1404 Network courses delivered Live Online

LAN training course description A concise overview course covering Local Area Networks with particular emphasis on the use of Ethernet and Wireless LANS. As well as explaining buzzwords we cover how the technology works at a simple level. After defining LANs the course moves onto Ethernet and switching also covering VLANs. WiFi is then covered, with coverage of 802.11 standards and frequencies along with integrating WiFi with Ethernet. The course then covers routers and their role in connecting networks and the course finishes with a comparison of Ethernet vs WiFi and when to use them. What will you learn Describe how Ethernet works (in simple terms) and when to use Ethernet. Explain the difference between a switch and a router. Describe how WiFi works (in simple terms). Describe the role of Access points. Evaluate wireless technologies and when to use them. List the speeds of various LAN technologies. LAN training course details Who will benefit: Sales staff, managers and other non technical staff. Prerequisites: None. Duration 1 day LAN training course contents LANS What is a LAN? LAN standards, LAN choices, choosing the media, copper, UTP, cat5e, fibre, RF, bandwidth speeds, link aggregation, Full/half duplex. Ethernet What is Ethernet? 802.3, parts of Ethernet, Ethernet evolution, MAC addresses, frames, broadcasts. Ethernet switches What are switches, switches versus hubs, how switches work, ways to configure switches, Loops, STP. VLANs What are VLANs? Why have VLANs, impact of VLANs, Tagging (aka trunking), 802.1Q Wireless LANS Type of wireless LAN, RF frequencies, 2.4GHz, 5GHz, others, interference, standards, 802.11 and variants, CSMA/CA. Wireless LANS NICs, Access points, integration with Ethernet, multiple access points, mesh networks, WiFi security. Interconnecting LANs Routers, connecting networks, interconnecting VLANs, IP addressing, Layer 3 switches. Summary WiFi vs Ethernet.

IPv6 demystified training course description IPv6 is the next generation Internet Protocol. This course looks at the benefits and features of the new protocol along with an assessment of the likely impact of the protocol and migration strategies. What will you learn Explain the benefits and disadvantages of IPv6 Recognise the impact of IPv6 on existing networks. Plan migration strategies for IPv6 Integrate IPv6 and IPv4 networks IPv6 demystified training course details Who will benefit: Sales staff, managers and other non technical staff. Prerequisites: None. Duration 1 day IPv6 demystified training course contents What's wrong with IPv4 IPv4 works, NAT, carrier grade NAT, addresses running out. Current state of IPv4 addressing. Why IPv6 Reasons for IPv6, what is IPv6? the origins of IPv6. IPv6 addressing IPv6 address allocation, address format, prefixes, address categories, scope zones, global unicast, link local. Plug and play. Migration techniques A migration plan, Dual stack, DNS, tunnelling, tunnel establishment, tunnel brokers, Tunnel types. IPv6 steps How IPv6 can affect the following: Firewalls, routers, switches!, DNS, Web services, Email. Current state of IPv6 IPv6 release 1996, 3G, World IPv6 day 2011, World IPv6 launch 2012.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3. Overview In this course, you will expand your Python proficiencies. You will: Select an object-oriented programming approach for Python applications. Create object-oriented Python applications. Create a desktop application. Create a data-driven application. Create and secure web service-connected applications. Program Python for data science. Implement unit testing and exception handling. Package an application for distribution.   Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications. Selecting an Object-Oriented Programming Approach for Python Applications Topic A: Implement Object-Oriented Design Topic B: Leverage the Benefits of Object-Oriented Programming Creating Object-Oriented Python Applications Topic A: Create a Class Topic B: Use Built-in Methods Topic C: Implement the Factory Design Pattern Creating a Desktop Application Topic A: Design a Graphical User Interface (GUI) Topic B: Create Interactive Applications Creating Data-Driven Applications Topic A: Connect to Data Topic B: Store, Update, and Delete Data in a Database Creating and Securing a Web Service-Connected App Topic A: Select a Network Application Protocol Topic B: Create a RESTful Web Service Topic C: Create a Web Service Client Topic D: Secure Connected Applications Programming Python for Data Science Topic A: Clean Data with Python Topic B: Visualize Data with Python Topic C: Perform Linear Regression with Machine Learning Implementing Unit Testing and Exception Handling Topic A: Handle Exceptions Topic B: Write a Unit Test Topic C: Execute a Unit Test Packaging an Application for Distribution Topic A: Create and Install a Package Topic B: Generate Alternative Distribution Files Additional course details: Nexus Humans Advanced Programming Techniques with Python 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 Advanced Programming Techniques with Python 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 is an intermediate-level course for web developers with prior practical experience