1695 Computing courses in Stone delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level course designed to teach experienced systems administrators how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Previous Hadoop experience is not required. Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to: Understand the benefits of distributed computing Understand the Hadoop architecture (including HDFS and MapReduce) Define administrator participation in Big Data projects Plan, implement, and maintain Hadoop clusters Deploy and maintain additional Big Data tools (Pig, Hive, Flume, etc.) Plan, deploy and maintain HBase on a Hadoop cluster Monitor and maintain hundreds of servers Pinpoint performance bottlenecks and fix them Apache Hadoop is an open source framework for creating reliable and distributable compute clusters. Hadoop provides an excellent platform (with other related frameworks) to process large unstructured or semi-structured data sets from multiple sources to dissect, classify, learn from and make suggestions for business analytics, decision support, and other advanced forms of machine intelligence. This is an introductory-level, hands-on lab-intensive course geared for the administrator (new to Hadoop) who is charged with maintaining a Hadoop cluster and its related components. You will learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Introduction Hadoop history and concepts Ecosystem Distributions High level architecture Hadoop myths Hadoop challenges (hardware / software) Planning and installation Selecting software and Hadoop distributions Sizing the cluster and planning for growth Selecting hardware and network Rack topology Installation Multi-tenancy Directory structure and logs Benchmarking HDFS operations Concepts (horizontal scaling, replication, data locality, rack awareness) Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, DataNode) Health monitoring Command-line and browser-based administration Adding storage and replacing defective drives MapReduce operations Parallel computing before MapReduce: compare HPC versus Hadoop administration MapReduce cluster loads Nodes and Daemons (JobTracker, TaskTracker) MapReduce UI walk through MapReduce configuration Job config Job schedulers Administrator view of MapReduce best practices Optimizing MapReduce Fool proofing MR: what to tell your programmers YARN: architecture and use Advanced topics Hardware monitoring System software monitoring Hadoop cluster monitoring Adding and removing servers and upgrading Hadoop Backup, recovery, and business continuity planning Cluster configuration tweaks Hardware maintenance schedule Oozie scheduling for administrators Securing your cluster with Kerberos The future of Hadoop

Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for all users of computers, mobile devices, networks, and the Internet, to enable them to use technology more securely and minimize digital risks, regardless of technical ability. This course is also designed for you to prepare for the CyberSAFE credential. You can obtain your CyberSAFE certificate by completing the CyberSAFE credential process on the CHOICE platform following the course presentation. Overview In this course, you will identify many of the common risks involved in using conventional computing technology, as well as ways to use it safely, to protect yourself from those risks. You will: Identify security compliance measures. Address social engineering attempts. Secure devices such as desktops, laptops, tablets, smartphones, and more. Use the Internet securely. Welcome to CyberSAFE: Exam CBS-410. Regardless of your computer experience, this class will help you become more aware of technology-related risks and what you can do to protect yourself and your organization from them. This course will help you to:Understand both security and compliance needs and requirements.Recognize and avoid phishing and other social engineering attempts.Recognize and avoid viruses, ransomware, and other malware.Help ensure data security on computers, mobile devices, networks, the Internet, and in the cloud.In this course, you will use discussions, case studies, and the experiences of your instructor and fellow students to explore the hazards and pitfalls of technology and learn how to use that technology safely and securely. Identifying Security Compliance Measures Topic A: Identify Organizational Compliance Requirements and Resources Topic B: Identify Legal Compliance Requirements and Resources Topic C: Identify Industry Compliance Requirements and Resources Recognizing and Addressing Social Engineering Attacks Topic A: Recognize Phishing and Other Social Engineering Attacks Topic B: Defend Against Phishing and Other Social Engineering Attacks Securing Devices Topic A: Maintain Physical Security of Devices Topic B: Use Secure Authentication Methods Topic C: Protect Your Data Topic D: Defend Against Malware Topic E: Use Wireless Devices Securely Using the Internet Securely Topic A: Browse the Web Safely Topic B: Use Email Securely Topic C: Use Social Networks Securely Topic D: Use Cloud Services Securely Topic E: Work from Remote Locations Securely

About this Virtual Instructor Led Training (VILT) This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system. The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way. With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed. Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery. Training Objectives Upon completion of this VILT course, participants will be able to: Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues. Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices. Understand and analyze energy performance from main renewable energy systems. Get equipped on the insights into forecasting models for solar energy. Predict solar generation from weather forecasts using machine learning. Explore operational aspects of a complex power system with variability from both the supply & demand sides. Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation. Target Audience Engineers, planners and operations professionals from the following organizations: Energy aggregators who would like to understand the system operations of renewable energy power plants Renewable energy power system operator Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. 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 1 Days 6 CPD hours This course is intended for Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.

