7476 Systems courses

Duration 5 Days 30 CPD hours This course is intended for IT professionals who have attended Red Hat System Administration I and want the skills to be full-time enterprise Linux administrators and/or earn RHCSA certifications This course focuses on the key tasks needed to become a full time Linux administrator and goes deeper into enterprise Linux administration including file systems and partitioning, logical volumes, SELinux, firewalling, and troubleshooting. Automate installation with Kickstart Automate the installation of Red Hat Enterprise Linux systems with Kickstart Use regular expressions with grep Write regular expressions that, when partnered with grep, will allow you to quickly isolate or locate content within text files. Create and Edit text files with vim Introduce the vim text editor, with which you can open, edit, and save text files. Schedule future Linux tasks Schedule tasks to automatically execute in the future. Manage priority of Linux processes Influence the relative priorities at which Linux processes run. Control access to files with access control lists (ACL) Manage file security using POSIX access control lists. Manage SELinux security Manage the Security Enhanced Linux (SELinux) behavior of a system to keep it secure in case of a network service compromise. Connect to network-defined users and groups Configure systems to use central identity management services. Add disks, partitions, and file systems to a Linux system Manage simple partitions and file systems. Manage logical volume management (LVM) storage Manage logical volumes from the command line. Access networked attached storage with network file system (NFS) Access (secure) NFS shares. Access networked storage with SMB Use autofs and the command line to mount and unmount SMB file systems. Control and troubleshoot the Red Hat Enterprise Linux boot process Limit network communication with firewall, Configure a basic firewall. Comprehensive review Practice and demonstrate knowledge and skills learned in this course.

STGO Abnormal Loads

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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.

Delegates will develop knowledge of the requirements for the design, installation and commissioning of Fire Detection and Fire Alarm systems within domestic properties in compliance with the requirements of BS 5839-6 and other codes of practice.

Delegates will develop knowledge of the requirements for the design, installation and commissioning of Fire Detection and Fire Alarm systems within domestic properties in compliance with the requirements of BS 5839-6 and other codes of practice.

Learn to assess, design, and monitor solar PV power plants with EnergyEdge's comprehensive training. Master PVsyst software for bankable system simulations.

Learn how to deploy, manage, and secure Oracle WebLogic in an enterprise environment.

Duration 2 Days 12 CPD hours This course is intended for The audience for this course is anyone who wants to acquire foundation level knowledge on data centre infrastructure. This course is ideally suited for data centre new hires, internal data centre support staff, IT support staff who work in the data centre, helpdesk staff, vendors/suppliers who install/maintain data centre equipment, building maintenance staff including data centre cleaners and other supporting functions, and fresh graduates. This course is also well suited for individuals working in data centre business support functions such as sales/pre-sales, HR, Finance and business administration. Overview The DCFC course will prepare participants for entry into the exciting and high-growth data centre industry. It will ensure that participants acquire the required basic knowledge to take on a wide variety of jobs in the data centre industry. It will also provide the required knowledge and skill to further their training into specialised areas on data centre design/build, operations/governance or standards/compliance. The Data Centre Foundation Certificate (DCFC©) is a 2-day course designed to deliver foundation knowledge about data centre facilities infrastructure. It provides participants with global overview and knowledge on data centres which will be of advantage to the participants who are looking at joining the ranks of professionals working in the data centre, ICT, infrastructure or the mechanical and electrical (M&E) design industries. It will also form a solid foundation for participants who wish to pursue his/her studies either academically or to further his/her industry specialisation with professional certification courses on data centre design/build, operations/governance and/or standards/compliance. With the tremendous growth of data and the data centres to support it, the demand for data centre professionals will grow in tandem. Introduction to Data Centres History of data centres Definition of different type data centres Data Centre Standards List of standards Rating definitions Data Centre Facilities Areas Listing of all areas and their functions Topology Designs Definition of Ratings Components of the Power Infrastructure Utility power Transformers Generators Fuel systems ATS UPS systems Batteries Electric panels Cabling/busbar systems Power rails/strips Lights Lights Emergency lights Cooling Infrastructure Chillers DX Systems Evaporators CRAC/CRAU/HVAC Raised floor Non-raised floor Containment ICT/Network Infrastructure Equipment racks Network cabling (fibre, copper) Cable trays and pathways TIA-606 labelling Data Centre Security Perimeter security Physical protection CCTV Access control Security management Fire Suppression Detection systems Suppression systems Prevention systems Fire extinguishers Fire Safety Monitoring and reporting DCIM EMS/BMS

This module aims to develop knowledge and understanding of customs procedures associated with international trade. The module includes trade agreements, tariffs and taxes, immigration, intellectual property rights, clearance procedures, transport regulations, sanitary and Phyto-sanitary measures, customs valuation, preference systems and anti-dumping measures.

Learners will develop knowledge from the FD&FA foundation courses (C01 modules 1 and 2) and/or industry experience with specific regard to more complex system design considerations.