9817 Courses

Every Wednesday at 16:50 – 17:30 (Newmarket Academy) or Every Saturday at 12:35 – 13:15 (Exning Community Church Hall) The piano is one of the most popular instruments among all western instruments. At M&L Music School we equip our piano players with all the necessary skills to play different styles of music using good technique. From beginners to grade 8 level (grade 5 is a level that would be enough to gain an A in a GCSE solo instrumental assessment). Piano Group Lessons are an encouraging and challenging environment that can be highly motivational. Learning and playing the piano in a group allows students to practice and perform in front of other people while building confidence. Our piano classes consist of learning pieces using notated music and by ear; scales; sight-reading; aural and technique exercises. We can prepare students to take Trinity guildhall grades, ABRSM, and Rock School piano or keyboard exams as well as performances. Book first lesson here: https://mandlschoolofperformingarts.com/book-first-lesson/

I am a 48 year old driving instructor, living in Bristol. I have taught all kinds of people to drive…all ages and all abilities, from almost every corner of the Bristol area, and I own the independent driving school, Rick's Driving School Bristol.

Explore ChatGPT, a cutting-edge world of AI content creation, with our comprehensive course. This meticulously curated program unravels the technology behind ChatGPT to practical applications in machine learning, social media, data analysis, and image generation. This course unveils new facets of AI to navigate this evolving landscape with prowess.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for network administrators, operators, and engineers responsible for managing the normal day-to-day operation and administration of a BIG-IP application delivery network. This course presents the prerequisite knowledge for many other of F5's BIG-IP instructor-led training courses. Overview Getting started with the BIG-IP system Traffic processing with BIG-IP Local Traffic Manager (LTM) Using the TMSH (TMOS Shell) command line interface Using NATs and SNATs Monitoring application health and managing object status Modifying traffic behavior with profiles, including SSL offload and re-encryption Modifying traffic behavior with persistence, including source address affinity and cookie persistence Troubleshooting the BIG-IP system, including logging (local, high-speed, and legacy remote logging), and using tcpdump User roles and administrative partitions vCMP concepts Customizing application delivery with iRules This course gives network administrators, network operators, and network engineers a functional understanding of the BIG-IP system as it is commonly deployed in an application delivery network. The course introduces students to the BIG-IP system, its configuration objects, how it processes traffic, and how typical administrative and operational activities are performed. The course includes lecture, hands-on labs, interactive demonstrations, and discussions. Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Configuring the Management Interface Activating the Software License Provisioning Modules and Resources Importing a Device Certificate Specifying BIG-IP Platform Properties Configuring the Network Configuring Network Time Protocol (NTP) Servers Configuring Domain Name System (DNS) Settings Configuring High Availability Options Archiving the BIG-IP Configuration Leveraging F5 Support Resources and Tools Traffic Processing Building Blocks Identifying BIG-IP Traffic Processing Objects Configuring Virtual Servers and Pools Load Balancing Traffic Viewing Module Statistics and Logs Using the Traffic Management Shell (TMSH) Understanding the TMSH Hierarchical Structure Navigating the TMSH Hierarchy Managing BIG-IP Configuration State and Files BIG-IP System Configuration State Loading and Saving the System Configuration Shutting Down and Restarting the BIG-IP System Saving and Replicating Configuration Data (UCS and SCF) Using NATs and SNATs Address Translation on the BIG-IP System Mapping IP Addresses with NATs Solving Routing Issues with SNATs Configuring SNAT Auto Map on a Virtual Server Monitoring for and Mitigating Port Exhaustion Monitoring Application Health Introducing Monitors Types of Monitors Monitor Interval and Timeout Settings Configuring Monitors Assigning Monitors to Resources Managing Pool, Pool Member, and Node Status Using the Network Map Modifying Traffic Behavior with Profiles Introducing Profiles Understanding Profile Types and Dependencies Configuring and Assigning Profiles Introducing SSL Offload and SSL Re-Encryption Managing Object State Modifying Traffic Behavior with Persistence Understanding the Need for Persistence Introducing Source Address Affinity Persistence Managing Object State Administering the BIG-IP System Configuring Logging Legacy Remote Logging Introducing High Speed Logging (HSL) High-Speed Logging Filters HSL Configuration Objects Configuring High Speed Logging Using TCPDUMP on the BIG-IP System Leveraging the BIG-IP iHealth System Viewing BIG-IP System Statistics Defining User Roles and Administrative Partitions Leveraging vCMP Configuring High Availability Introducing Device Service Clustering (DSC) Preparing to Deploy a DSC Configuration Configuring DSC Communication Settings Establishing Device Trust Establishing a Sync-Failover Device Group Synchronizing Configuration Data Exploring Traffic Group Behavior Understanding Failover Managers and Triggers Achieving Stateful Failover with Mirroring

