2998 Development courses in Leicester delivered Live Online

Overview There are many companies that have designed a creative environment for their employees to help them relax and spark creative thinking to enhance the performance of the people working in the organisation. The creative way help boost the mind of the employees and thereby generate a positive attitude. This course will help organizations to do regular brainstorming sessions when working on a project to allow employees to contribute and build on a project. This will create an immense engagement as their team members are involved in the creative process.

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.

About this training course Business Impact: The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets. Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles. Unique Features: Eight business use cases covering their business impact, code walkthroughs for most all and solution approach. Industry data sets for participants to practice on and take home. No software or complicated Python frameworks required. Training Objectives After the completion of this training course, participants will be able to: Understand digital oil field transformation and its impact on business Examine machine learning methods Review workflows and code implementations After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models Target Audience This training course is suitable and will greatly benefit the following specific groups: Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets Course Level Intermediate Advanced Training Methods The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution. Course Duration: 2 days in total (14 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts Knowledge of Python is not a must but preferred to get the full benefit. The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free) Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. 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 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

Project Estimating and Scheduling: Virtual In-House Training Establishing realistic estimates and goals for projects that support business objectives and meet client expectations is one of the most challenging aspects of project planning. Delivering those results within the agreed-upon time, cost, and quality constraints is also challenging. Attempting to meet impossible deadlines with limited budgets often leads to unplanned product shortfalls, causing long-term support and utilization problems. We have all anguished about this recurring problem, but without having the skills or knowledge to take action, we are unable to break the cycle! The goal of this course is for you to be able to support business objectives and meet client expectations by selecting the right planning approach for realistic and cost effective schedules, as well as project budgets. To achieve that, you will focus on gaining the necessary knowledge, skills, and techniques. What You Will Learn At the end of this program, you will be able to: Use the work breakdown structure (WBS) as the basis for effective estimating of project resources Estimate effort and duration using a variety of techniques Develop preliminary schedules using the critical path method Apply a variety of optimization techniques to refine preliminary schedules Establish realistic schedule and cost baselines, with appropriate contingency reserves Explain how earned value management (EVM) contributes to control time and cost performance Foundation Concepts Project management basic definitions and concepts PES Key driver: competing constraints PES Process and success factors Project Definition and the WBS Project definition overview Work Breakdown Structure (WBS) Decomposition: WBS development technique Resource Planning Resource planning overview Identifying resource requirements Identifying and filling resource gaps Applying resource planning tools Effort and Duration Estimating Estimating overview Estimating perspectives and approaches Estimating techniques Effort and duration estimating best practices Project Scheduling Overview of project scheduling Dependencies and the project network diagram Critical path method (CPM) Optimizing the schedule Budget, Risk, and Contingency Planning Overview of budget, risk, and contingency planning Estimating costs Determining the budget Project risk management processes Planning contingency reserves Project Baseline and Control Overview of project baseline Negotiating and the project baseline Earned value management (EVM) Project variances and actions Project control

Overview By the end of this Fundamentals of Transfer Pricing Strategies training course, participants will be able to: Acquire basic technical knowledge of transfer pricing Appreciate the importance of the arm's length principle Identify the different stages of a typical transfer pricing analysis Developing a high-level appreciation of the transfer pricing including tax areas and opportunities for multinationals Analyze the current transfer pricing legislative framework Be updated on recent developments in transfer pricing

Guided Teaching Practice (20 Hours – 8 Sessions – 4 Days)

Overview Objectives Define Policies and Procedures Differentiate between Policies and Procedures Explain the importance of Policies and Procedures Build and understand the SOP (Standard Operating Procedures) Define the roles and responsibilities of employees in various departments Abide by the Code of Conduct, the acceptable behaviour standards Justify how the Policies and Procedures help employees safeguard their self-respect Give equal opportunities to all the employees

Overview Performance management is a continuous process which involves making sure the performance of your employees contributes to organisational and team goals. Having effective employment management in place helps everyone in the organisation to know what the business is trying to achieve, the skill and competencies they need to fulfil their role and how they can develop their performance to develop the organisation.

Overview To achieve maximum effectiveness, managers and professionals must continually expand their business knowledge and sharpen their skills. This program is designed to achieve this goal in a time-efficient manner. Integration of Downstream Refining and Petrochemicals to achieve greater efficiencies is yet another critical factor in this business which will be covered in this course