a date table Work with dimensions Define data granularity Work with relationships and cardinality Resolve modeling challenges 6 - Add measures to Power BI Desktop models Create simple measures Create compound measures Create quick measures Compare calculated columns with measures 7 - Add calculated tables and columns to Power BI Desktop models Create calculated columns Learn about row context Choose a technique to add a column 8 - Use DAX time intelligence functions in Power BI Desktop models Use DAX time intelligence functions Additional time intelligence calculations 9 - Optimize a model for performance in Power BI Review performance of measures, relationships, and visuals Use variables to improve performance and troubleshooting Reduce cardinality Optimize DirectQuery models with table level storage Create and manage aggregations 10 - Design Power BI reports Design the analytical report layout Design visually appealing reports Report objects Select report visuals Select report visuals to suit the report layout Format and configure visualizations Work with key performance indicators 11 - Configure Power BI report filters Apply filters to the report structure Apply filters with slicers Design reports with advanced filtering techniques Consumption-time filtering Select report filter techniques Case study - Configure report filters based on feedback 12 - Enhance Power BI report designs for the user experience Design reports to show details Design reports to highlight values Design reports that behave like apps Work with bookmarks Design reports for navigation Work with visual headers Design reports with built-in assistance Tune report performance Optimize reports for mobile use 13 - Perform analytics in Power BI Explore statistical summary Identify outliers with Power BI visuals Group and bin data for analysis Apply clustering techniques Conduct time series analysis Use the Analyze feature Create what-if parameters Use specialized visuals 14 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 15 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 16 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 17 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method Additional course details: Nexus Humans PL-300T00: Microsoft Power BI Data Analyst 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 PL-300T00: Microsoft Power BI Data Analyst 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.

Is your learner ready to transition to a Speech Generating Device? Do you need help selecting a device and/or preparing your learner for the transition? This training will help get your questions answered! With the current influx of communication devices and apps to the market how do we ensure that basic functional communication skills are maintained and taught right from the beginning? Speech Generating Devices (SGDs) were first introduced for people with motor difficulties like cerebral palsy and now these devices are being introduced to our learners with autism and other related communication difficulties. for these populations, language and cognition are often compromised and basic social and communication skills have not always been mastered prior to the introduction of a device. Because of this, the way we teach the use of SGDs needs to be specifically tailored to fit the needs of each individual paying attention to devices capabilities vs. user capabilities. This full-day workshop will describe procedures for analysing a learner's current PECS skills to determine candidacy for transitioning to a Speech Generating Device (SGD), choosing a device, and teaching functional use of the device, and why we must teach the basic principles of communication to our learner first to ensure positive outcomes are achieved. *Participants should bring a Speech Generating Device (SGD) to the training for use during a variety of activities. WATCH VIDEO TOPICS COVERED INCLUDE Review of the PECS Protocol The unique challenges of learners with complex communication needs Procedures for analysing current PECS skills Determining candidacy for transitioning from PECS to a Speech Generating Device The 5 criteria for appropriate device selection Preparing the learner for the transition Using elements of the PECS protocol to teach functional SGD use Problem solving SGD use Tuition Includes: Detailed Handout with space for note taking, Delegate Practise Bag and Certificate of Attendance. CEUs: 5.5 BACB CEUs; Satisfactory completion of this course requires participants to be present for the duration of the course and to participate in all student responding activities (e.g. questions, role play, quizzes, and surveys). Pyramid Educational Consultants is an approved BACB ACE Provider for Learning (Type 2) Continuing Education Credits. The BACB does not warrant, endorse, sponsor, approve, or partner with the event, organisation, or instructor.

Elevate your understanding of relay protection in power systems with EnergyEdge's specialized classroom training course and gain valuable insights.

About this Virtual Instructor Led Training (VILT)  Electrical machines, mainly power transformers and electric motors are critical equipment that run production, and it must operate without any abnormalities. A wide variety of tests and standards have been developed to assist manufacturers and users of motors and transformer winding, assess the condition of the electrical insulation. The objective of this training course is to provide an understanding of power transformers and electric motors, their materials, components, and how they operate. It will also emphasize the importance of transformer life management, especially for those transformers and electric motors which have been in operation for than 10 years. The course will address in detail all aspects related to transformer principles, calculations, operation, testing and maintenance. Training Objectives This course aims to provide participants with the understanding of the fundamentals and constructional features of power transformers and electric motors, with particular reference to the design, testing, operation and maintenance of transformers in power systems. Delegates will gain a detailed appreciation of the following: Practical solutions for specifying, operating and maintaining power transformers and electric motors in a utility or plant environment Comprehensive understanding of principles, protection, maintenance and troubleshooting of power transformers and electric motors The necessary safe procedures relating to transformer operation and related circuitry Understand the principles of operation of the transformer and electric motors Identify the different features of power transformers and electric motors Appreciate the principles of transformer design, ratings, winding, core structure and materials, insulation and cooling methods, insulation and lifetime Utilize thermal limits and loading guides of transformers Analyze transformer and electric motors failure modes Target Audience Engineers of all disciplines Managers Technicians Maintenance personnel Other technical individuals Course Level Basic or Foundation Training Methods The VILT will be delivered online in 4 half-day sessions comprising 4 hours per day, with 1 x 10 minutes break per day, including time for lectures, discussion, quizzes and short classroom 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 the course. Trainer Our key expert is actively involved in electrical inspections, energy audits, energy efficiency and technical consultation for M&E activities for industrial and commercial sectors. He is involved in testing and commissioning works of factory substations of up to 132kV system. He previously worked for Jimah coal-fired power plant in Port Dickson for 9 years with his last position being Electrical Maintenance Section Head. He was involved in the commissioning of coal-fired power plant mainly with 500kV generator transformer, 934 MVA generator, and up to 33kV MV motors and switchgear panels. Our key expert has managed the maintenance team to perform routine maintenance activities (together with supporting tools such as motor lube oil analysis, infrared thermography analysis, transformer oil analysis) & electrical troubleshooting and plant outages for critical and non-critical equipment. Besides that, our key expert has published several IEEE conference papers and journals such as: (2009). Effectiveness of auxiliary system monitoring & continuous hydrogen scavenging operation on hydrogen-cooled generator at power plant. In Energy and Environment, 2009. ICEE 2009. 3rd International Conference on (pp. 151-160). IEEE. (2010). Study on electric motor mass unbalance based on vibration monitoring analysis technique. In Mechanical and Electrical Technology (ICMET), 2010 2nd International Conference on (pp. 539-542). IEEE. (2012). Re-Design of AC Excitation Busduct based on Infrared (IR) Thermography: Condition-Based Monitoring (CBM) data analysis. eMaintenance, 101. (2016). Energy Saving Studies for a University Campus: An Educational-Based Approach, 3rd International Conference on Language, Education, Humanities and Innovation 2016. 'Grid-tied photovoltaic and battery storage systems with Malaysian electrcity tariff - A review on maximum demand shaving.' Energies 10.11 (2017): 1884 'Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia.' Energies 12.18 (2019): 3531 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