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2 Days 12 CPD hours This course is intended for People working in an organization aiming to improve performance, especially in response to digital transformation or disruption. Any roles involved in the creation and delivery of products or services: Leadership and CXO, especially CIO, CTO, CPO, and CVO Transformation and evolution leads and change agents Value stream architects, managers, engineers Scrum Masters, agile and DevOps coaches and facilitators Portfolio, product and project managers, and owners Business analysts Architects, developers, and engineers Release and environment managers IT Ops, service and support desk workers Customer experience and success professionals Overview After completing this course, students will be able to: Describe the origins of value stream management and key concepts such as flow, value, and delivery Describe what value stream management is, why it's needed and the business benefits of its practice Describe how lean, agile, DevOps, and ITSM principles contribute to value stream management Identify and describe value streams, where they start and end, and how they interconnect Identify value stream roles and responsibilities Express value streams visually using mapping techniques, define current and target states and hypothesis backlog Write value stream flow and realization optimization hypotheses and experiments Apply metrics such as touch/processing time, wait/idle time, and cycle time to value streams Understand flow metrics and how to access the data to support data-driven conversations and decisions Examine value realization metrics and aligning to business outcomes, and how to sense and respond to them (outcomes versus outputs) Architect a DevOps toolchain alongside a value stream and data connection points Design a continuous inspection and adaptation approach for organizational evolution The Value Stream Management Foundation course from Value Stream Management Consortium, and offered in partnership with DevOps Institute, is an introductory course taking learners through a value stream management implementation journey. It considers the human, process, and technology aspects of this way of working and explores how optimizing value streams for flow and realization positively impacts organizational performance. History and Evolution of Value Stream Management and its Application Value stream management?s origins Definitions of value stream management Flow Lean and systems thinking and practices Agile, DevOps and other frameworks Research and analysis Identifying Value Streams What is a value stream? Identifying value streams Choosing a value stream Digital value streams Value stream thinking Mapping Value Streams Types of maps Value stream mapping The fuzzy front end Artifacts 10 steps to value stream mapping Mapping and management VSM investment case Limitations of value stream mapping Connecting DevOps Toolchains CICD and the DevOps toolchain Value stream management processes Value stream management platforms DevOps tool categories Building an end-to-end DevOps toolchain Common data model and tools integrations Value Stream Metrics The duality of VSM Downtime in technology Lean, DORA and Flow metrics Definition of Done Value metrics Benefits hypotheses Value streams as profit centers KPIs and OKRs Inspecting the Value Stream 3 Pillars of Empiricism Organizational performance Visibility When to inspect Data and discovery Insights and trends Organizing as Value Streams Value stream alignment Team types and topologies Project to product Hierarchy to autonomy Target Operating Model Value stream people Value stream roles Value stream funding Evolving Value Streams Why now? Transitions VSM capability matrix VSM culture iceberg Learning Making local discoveries global improvements Managing value stream interdependencies

Duration 2 Days 12 CPD hours This course is intended for The course is designed for individuals who want to gain in-depth knowledge and practice in the discipline of Business Analysis (Business Analysts, Requirements Engineers, Product manager, Product Owner, Chief Product Owner, Service Manager, Service Owner, Project manager, Consultants) Overview Students should be able to demonstrate knowledge and understanding and application of Business Analysis principles and techniques. Key areas are: The breath of the role of a Business Analyst The processes and techniques of strategy analysis Investigation of an organization's business systems Techniques used within stakeholder analysis and the need for analyzing perspectives Conceptual modelling and business activity models Business improvements through gap analysis The Business case within the business change lifecycle The Business Analyst role analyzes, understands and manages the requirements in a customer-supplier relationship and ensures that the right products are delivered.The course provides in-depth knowledge and practice in Business Analysis Course Introduction Let?s Get to Know Each Other Course Overview Course Learning Objectives Course Structure Course Agenda Introduction to Business Analysis Practice Exam Details Business Analysis Certification Scheme Rationale for Business Analysis The role of the BA throughout the stages of the Business change lifecycle The scope of the BA role within the context of the range of analysis activities Three areas of competencies Understanding the Strategic Context Techniques in practice: MOST Resource audit PESTLE Porter's Five Forces SWOT analysis CSF, KPI and Performance target Balanced Business Score Card Understanding the Current Situation Identification of stakeholder categories Identification of relevant investigation techniques The rationale for taking a holistic view Rich pictures, Mind Maps and Fishbone diagrams Stakeholder Analysis and Management Power/interest and level of interest Appropriate stakeholder management strategy Stakeholder perspectives and CATWOE technique Analysing and Modelling Business Activities Conceptual models of a business situation Five types of high level activity Planning activities Enabling activities Doing activities Monitoring and control activities Three types of business events The consensus business activity model Identifying Potential Solutions Different categories of business rules Gap analysis (through conceptual business activity model and as-is business situation) Components of a new business model Building the Business Case Rationale for the development of a business case Contents of a business case Identification of tangible/intangible costs and benefits, risks and impacts Rationale for the financial case and appraisal techniques Business case review in the business change lifecycle Additional course details: Nexus Humans Business Analysis - Practice 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 Business Analysis - Practice 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.

A question of trust. Leadership implies followership. And that means trust. Because who's going to follow a leader they don't trust? This programme takes a values-driven approach to leadership. It gets current and aspiring leaders to hold up the mirror to themselves and to see their reflections as leaders of people. It asks them whether what they see justifies their view of themselves as leaders. It helps them understand just what it takes to be an effective leader. And it does so in a highly practical, constructive manner. It helps the course participants to truly understand the core skills of effective leadership. It focuses on the difference between leadership and management, defining what high performing teams do and how they do it. It helps people to see their teams from different perspectives, allowing them to adapt their styles to maximise team outputs. And it explores concepts such as emotional intelligence, authentic leadership and the RAIV approach (relationships-achievement-independence-vocation) to help explore underlying values and use them to drive effective leadership. Because what worth do our values have unless we put them into practice? The course will help you:• Appreciate the key skills a leader needs to be effective• Understand what the organisation expects of you as a leader• Recognise your leadership style and the impact it has on others• Consider your role models - who inspires you?• See leadership from the 'followers' perspective - how do you like to be led?• Discover what holds you back - limiting beliefs• Examine your core values -do they support your ambition?• Explore the concept of Emotional Intelligence - how do we manage ourselves?• Discover how to lead through change• Explore the concept of 'Authentic Leadership' - consider how it can work for you• Practice some of the skills essential to motivating and influencing for success• Use the RAIV approach to generating enthusiasm and commitment• Plan how best to 'walk the leadership talk' - in your role, in your organisation Above all, this course will help you put theory into practice, values into actions, in a mature, considered, effective way. Day 1 1 Welcome and introduction Participants are welcomed to the programme and invited to share their personal objectives and people challenges Participants given an action plan template to complete throughout the workshop Participants required to bring an inspirational quote to share with the group 2 What is leadership? The concept of 'leadership' The role of a leader Skills assessment for all participants# Leadership v Management Assess your team effectiveness 3 Your leadership style Leadership questionnaire You and your role models Push v Pull styles of leadership Empowerment v Control Team goals and role profiling Day 2 1 You, the leader Your core values Your communication style Situational leadership The Emotional Bank Account Buy Me Today 2 Are you Emotionally Intelligent? (EI) What is emotional intelligence? Self-assessment exercise Manage your emotions Nine strategies for promoting EI 3 Leading through change Identify the major changes affecting you / your team Types of change The roles of resistance How safe are you to talk to? Forcefield Analysis Day 3 1 Authentic Leadership (AL) What is AL? Managing perceptions is managing their truth A leadership challenge 2 Motivating and influencing for success What motivates you? Motivational theory Leading by example Influencing skills required Influencing styles The influence challenge! 3 Creating enthusiasm and commitment The RAIV approach (relationships-achievement-independence-vocation) Building self-worth What drives your team? Your leadership legacy Your commitment to leadership

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Level 4 Construction Site Management Have you ever thought of gaining training in construction site management? If so, then you can join our Construction Site Management Course to learn about this field. The construction site management course offers comprehensive training in overseeing construction projects. Also, the construction site management course teaches project planning, scheduling, budgeting, and resource management. This construction site management course includes safety regulations, risk assessment, and conflict resolution. Moreover, the construction site management course provides practical exercises and case studies to enhance understanding of project management software and communication techniques. Enrol in our construction site management course to efficiently manage construction sites, ensuring projects are completed on time, within budget, and to the highest safety standards. Learning outcome of construction site management course This construction site management course explain about: A brief introduction to construction management. This construction site management course describes equipment procurement plans, construction project management, and equipment planning. How to manage purchasing and procurement management is part of this construction site management course. The construction site management course explains material management and proper project planning. The management of construction project contracts, HRM, team building, and management training are also involved in this construction site management course. Our construction site management course teaches health and safety in the construction environment. Through the construction site management course, you will learn how to work at height, provide first aid, and manage violence at the workplace. Main Course: Construction Site Management Special Offers of this Construction Site Management Course This Construction Site Management Course includes a FREE PDF Certificate. Lifetime access to this Construction Site Management Course Instant access to this Construction Site Management Course Get FREE Tutor Support to this Construction Site Management Course Level 4 Construction Site Management A thorough education in managing construction projects is provided by the construction site management course. Project scheduling, budgeting, resource management, and project planning are also included in the construction site management course. Conflict resolution, risk assessment, and safety standards are all covered in this building site management course. In addition, the course on construction site management offers hands-on activities and case studies to improve comprehension of project management software and communication strategies. Who is this course for? Level 4 Construction Site Management Anyone can enrol in this course. Requirements Level 4 Construction Site Management To enrol in this Construction Site Management Course, students must fulfil the following requirements. To join in our Construction Site Management Course, you must have a strong command of the English language. To successfully complete our Construction Site Management Course, you must be vivacious and self driven. To complete our Construction Site Management Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Construction Site Management Course. Career path Level 4 Construction Site Management You will be able to advance your career in the relevant field with this course.