working with React. Overview Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore: React Native Essentials React Fundamentals: 7 steps of app development Building a React Native App / Case Study Core Components Core APIs Getting Started with React Native is a hands-on, intermediate level web development course geared for experienced web developers who need to build and design applications using React Native. Students will explore the core APIs and Components, applying these skills to the course case study project to create a React Native app in class. React Native: An Introduction What Is React Native, Exactly? What Does React Native Bring to the Table? Pros and Cons Introduction to React Native Prerequisites: How to Get React Native Baby Steps: A First App Getting Started with React Native Weather App Starting the project Expo Components Custom components React Fundamentals Breaking the app into components 7 step process Step 2: Build a static version of the app Step 3: Determine what should be stateful Step 4: Determine in which component each piece of state should live Step 5: Hardcode initial states Step 6: Add inverse data flow Updating timers Deleting timers Adding timing functionality Add start and stop functionality Methodology review Core Components, Part 1 What are components? Building an Instagram clone View StyleSheet Text TouchableOpacity Image ActivityIndicator FlatList Core Components, Part 2 TextInput ScrollView Modal Core APIs, Part 1 Building a messaging app Initializing the project The app Network connectivity indicator The message list Toolbar Geolocation Input Method Editor (IME) Core APIs, Part 2 The keyboard Day Four to Five or Time Permitting Navigation Navigation in React Native Contact List Starting the project Container and Presentational components Contacts Profile React Navigation Stack navigation Tab navigation Drawer navigation Sharing state between screens Deep Linking Testing Flow - Benefits of Using Flow Jest - Jest with React Native Snapshot Testing with Jest Building and publishing Building Building with Expo OS Android Handling Updates Additional course details: Nexus Humans Getting Started with React Native (TT4198) 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 Getting Started with React Native (TT4198) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

About this Virtual Instructor Led Training (VILT) Hydrogen will play an increasingly critical role in the future of energy system as it moves forward to supplement and potentially replace fossil fuels in the long run. Offshore wind offers a clean and sustainable renewable resource for green hydrogen production. However, it can also be volatile and presents inherent risks that need to be managed. Even though offshore production of hydrogen has yet to achieve a high state of maturity, many current projects are already dealing with the conditions and effects of offshore production of hydrogen and are grappling with the technological requirements and necessary gas transportation with grid integration. This 2 half-day Virtual Instructor Lead Training (VILT) course will examine the technological options for on-site production of hydrogen by electrolysis (onshore or offshore directly at the platform) as well as the transport of hydrogen (pipeline or ship). This VILT course will also explore the economic considerations and the outlook on future market opportunities. There will be exercises for the participants to work on over the two half-days. This course is delivered in partnership with Fraunhofer IEE. Training Objectives By the end of this VILT course, participants will be able to: Understand the technological attributes and options for green hydrogen production based on electricity from offshore wind. Explore the associated economic analysis for offshore wind hydrogen production, including CAPEX, OPEX, LCOE and LCOH Identify the critical infrastructure and technical configuration required for offshore green hydrogen including transportation networks and grid connectivity Learn from recent findings from current Research & Development projects concerning the differences between onshore and offshore hydrogen production. Target Audience This VILT course is intended: Renewable energy developers and operators Offshore oil & gas operators Energy transport and marine operators Energy policy makers and regulators IPPs and power utilities Training Methods The VILT course will be delivered online in 2 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 2 half-day sessions, 4 hours per session (8 hours in total). Trainer Trainer 1: Your expert course leader is Director of Energy Process Technology Division at the Fraunhofer Institute for Energy Economics and Energy System Technology, IEE. The research activities of the division link the areas of energy conversion processes and control engineering. The application fields covered are renewable energy technologies, energy storage systems and power to gas with a strong focus on green hydrogen. From 2006 - 2007, he worked as a research analyst of the German Advisory Council on Global Change, WBGU, Berlin. He has extensive training experience from Bachelor and Master courses at different universities as well as in the context of international training activities - recently on hydrogen and PtX for partners in the MENA region and South America. He holds a University degree (Diploma) in Physics, University of Karlsruhe (KIT). Trainer 2: Your expert course leader is Deputy Head of Energy Storage Department at Fraunhofer IEE. Prior to this, he was the director of the Grid Integration Department at SMA Solar Technology AG, one of the world's largest manufacturers of PV power converters. Before joining SMA, he 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 from 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 known as Fraunhofer IEE) in Kassel. In 2004, he started his career at RWE TSO with a main focus on wind power integration and congestion management. He 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. Trainer 3: Your expert course leader is Deputy Director of the Energy Process Technology division and Head of the Renewable Gases and Bio Energy Department at Fraunhofer IEE. His work is mainly focused on the integration of renewable gases and bioenergy systems into the energy supply structures. He has been working in this field since more than 20 years. He is a university lecturer in national and international master courses. He is member of the scientific advisory council of the European Biogas Association, member of the steering committee of the Association for Technology and Structures in Agriculture, member of the International Advisory Committee (ISAC) of the European Biomass Conference and member of the scientific committees of national bioenergy conferences. He studied mechanical engineering at the University of Darmstadt, Germany. He received his Doctoral degree on the topic of aerothermodynamics of gas turbine combustion chambers. He started his career in renewable energies in 2001, with the topic of biogas fired micro gas turbines. Trainer 4: Your expert course leader has an M. Sc. and she joined Fraunhofer IEE in 2018. In the Division of Energy Process Technology, she is currently working as a Research Associate on various projects related to techno-economic analysis of international PtX projects and advises KfW Development Bank on PtX projects in North Africa. Her focus is on the calculation of electricity, hydrogen and derivative production costs (LCOE, LCOH, LCOA, etc) based on various methods of dynamic investment costing. She also supervises the development of models that simulate different PtX plant configurations to analyze the influence of different parameters on the cost of the final product, and to find the configuration that gives the lowest production cost. She received her Bachelor's degree in Industrial Engineering at the HAWK in Göttingen and her Master's degree in renewable energy and energy efficiency at the University of Kassel. 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

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 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 5 Days 30 CPD hours This course is intended for System architects and system administrators Overview By the end of the course, you should be able to meet the following objectives: Introduce troubleshooting principles and procedures Use command-line interfaces, log files, and the vSphere Client to diagnose and resolve problems in the vSphere environment Explain the purpose of common vSphere log files Identify networking issues based on reported symptoms Validate and troubleshoot the reported networking issue Identify the root cause of networking issue Implement the appropriate resolution to recover from networking problems Analyze storage failure scenarios using a logical troubleshooting methodology identify the root cause of storage failure Apply the appropriate resolution to resolve storage failure problems Troubleshoot vSphere cluster failure scenarios Analyze possible vSphere cluster failure causes Diagnose common VMware vSphere High Availability problems and provide solutions Identify and validate VMware ESXiTM host and VMware vCenter problems Analyze failure scenarios of ESXi host and vCenter problems Select the correct resolution for the failure of ESXi host and vCenter problems Troubleshoot virtual machine problems, including migration problems, snapshot problems, and connection problems Troubleshoot performance problems with vSphere components This five-day training course provides you with the knowledge, skills, and abilities to achieve competence in troubleshooting the VMware vSphere© 8 environment. This course increases your skill level and competence in using the command-line interface, VMware vSphere© Client?, log files, and other tools to analyze and solve problems. Course Introduction Introductions and course logistics Course objectives Introduction to Troubleshooting Define the scope of troubleshooting Use a structured approach to solve configuration and operational problems Apply troubleshooting methodology to logically diagnose faults and improve troubleshooting efficiency Troubleshooting Tools Discuss the various methods to run commands Discuss the various ways to access ESXi Shell Use commands to view, configure, and manage your vSphere components Use the vSphere CLI Use ESXCLI commands from the vSphere CLI Use Data Center CLI commands Identify the best tool for command-line interface troubleshooting