Duration 2 Days 12 CPD hours This course is intended for Students should have a fundamental understanding of financial principles and business operations. An understanding of cloud computing is helpful but isn't necessary. Overview After completing this course, students will be able to: Describe the core capabilities of Dynamics 365 finance and operations apps Describe the capabilities and functionality of Dynamics 365 Finance Describe the capabilities and functionality of Dynamics 365 Supply Chain Management Describe the capabilities and functionality of Dynamics 365 Commerce Describe the capabilities and functionality of Dynamics 365 Human Resources Describe the capabilities and functionality of Dynamics 365 Project Operations (ERP) This course will provide you with a broad introduction to the finance and operations capabilities of Dynamics 365. You will become familiar with the concept of enterprise resource management (ERP), as well as each of the finance and operations apps, including Dynamics 365 Supply Chain Management, Dynamics 365 Finance, Dynamics 365 Commerce , Dynamics 365 Human Resources, and the ERP capabilities of Dynamics 365 Project Operations. This course will include lecture as well as hands-on-labs. Module 1: Explore the core capabilities of Dynamics 365 finance and operations apps Get introduced to the finance and operations apps Create reports and integrate finance and operations apps Module 2: Learn the fundamentals of Dynamics 365 Finance Explore Dynamics 365 Finance core capabilities Explore general ledger Explore accounts payable and accounts receivable Explore expense management, fixed asset management, and budgeting Module 3: Learn the fundamentals of Dynamics 365 Supply Chain Management Identify general capabilities of Dynamics 365 Supply Chain Management Explore warehouse and inventory capabilities Explore manufacturing strategies in Dynamics 365 Supply Chain Management Module 4: Learn the fundamentals of Dynamics 365 Commerce Explore Dynamics 365 Commerce capabilities Explore Microsoft Dynamics 365 B2B e-commerce, Store Commerce and Clienteling Module 5: Learn the fundamentals of Dynamics 365 Human Resources Explore Dynamics 365 Human Resources core capabilities Explore personnel management capabilities in Dynamics 365 Human Resources Module 6: Learn the fundamentals of Dynamics 365 Project Operations Identify project life cycle management capabilities in Dynamics 365 Project Operations Explore the project planning and execution capabilities of 365 Project Operations

About this Virtual Instructor Led Training (VILT)  This 4 half-day Virtual Instructor Led Training (VILT) course will address a variety of contract and loan structuring issues associated with geothermal energy projects as well as comparison with solar, wind and battery storage. The course is designed to investigate how various project finance techniques and contract structures can be used to achieve a competitive power prices while maintaining a satisfactory equity return. Distinctive project finance features of power facilities that depend on geothermal, wind, hydro or solar resources will be evaluated with financial models. The course will cover economic analysis of exploration and development of geothermal facilities and how to incorporate probability of failure and success into an IRR framework. Subsequent sessions will address the theory underlying liquidated damages for delay, and performance as well as design of other incentives that is inherent in different contract structures. Nuanced project finance issues associated with structuring debt for renewable projects will be discussed including under what conditions the DSCR drives debt capacity and when the debt to capital ratio is instrumental. The course will be taught with a combination of theoretical discussions, term sheet review and focused financial models. Training Objectives Evaluation of the economic risks that arise from uncertainty associated with drilling exploration wells and development wells for geothermal projects. Analyse the theoretical issues with computing LCOE for geothermal projects compared to other renewable and non-renewable resources and the importance of cost of capital for renewable projects; Understand differences in contract structures for renewable projects and dispatchable projects and how a single price structure can distort incentives for efficient construction and operation; Understand components of financing that influence the bid price required to