3814 Engineer courses in Cowdenbeath delivered Online

Online Asset Management Diploma course. Sit the IAM Diploma anywhere in the world

Level 5 QLS Endorsed Diploma | 150 CPD Points | +Gifts: QLS Certificate + PDF Certificate | 24/7 Learner Support

Our unique 5 day workshop prepares you for a first time pass of your CISSP exam. Covering each of the famous 8 CBK's, cram the theory before testing your knowledge during exam simulations. Led by a multi-award winning InfoSec consultant, this workshop delivers everything you need to pass,

Explore the complexities of seismic interpretation in carbonates through our dynamic classroom training course. Energyedge delivers cutting-edge instruction and valuable insights.

QSIG training course description A concise overview of QSIG, covering the development, current use and future of this private network signalling protocol. What will you learn Describe the use of QSIG. Describe the evolution of QSIG. Describe functionality of the QSIGProtocol Stack. Describe functionality and use of the main Supplementary Services and Additional Network Functions within QSIG. QSIG training course details Who will benefit: Network/Systems Engineers Operators/Planners or anyone working within the QSIG Arena. Prerequisites: Telecommunications Introduction Duration 1 day QSIG training course contents Introduction What is QSIG? User benefits, flexible interconnection, public ISDN synergy, feature transparency-end to end intelligence, innovation specialist features - heterogeneous environment. Evolution of QSIG Evolution of QSIG, ISDN PBX Networking, Specification forum (IPNS), QSIG standardisation. The ITU-T reference model extended for corporate networks. QSIG Protocol Q Protocol stack, QSIG basic call layer 3 - SubLayer 1, QSIG Generic Functional layer 3 Sub-Layer 2 (GF), QSIG protocols for supplementary services & ANF's- Layer 3, Sub-Layer 3, Layer 3 Message Overview. Supplementary Services and ANFs QSIG supplementary services standardisation methodology. QSIG Services and additional network features: Advice of charge, Call Completion, (CCBS, CCNR), Call Forwarding and diversion (CFB, CFNR, CFU, CD), Services (CINT, CI, CO, CT, CW, DDI) Services cont. (DND, DNDO), Identification Services - (CLIP, COLP, CLIR, CNIP, CONP, CNIR), Other QSIG services and additional network features (Mobile, Multi Subscriber Number (MSN), Operator Services, Recall (RE), Sub-Addressing (SUB)), User to user signalling, compliance with services. Conclusion - QSIG1 FAQ's, European Computer Manufacturers Association. The Future.

OOAD training course description A workshop course providing thorough practical knowledge of object oriented analysis and design methods. What will you learn Perform Systems Analysis with Object Oriented methods. Identify key classes and objects. Expand and refine OO problem domain models. Design Class hierarchies using inheritance and polymorphism. Design programs with Object Oriented methods. OOAD training course details Who will benefit: System analysts, designers, programmers and project managers. Prerequisites: It is desirable that delegates have experience of programming in C++/Java or some other OOP language. Duration 5 days OOAD training course contents What is OO? Classes, objects, messages, encapsulation, associations, inheritance, polymorphism, reusability. What is Systems Analysis and design? Data flow diagrams, structure diagrams. The OO approach. OOA The problem domain and object modelling. Identifying classes and objects. Generalisation and inheritance. Defining attributes and methods. OOD Refining the OOA results. Designing the User Interface. Designing the algorithms and data structures using objects. Designing the methods. OOP Prototyping. Implementing OOD with OOPs and OOPLs.

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About this Virtual Instructor Led Training (VILT) Preventive and Predictive maintenance are not new concepts. Both have been used across industry all over the world and when done properly, can yield impressive results (cost reductions of 20% or greater and a leap forward in equipment reliability and performance are very achievable). However, for every company using these concepts effectively, there are many others who are not. This 8 half-day Virtual Instructor Led Training (VILT) course has been derived from the Plant Performance Improvement Road Map developed by practitioners that guarantee the reliability of your operations. The VILT training focuses on how to improve profitability of any business by identifying the right maintenance strategy for any equipment. The aim of the VILT training is to help practitioners run programmes that will deliver real benefits as fast as possible with minimum zero wasted effort. The VILT training will also cover the core principles of Reliability Centred Maintenance, Total Productive Maintenance and Six Sigma and the increasingly important role of operations in achieving optimised asset performance. This is a certified course with the option of sitting for a short exam on the final day of the course to give participants the opportunity to gain a Certificate from petroEDGE and the Carcharodon Maintenance Academy. Training Objectives Master the critical skills by acquiring the following: An understanding of how maintenance can add profit The ability to develop improvement programmes that deliver maximum benefit in the shortest time A fundamental understanding of the principles of Preventive, Predictive and other maintenance types A practical understanding of the latest methods of solving problems at root cause level An appreciation of maintenance methodologies such as Reliability Centred Maintenance Strategies for ensuring your company gets value for money from your Contractors How to use the Maintenance Model of Excellence and Plant Performance Improvement Road Map Target Audience This VILT course has been designed for maintenance managers and engineers, reliability professionals, planners, project engineers, operations team members, and functional specialists. Training Methods The VILT course will be delivered online in 8 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 8 half-day sessions, 4 hours per session (32 hours in total). Trainer Your expert course leader is an award-winning consultant and trainer with 30 years' experience in maintenance and reliability improvement. He has worked across five continents, in a wide variety of environments from the world's largest oil refinery to a small drinks production line. He has 10 years of maintenance management experience in the process industry, so he brings a very practical approach to training. He moved into consulting with ABB Eutech as their global maintenance specialist where he led maintenance and reliability best practice panels, delivered a wide range of maintenance improvement projects and trained other consultants. He is a fully qualified CMRP professional, an approved SMRP* Proctor, authorised to conduct CMRP exams and a globally respected maintenance consultant and best practice trainer. He founded his consultancy and training business in 2002 to focus on maintenance and reliability improvement. As part of this, he developed a range of maintenance 'models of excellence' with inputs from authors, international lecturers and some of the world's leading consultants and operators. His work has been recognised as being at the leading edge of industry best practice, winning independent awards such as the UK Chemical Industries Association 'Excellence in Engineering' award. He remains close to the industry as a respected specialist helping operating companies to achieve changes in performance. This ongoing field work enables him to continue to refine and extend best practice and the learning from this is continually fed into his training. His unique experience of facilitating two major turnarounds when the Coronavirus escalated into lockdown have given him a unique insight into how events of this type can disrupt maintenance. Moreover, his involvement in developing management processes and leading a Coronavirus response on a major industrial asset means he can talk with direct experience about how to cope and innovate in this global pandemic. *SMRP refers to Society of Maintenance and Reliability Professionals. PetroEdge is not affiliated with SMRP 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

This course will show you why Hadoop is one of the best tools to work with big data. With the help of some real-world data sets, you will learn how to use Hadoop and its distributed technologies, such as Spark, Flink, Pig, and Flume, to store, analyze, and scale big data.

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.