Identify important log files for troubleshooting vCenter Server and ESXi Describe the benefits and capabilities of VMware SkylineTM Explain how VMware Skyline works Describe VMware SkylineTM Health Describe VMware Skyline AdvisorTM Troubleshooting Virtual Networking Analyze and troubleshoot standard switch problems Analyze and troubleshoot virtual machine connectivity problems Analyze and troubleshoot management network problems Analyze and troubleshoot distributed switch problems Troubleshooting Storage Discuss the vSphere storage architecture Identify the possible causes of problems in the various types of datastores Analyze the common storage connectivity and configuration problems Discuss the possible storage problems causes Solve the storage connectivity problems, correct misconfigurations, and restore LUN visibility Review vSphere storage architecture and functionality necessary to troubleshoot storage problems Use ESXi and Linux commands to troubleshoot storage problems Analyze log file entries to identify the root cause of storage problems Investigate ESXi storage issues Troubleshoot VM snapshots Troubleshoot storage performance problems Review multipathing Identify the common causes of missing paths, including PDL and APD conditions Solve the missing path problems between hosts and storage devices Troubleshooting vSphere Clusters Identify and troubleshoot vSphere HA problems Analyze and solve vSphere vMotion problems Diagnose and troubleshoot common vSphere DRS problems Troubleshooting Virtual Machines Discuss virtual machine files and disk content IDs Identify, analyze, and solve virtual machine snapshot problems Troubleshoot virtual machine power-on problems Identify possible causes and troubleshoot virtual machine connection state problems Diagnose and recover from VMware Tools installation failures Troubleshooting vCenter Server and ESXi Analyze and solve vCenter Server service problems Diagnose and troubleshoot vCenter Server database problems Use vCenter Server Appliance shell and the Bash shell to identify and solve problems Identify and troubleshoot ESXi host problems

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to systems administrators and IT managers. Overview Skills gained in this training include:Determining the correct hardware and infrastructure for your clusterProper cluster configuration and deployment to integrate with the data centerConfiguring the FairScheduler to provide service-level agreements for multiple users of a clusterBest practices for preparing and maintaining Apache Hadoop in productionTroubleshooting, diagnosing, tuning, and solving Hadoop issues Cloudera University?s four-day administrator training course for Apache Hadoop provides participants with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster. The Case for Apache Hadoop Why Hadoop? Core Hadoop Components Fundamental Concepts HDFS HDFS Features Writing and Reading Files NameNode Memory Considerations Overview of HDFS Security Using the Namenode Web UI Using the Hadoop File Shell Getting Data into HDFS Ingesting Data from External Sources with Flume Ingesting Data from Relational Databases with Sqoop REST Interfaces Best Practices for Importing Data YARN & MapReduce What Is MapReduce? Basic MapReduce Concepts YARN Cluster Architecture Resource Allocation Failure Recovery Using the YARN Web UI MapReduce Version 1 Planning Your Hadoop Cluster General Planning Considerations Choosing the Right Hardware Network Considerations Configuring Nodes Planning for Cluster Management Hadoop Installation and Initial Configuration Deployment Types Installing Hadoop Specifying the Hadoop Configuration Performing Initial HDFS Configuration Performing Initial YARN and MapReduce Configuration Hadoop Logging Installing and Configuring Hive, Impala, and Pig Hive Impala Pig Hadoop Clients What is a Hadoop Client? Installing and Configuring Hadoop Clients Installing and Configuring Hue Hue Authentication and Authorization Cloudera Manager The Motivation for Cloudera Manager Cloudera Manager Features Express and Enterprise Versions Cloudera Manager Topology Installing Cloudera Manager Installing Hadoop Using Cloudera Manager Performing Basic Administration Tasks Using Cloudera Manager Advanced Cluster Configuration Advanced Configuration Parameters Configuring Hadoop Ports Explicitly Including and Excluding Hosts Configuring HDFS for Rack Awareness Configuring HDFS High Availability Hadoop Security Why Hadoop Security Is Important Hadoop?s Security System Concepts What Kerberos Is and How it Works Securing a Hadoop Cluster with Kerberos Managing and Scheduling Jobs Managing Running Jobs Scheduling Hadoop Jobs Configuring the FairScheduler Impala Query Scheduling Cluster Maintainence Checking HDFS Status Copying Data Between Clusters Adding and Removing Cluster Nodes Rebalancing the Cluster Cluster Upgrading Cluster Monitoring & Troubleshooting General System Monitoring Monitoring Hadoop Clusters Common Troubleshooting Hadoop Clusters Common Misconfigurations Additional course details: Nexus Humans Cloudera Administrator Training for Apache Hadoop 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 Cloudera Administrator Training for Apache Hadoop 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.