meet a required rate of return on equity and can result in relatively low prices with reasonable returns. Understand the importance of debt sizing constraints and what strategies are relevant when the debt to capital constraint applies relative to when the debt service coverage ratio drives the debt size; Understand how to compute P50, P90 and P99 for different projects driven by resource risk; Understand the difference between mean reverting resource variation and estimation mistakes that do not correct as the basis for 1-year P90 and 10-year P90. Understand under what conditions debt sculpting can affect returns and how synthetic sculpting can be used to increase returns when the DSCR constraint applies. Understand the theory of credit spreads, variable rate debt and interest rates in different currencies and compute the implied probability of default that in inherent in credit spreads. Understand how to evaluate the costs to equity investors and the benefits to lenders for various credit enhancements including DSRA accounts, cash flow sweeps and covenants. Course Level Basic or Foundation Training Methods The VILT will be delivered online in 4 sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day, including time for lectures, discussion, quizzes and short classroom exercises. Trainer Your expert course leader provides financial and economic consulting services to a variety of clients, he teaches professional development courses in an assortment of modelling topics (project finance, M&A, and energy). He is passionate about teaching in Africa, South America, Asia and Europe. Many of the unique analytical concepts and modelling techniques he has developed have arisen from discussion with participants in his courses. He has taught customized courses for MIT's Sloan Business School, Bank Paribas, Shell Oil, Society General, General Electric, HSBC, GDF Suez, Citibank, CIMB, Lind Lakers, Saudi Aramco and many other energy and industrial clients. His consulting activities include developing complex project finance, corporate and simulation models, providing expert testimony on financial and economic issues before energy regulatory agencies, and advisory services to support merger and acquisition projects. Our key course expert has written a textbook titled Corporate and Project Finance Modelling, Theory and Practice published by Wiley Finance. The book introduces unique modelling techniques that address many complex issues that are not typically used by even the most experienced financial analysts. For example, it describes how to build user-defined functions to solve circular logic without cumbersome copy and paste macros; how to write function that derives the ratio of EV/EBITDA accounting for asset life, historical growth, taxes, return on investment, and cost of capital; and how to efficiently solve many project finance issues related to debt structuring. He is in the process of writing a second book that describes a series of valuation and analytical mistakes made in finance. This book uses many case studies from Harvard Business School that were thought to represent effective business strategies and later turned into valuation nightmares. Over the course of his career our key course expert has been involved in formulating significant government policy related to electricity deregulation; he has prepared models and analyses for many clients around the world; he has evaluated energy purchasing decisions for many corporations; and, he has provided advice on corporate strategy. His projects include development of a biomass plant, analysis and advisory work for purchase of electricity generation, distribution and transmission assets by the City of Chicago, formulation of rate policy for major metro systems and street lighting networks, advocacy testimony on behalf of low income consumers, risk analysis for toll roads, and evaluation of solar and wind projects. He has constructed many advisory analyses for project finance and merger and acquisition transactions. Lastly, our key course expert was formerly Vice President at the First National Bank of Chicago where he directed analysis of energy loans and also created financial modelling techniques used in advisory projects. He received an MBA specializing in econometrics (with honours) from the University of Chicago and a BSc in Finance from the University of Illinois (with highest university honours). POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 4 Days 24 CPD hours This course