2218 Courses in Cardiff delivered Live Online

Overview OBJECTIVES Develop practical skills enabling effective communication at the time of an incident Familiarize students with both techniques & technologies involved in crisis communication Provide a health check for your personal & organizational readiness Provide the confidence to know that your response strategies are appropriate and effective Build relevant knowledge through exploring relevant case studies and practical exercises Develop flexible creative and well-motivated teams Upcoming Events Online (USD 1950) Online Streaming Live (Flexible Dates) At Venue (USD 4500) Dubai 20 Feb - 24 Feb Istanbul 27 Feb - 3 March London 20 March - 24 March For more dates and Venue, Please email sales@gbacorporate.co.uk

The course covers investigation and risk assessment of asbestos-contaminated soils and sites, including waste classification and land remediation. It will cover the current HSE and EA legislation and guidance, assessing risk to health from asbestos in soils and how to assess the land, analysis types and interpretation, and remedial actions.

Duration 3.5 Days 21 CPD hours This course is intended for This course is aimed at students new to the language who may or may not have experience with other programming languages. Overview Learn how Python works and what it's good for. Understand Python's place in the world of programming languages Learn to work with and manipulate strings in Python. Learn to perform math operations with Python. Learn to work with Python sequences: lists, arrays, dictionaries, and sets. Learn to collect user input and output results. Learn flow control processing in Python. Learn to write to and read from files using Python. Learn to write functions in Python. Learn to handle exceptions in Python. Learn to work with dates and times in Python. In this Python training course by Webucator, Inc, students learn to program in Python. Python Basics Running Python Hello, World! Literals Python Comments Data Types Variables Writing a Python Module print() Function Named Arguments Collecting User Input Getting Help Functions and Modules Defining Functions Variable Scope Global Variables Function Parameters Returning Values Importing Modules Math Arithmetic Operators Modulus and Floor Division Assignment Operators Built-in Math Functions The math Module The random Module Seeding Python Strings Quotation Marks and Special Characters String Indexing Slicing Strings Concatenation and Repetition Common String Methods String Formatting Built-in String Functions Iterables: Sequences, Dictionaries, and Sets Definitions Sequences Unpacking Sequences Dictionaries The len() Function Sets *args and **kwargs Flow Control Conditional Statements The is and is not Operators Python's Ternary Operator Loops in Python The enumerate() Function Generators List Comprehensions File Processing Opening Files The os and os.path Modules Exception Handling Wildcard except Clauses Getting Information on Exceptions The else Clause The finally Clause Using Exceptions for Flow Control Exception Hierarchy Dates and Times Understanding Time The time Module The datetime Module Running Python Scripts from the Command Line The sys Module sys.argv

CCHRC has been specially designed to provide training for anyone who has functional responsibility for controlling health risks on a construction site, such as site supervisors and site managers.

P400 - Asbestos Surveying and Analysis is a one day foundation level course, which provides candidates with the fundamental knowledge to start a career in the asbestos surveying and analysis professions, and as a progression route to the asbestos Proficiency qualifications. It gives candidates an introductory level of knowledge on the health risks of asbestos fibres, and how to manage asbestos-containing materials in their work. Candidates for this course are not expected to have prior knowledge and experience but having an awareness of the contents of both HSG248 Asbestos: The analysts' guide (July 2021) and HSG264 Asbestos: the survey guide January 2010), would be advantageous.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is as follows: Cisco Unified Communications system channel partners and resellers who are responsible for deployment and application engineering for Cisco Unified Contact Center Express customers. System and technical support engineers. Day 1 and Day 2 support personnel. Customers deploying and maintaining Cisco Unified CCX Overview Upon completing this course, the learner will be able to meet these overall objectives: Review Cisco Unified CCX environment components Create prompt recording tools Create a helpdesk script Apply common sense principles for scripting and system management, such as: Prompt, document, and grammar management Using the default script Scripting for proper call termination and ending a script Abandon rates Exception handling Check Agent Availability before and after entering queue Using Java Methods for Holiday and Time of Day routing Setup access and use an external database Define and use skills Script for conditional routing Script for basic callback scenarios Setup and use enterprise data and session management Script for queuing and scheduled callback scenarios Building on the knowledge base and scripting experience learned in the UCCXD class, the student will explore advanced techniques in scripting and overall Cisco Unified CCX functionality. During this five day class the students will use advanced scripting to implement features that extend the functionality of Cisco Unified CCX using many of the tools that are already available in the premium version of the product. Students should expect to spend time using the script editor and other tools to create developer tools and enhanced scripts to provide for a more functional and user-friendly customer experience. Activities include creating prompt recording tools, applying common sense scripting principles, creating simple and complex ACD routing scripts, holiday routing, external database access, various callback scenarios such as non-queuing, queuing, and scheduled callbacks, defining and using enterprise data, passing data from one script to another using session management, and much more. Additionally, since this class focuses on complex scripting concepts, it requires the student to learn more about fundamental scripting requirements such as data manipulation and formatting, using variables and array variables, and using Java programming methods. Course Introduction Learner Prerequisite Skills and Knowledge Course Goal Course Objectives Course Flow General Administration Lab Diagram Please Introduce Yourself Lesson 1: Cisco Unified CCX Overview Components of the Cisco Unified CCX Environment Gateways Routers Cisco Unified Communications Manager Cisco Unified CCX Script Editor Cisco Finesse Cisco Unified Intelligence Center Cisco Unified CCX Agent External Servers Cisco Unified CCX System Cluster Components Engine Database Server Call Flow Terms The Call Flow The Debug Process Reactive Non-Reactive Lesson 2: Prompt Recording Utilities Prompt Recorder Emergency Message Recorder Lesson 3: Basic ACD Routing Review Script Steps used in a Simple ACD Routing Script Resource Group Routing Defining the Contact Service Queue Create a Simple ACD routing script Lesson 4: Common Scripting Concepts Prompt Management Using the Default Script Terminating a Call and Ending a Script Abandon Rates Exception Handling Script Interruptions Check Agent Availability before and after entering queue Using Java Methods for Holiday and Time of Day routing Lesson 5: Accessing an External Database Database architecture and supported databases Setting up the Database Subsystem Using Database script steps Lesson 6: Skills Based Routing Appling skills to agents Defining the Contact Service Queue Specifying the CSQ in the Script Lesson 7: Advanced ACD Routing Overflow Routing When to Overflow How to get the Data Needed for Making Decisions Describe Methods of Overflowing Lesson 8: Basic ACD Callback Options Setup the Email Subsystem Script for Email Notification Script for Leaving a Recorded Message Script for Callback when Queue Times have Decreased Lesson 9: Enterprise Data and Session Management Define Enterprise Data in Cisco Finesse Define a Call Variable Layout in Cisco Finesse Define ECC Variables in the script editor Set Enterprise Data in the script Define Session Management Setup Session Management Use Session Management to Pass Variable Information Between Scripts Lesson 10: Advanced ACD Callback Options Leave Queued Message with an Option for Callback Scheduled Callback

This course provides the theory, practical knowledge and skills required for use of microscopes and fibre counting to WHO rules, air sampling and four-stage clearance procedures. The course is based around 'HSG248 Asbestos: The Analysts Guide for Sampling, Analysis and Clearance Procedures'.

We have expanded our asbestos awareness courses to specifically cover the awareness of asbestos in soils, made-ground and construction and demolition materials. Essential for geotechnical engineers, plant operators, civil engineering contractors and ground workers.

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