4224 Engineer courses

About this Virtual Instructor Led Training (VILT) This 4 half-day Virtual Instructor Led Training (VILT) course presents the principles and best practices of portfolio management in the upstream (E&P) oil and gas industry. The VILT course is equally valuable for small independents, large integrated international companies and national oil companies. The VILT course consists of presentations, case studies, illustrative practical exercises and syndicate discussions. Particular emphasis is given to pragmatic portfolio management approaches and solutions which can be implemented swiftly without recourse to major investments in planning and portfolio management software. The VILT course will draw on examples from your expert course leader's 35+ years' experience in the oil and gas industry as an explorationist, upstream vice-president and management consultant. The VILT course handout will comprise softcopy slides used in the presentation and a softcopy workbook for the exercises. Participants will gain proficiency in portfolio management techniques, understand how and why to undertake this activity and be able to apply key concepts directly in the business of their teams / divisions. The VILT course will be presented over 4 half-days, using Microsoft Teams or Zoom and a proprietary set of VILT tools. Participants will be asked to complete a pre course questionnaire (PCQ) addressing their objectives and experience, and attend a session to familiarise themselves with VILT tools before course commencement.     Training Objectives To present the tools, concepts and principles of portfolio management To define the quantitative metrics which are used to describe projects in a portfolio To understand the benefits of portfolio management at different stages of the upstream business: in strategy development, opportunity screening, business development, drilling prospects, conducting appraisal of discoveries and developing fields To put portfolio management in the organisational context by describing the role of the portfolio management team and examining how value assurance (quality control) is best conducted on portfolio data for projects and assets To demonstrate how portfolio management contributes to improved business performance By the end of the VILT course, participants will understand: Key concepts and principles of portfolio management How to design a simple portfolio database and describe complex projects in a small number of objective metrics How to segment the portfolio into meaningful units How to use portfolio data in making business choices and decisions at the strategic and tactical levels The extent to which it is meaningful and reasonable to make comparisons across different portfolio segments How the portfolio management team can support the wider business in decision-making Target Audience This VILT course is specially designed for exploration and development geoscientists, E&P economists and finance staff, and E&P managers. Both technical and non-technical staff will benefit from the concepts presented. Companies are encouraged to send participants from different functions and seniority levels to gain great benefits especially those which would like to implement the concepts presented in this VILT course. Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 4 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. The VILT course will be presented in an interactive workshop format that allows for discussion. Course Duration: 4 half-day sessions, 4 hours per session (16 hours in total). Trainer Your expert course leader draws on more than 35 years of experience managing, reviewing and directing projects in all aspects of the exploration business: from exploration business development (new ventures), through prospect maturation and drilling, to the appraisal of discoveries. He has more than 30 years' experience with Shell International, followed by 10 years consulting to NOCs in Asia Pacific, Africa and South America and independent oil companies in the United Kingdom, continental Europe and North America. Other than delivering industry training, he has worked on projects for oil & gas companies of all sizes, including independents, national oil companies and (super)-majors, private equity firms, hedge funds and investment banks, and leading management consulting firms. He is an alumnus of Cambridge University. He has M.A and Ph.D. degrees in geology and is a Fellow of the Geological Society of London as well as a respected speaker on management panels at international conferences. Professional Experience Management consultancy & executive education: Advice to investment banks, businesses and major consulting firms. Specialist expertise in upstream oil & gas, with in depth experience in exploration strategy, portfolio valuation and risk assessment. Leadership: Managed and led teams and departments ranging from 3 - 60 in size. Provided technical leadership to a cadre of 800 explorationists in Shell worldwide. Member of the 12-person VP team leading global exploration in Shell, a $3 bln p.a. business and recognised as the most effective and successful among its industry peers. Accountability & decision-making: Accountable for bottom-line results: in a range of successful exploration ventures with budgets ranging from $10's million to $100's million. Made, or contributed to, complex business decisions / investments, taking into account strategic, technical, commercial, organisational and political considerations. Corporate governance: Served as non-executive director on the Boards of the South Rub al Khali Company (oversight of gas exploration studies and drilling in Saudi Arabia) and SEAPOS B.V. (exploration deep-water drilling and facilities management). Technical & operations: Skilled in exploration opportunity evaluation, the technical de risking of prospects, portfolio analysis and managing the interface between exploration and well engineering activities. Unparalleled knowledge of the oil and gas basins of the world, and of different operating regimes and contractual structures, ranging from Alaska, Gulf of Mexico and Brazil, through to the Middle East, former Soviet Union, Far East and Australia. Safety: Following an unsatisfactory audit, became accountable for safety performance in Shell's exploration new ventures. Through personal advocacy and leadership of a small team, delivered pragmatic and effective HSE systems, tools and staff training / engagement and a dramatically improved safety record. R&D: Experience in the 3 key roles in R&D: scientific researcher, research manager, and 'customer' for R&D products. After re-defining Shell's exploration R&D strategy, led the re-structuring of the R&D organization, its interface with 'the business' and approaches to deployment and commercialization. Strategy: Accomplished at formulating competitive strategies in business, R&D and technology deployment, translating them into actionable tactics and results. Defined the exploration strategy of PDO (a Shell subsidiary in Oman) and latterly of Shell's global exploration programme. Professional education, behavioural/motivational coaching: Experienced in organisational re-design, change management, leadership education and talent development. Commercial skills: Personally negotiated drilling compensation claims, educational contracts and E&P contracts, with values of $5 million to $100+ million. 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

REST and RESTCONF training course description An introduction to REST and RESTCONF using Python. The course progresses from how to use them onto how they work and then looks at using them from within Python all the time on network devices. What will you learn Explain what REST and RESTCONF are. Use the REST API on network device. Use RESTCONF. REST and RESTCONF training course details Who will benefit: Network engineers. Prerequisites: Python for network engineers. Duration 1 day REST and RESTCONF training course contents Using REST Curl, Browser plugins, Postman, RESTClient, Python. Hands on Using the REST API on network devices. What is REST? What is REST? Architecture, APIs, RESTful APIs, APIs over HTTP/HTTPS, URIs, resources, HTTP methods, GET, POST, PUT, DELETE. CRUD. Comparison with other APIs. Hands on REST analysis with Wireshark. Rest conventions Passing parameters, return values, HTTP status, JSON. XML. Hands on Configuring REST on network devices, changing format of responses, POST requests, using parameters. Configuring network devices with REST Invoking multiple RPCs. Hands on Device configuration with REST. The request library RESTFUL APIs in Python, the request library, Installation, example to retrieve the interface configuration. Hands on Using the Python requests library on network devices. RESTCONF What is RESTCONF? YANG and NETCONF, relationship with REST, RESTCONF URIs, A RESTCONF example with ietf-interfaces, RESTCONF responses. PATCH. Hands on Using RESTCONF to update a network device configuration.

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Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Generation of High Voltage Introduction to Electrical Power System and Why Do We Need High Voltage 00:24:00 Types of High Voltage 00:16:00 Generation of High Voltage AC at Power Frequency 00:30:00 Generation of High Voltage High Frequency AC 00:14:00 Generation of High Voltage Impulse Part 1 00:37:00 Generation of High Voltage Impulse Part 2 00:13:00 Generation of High Voltage DC Part 1 00:42:00 Generation of High Voltage DC Part 2 00:44:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

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Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.