is intended for Data center engineers Engineers (design, implementation, pre-sales, post-sales) Product managers and sales Overview After taking this course, you should be able to: Describe hyperconvergence, Cisco HyperFlex, and the components of Cisco HyperFlex Explain the Cisco Unified Computing System™ (Cisco UCS) and what makes it valuable to business Describe how Cisco HyperFlex Data Platform (HXDP) works Describe the physical components of Cisco HyperFlex Describe Cisco Intersight and introduce functionalities relevant to HyperFlex Install standard ESXi-based vSphere Cisco HyperFlex Manage your Cisco HyperFlex VMware ESXi-based cluster Describe how to maintain Cisco HyperFlex Design a Cisco HyperFlex solution Protect the data on your Cisco HyperFlex cluster using replication and data at rest encryption Describe a stretched cluster and how is it different from a standard cluster Describe an Edge cluster and how is it different from a standard cluster Perform basic troubleshooting tasks and explain Cisco Intersight The Implementing Cisco HyperFlex (DCIHX) v1.3 course shows you how to deploy and use the Cisco© HyperFlex? data platform to support multicloud workloads. You will become familiar with HyperFlex components and learn how to install, design, manage, and troubleshoot Cisco HyperFlex to support highly scalable and resilient multicloud implementations. You will also gain hands-on experience focused on installation, management, maintenance, and native replication, and you will explore cluster technologies as well as Cisco Intersight.? Introducing Hyperconvergence and Cisco HyperFlex Traditional Data Center Design What Is Hyperconvergence? Describing Cisco UCS: The Foundation of Cisco HyperFlex Cisco Server Deployment Models: Standalone Versus Managed Cisco UCS Managed Model Benefits Describing Cisco HyperFlex Software Components Virtual Machine Hypervisor Log-Structured File System Describing Cisco HyperFlex Hardware Components Introducing Cisco HyperFlex Servers Storage Technologies in Cisco HyperFlex Introducing Cisco Intersight Introducing Cisco Intersight Installing and Expanding Standard ESXi Cisco HyperFlex Installation Summary Software Prerequisites Managing Cisco HyperFlex in vSphere Environment Management Interfaces Overview Cisco HyperFlex Plugin for vCenter Maintaining Cisco HyperFlex Cisco HyperFlex Upgrade Overview Cisco HyperFlex Online Upgrade Designing Cisco HyperFlex Cluster Resiliency: VM-Level Cluster Resiliency: HXDP-Level Protecting Your Data Disaster Recovery Overview Third-Party Data Restore Solutions Introducing Cisco HyperFlex Stretched Deployment Stretched Cluster Overview Prerequisites Introducing Cisco HyperFlex EDGE Cisco HyperFlex EDGE Cluster Overview Prerequisites and Recommendations Troubleshooting Cisco HyperFlex Troubleshooting Guidelines Generating Tech Support Bundles

About this Virtual Instructor Led Training (VILT) This Virtual Instructor Led Training (VILT) course presents advanced methodologies that implement demand response and energy conservation programs in light of the integration of new technologies, regulatory changes and the accelerated penetration of renewable energy resources. This VILT course provides examples and case studies from North American and European jurisdictions covering the operational flexibilities on the demand side including requirements for new building codes to achieve zero net energy. The course describes a public agency's goals and objectives for conserving and otherwise reducing energy consumption and managing its demand for energy. This course presents the demand response implemented for economics and system security such as system balancing and relieving transmission congestion, or for system adequacy. The course also presents the principal attributes of conservation programs and the associated success criteria. In a system with increased penetration of renewable resources, demand response provides flexibility to system operators, helping them to maintain the reliability and the security of supply. Demand response is presented as a competitive alternative to additional power sources, enhancing competition and liquidity in electricity markets. The unique characteristics are discussed from a local, consumer centric and also from a system perspective bringing to life the ever changing paradigm for delivery energy to customers. Interoperability aspects and standards are discussed, as well as the consumer centric paradigm of Transactive Energy with IOT enabled flexibilities at system level, distribution networks and microgrids. The VILT course introduces the blockchain as a new line of defense against cyber threats and its increasing application in P2P transactions and renewable certificates. Our trainer's industry experience spans three decades with one of the largest Canadian utilities where she led or contributed to large operational studies and energy policies and decades of work with IEEE, NSERC and CIGRE. Our key expert also approaches to the cross sectional, interdisciplinary state of the art methodologies brings real life experience of recent industry developments. Training Objectives Innovative Digital Technologies How systems Facilitate Operational Flexibility on the Demand Side The Ecosystem of Demand Side Management Programs Advanced Machine Learning techniques with examples from CAISO Regulatory Policy Context and how to reduce regulatory barriers Industry Examples from NERC and ENTSO Relevant Industry standards: IEEE and IEC Manage Congestion with Distributed Operational Flexibilities: Grid to Distribution Controls; examples from NERC (NA) and ENTSO (Europe) Grid solutions with IEC 61850 communication protocols Decentralized grid controls The New Grid with accelerated V2G and Microgrids How DSM is and will be applied in Your System: Examples and discussions Target Audience Regulators and government agencies advising on public energy conservation programs All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices Any utility professional interested in understanding the new developments in the power industry Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 x 10 minutes break per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 2 Days 12 CPD hours This course is intended for This course benefits individuals responsible for configuring and monitoring devices running the Junos OS. Overview Describe the history and rationale for MPLS, as well as its basic terminology. Explain the MPLS label operations (push, pop, swap) and the concept of label-switched path (LSP). Describe the configuration and verification of MPLS forwarding. Describe the functionalities and operation of RSVP and LDP. Configure and verify RSVP-signaled and LDP-signaled LSPs. Select and configure the appropriate label distribution protocol for a given set of requirements. Describe the default Junos OS MPLS traffic engineering behavior. Explain the Interior Gateway Protocol (IGP) extensions used to build the Traffic Engineering Database (TED). Describe the Constrained Shortest Path First (CSPF) algorithm, its uses, and its path selection process. Describe administrative groups and how they can be used to influence path selection. Describe the default traffic protection behavior of RSVP-signaled LSPs. Explain the use of primary and secondary LSPs. Describe the operation and configuration of fast reroute. Describe the operation and configuration of link and node protection. Describe the operation and configuration of LDP loop-free alternate. Describe the LSP optimization options. Explain LSP priority and preemption. Describe the behavior of fate sharing. Describe how SRLG changes the CSPF algorithm when computing the path of a secondary LSP. Explain how extended admin groups can be used to influence path selection. Explain the purpose of several miscellaneous MPLS features. This two-day course is designed to provide students with a solid foundation on Multiprotocol Label Switching (MPLS). Course Outline Course Introduction MPLS Fundamentals MPLS Foundation Terminology MPLS Configuration MPLS Packet Forwarding Label Distribution Protocols Label Distribution Protocols RSVP LDP Routing Table Integration Mapping Next-Hops to LSPs Route Resolution Example Route Resolution Summary IGP Passive Versus Next-Hop Self for BGP Destinations Constrained Shortest Path First RSVP Behavior Without CSPF CSPF Algorithm CSPF Tie Breaking Administrative Groups Inter-area Traffic Engineered LSPs Traffic Protection and LSP Optimization Default Traffic Protection Behavior Primary and Secondary LSPs Fast Reroute RSVP Link Protection LDP LFA and Link Protection LSP Optimization Fate Sharing Junos OS Fate Sharing SRLG Extended Admin Groups Miscellaneous MPLS Features Forwarding Adjacencies Policy Control over LSP Selection LSP Metrics Automatic Bandwidth Container LSPs TTL Handling Explicit Null Configuration MPLS Pings

Duration 5 Days 30 CPD hours This course is intended for This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines