Overview This is particularly important for PPP projects where long-term commitments are made now based on bankability, value for money and risk allocation. During the course, participants will gain knowledge and skills on the frameworks, tools, and methodologies necessary to build quantitative models for financial decision-making in order to improve the financial viability and bankability of PPP projects. Participants will master modelling frameworks on capital budgeting, risk measurement, regression analysis and Monte Carlo Simulation among others.
Overview Business modelling requires analysts to produce the quantitative models that top management uses to support their decision-making, but top management must also understand the strengths and weaknesses of the models if they are to use them effectively to support their decisions and robustly navigate the strategic negotiation landscape. This is particularly important for PPP projects where long-term commitments are made now based on bankability, value for money and risk allocation. During the course, participants will gain knowledge and skills on the frameworks, tools, and methodologies necessary to build quantitative models for financial decision-making in order to improve the financial viability and bankability of PPP projects. Participants will master modelling frameworks on capital budgeting, risk measurement, regression analysis and Monte Carlo Simulation among others.
This module focuses on developing leadership confidence through self-discovery, emphasising the importance of understanding one's unique leadership style and personal philosophy. Participants will explore their core identity as leaders and learn strategies to enhance their influence, credibility, and relationships within their organisation. Exploring the link between self-discovery and effective leadership, focusing on developing confidence to lead from within. Testimonial: “Without guidance, personal branding can quickly become an exercise in aspiration and competition; letting the carefully curated public personas of others dictate our own validity and definition of success. Clarity on who we truly are, what matters to us and therefore how we position ourselves in the world takes reflection and time. Rachael’s work in this area has inspired the nearly 100 delegates who have been part of our HR Leadership Academy over the past 8 years, and I have no doubt will continue to resonate with future cohorts.” MD, Nina Metson - Suffolk
Commission an original, traditional and quirky Portrait in oils, acrylics or digital sketches
Advanced Python training course description This course caters to network engineers aiming to enhance both their Python proficiency and network automation skills. Delving deeper into key areas such as netmiko, Nornir, and ncclient, we also focus on automating network testing and validation. Participants gain greater confidence working with Python functions, classes, objects, and error handling. The course additionally introduces more libraries like Scrapli, TTP, pyATS, Genie, pybatfish, and Suzieq, which cover parsing strategies, automation testing, validation, network analysis, observability, and telemetry. The curriculum also encompasses concurrency techniques. What will you learn Write Python modules and functions. Evaluate techniques to parse unstructured data. Use NETCONF filters. Handle Python errors effectively (try, assertâ¦). Use postman. Automate testing and validation of the network. Use scrapli, Genie, batfish and Suzieq. Advanced Python training course details Who will benefit: Network engineers. Prerequisites: Python for network engineers Duration 5 days Advanced Python training course contents Review CLI, NETCONF, RESTCONF, structured versus unstructured data, gNMI and when to use which. PEP 8. Naming conventions. Packages, modules, Classes and methods. The scrapli library. Netmiko versus scrapli. Hands on: scrapli, Dictionaries versus Regular Expressions. Modules and Functions Writing your own modules, containers versus packages, virtual environments. Best practices, calling functions, writing your own functions. Parameters, arguments. Named arguments, dictionaries as arguments. Builtins. Docstrings. Main. __name__, __main__ . Program arguments. Hands on: Getting interfaces, showing interface status using Netmiko and functions. Using dictionaries as arguments. Writing your own modules. Parsing strategies Turning unstructured data into structured data. textfsm, PyATS Genie parser, NAPALM getters, Template Text Parser. Hands on: Genie parser, TTP. Accessing structured data with lists and dictionaries. Classes, objects and Python Python classes in Genie, PyEZ and others . Hands on: studying network automation classes, objects, methods and attributes. Configuration management - more nornir, ncclient, requests Nornir tasks. Nornir results, Nornir functions, Nornir plugins. Nornir processors. YANG, YANG models, pyang. NETCONF hello. Capabilities. Schemas. Filters. Subtrees. XPATH. Exploring available YANG data models. NETCONF and network wide transactions. Asserting NETCONF capabilities. Configuration types. Locking configurations, commits. NETCONF data stores. Netconf-console. RESTCONF differences from NETCONF. URI construction. Postman. More XML and JSON. Git and configuration versions. Hands on: Nornir and Jinja2. Exploring available models, NETCONF filters. Using postman. Python error handling and debugging Context handlers, try, assert, logging, pdb, pytest, unit testing, chatgpt. Hands on: Writing code with each of the error handling methods, investigating what happens on an error. Use chatgpt to debug your code. Python Automation Testing Testing and validation. pyATS, Genie. Testbed file. Genie parse, genie learn, genie diff. Genie conf, Genie ops, Genie SDK, Genie harness. Xpresso. Hands on: Using Genie for state comparisons of the network. Network analysis Batfish, pybatfish, configuration analysis, analysing routing, analysing ACLs. Pandas. Pandas dataframe. Filtering and selecting values of interest. Hands on: Use Batfish to analyse network snapshots, find network adjacencies, flow path analysis. Network observability Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server. Namespaces and seeing devices, network state and Asserts. Time based analysis, snapshots and changes. Hands on: Suzieq: Gathering data from the network, analysing data from the network. Network state assertion. Telemetry gRPC, gNMI. CAP, GET, SET. Subscriptions. Model Driven telemetry. Hands on: Analysing telemetry data with Python. Concurrency asyncio, threads, processes. Nornir concurrency. Scrapli and netmiko concurrency. Hands on: Multiple SSH connections to devices at same time. Scarpli asyncio.
Gain certification as a safe people handling instructor and assessor with our comprehensive course. Equip yourself with the necessary skills and knowledge to effectively train and assess others in safe manual handling techniques.
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The NVQ Level 3 NVQ Diploma in Occupational Work Supervision is appropriate for individuals who supervise others in a construction area and are looking to become eligible for the Gold CSCS Card. The qualification modules will be discussed and agreed upon with each individual candidate to ensure that the qualification will be suited to your job role. Each candidate will be allocated a designated and qualified assessor to provide support throughout the qualification and provide information, advice and guidance to candidates in order that they can achieve the qualification. If you require further information or are looking to undertake this qualification, please contact us. CSCS Cards Candidates can undertake the CSCS test and obtain the red (Provisional) CSCS card on signing up for various qualifications. The red card can usually be obtained within 7 to 14 days and can be used to access the construction sites for a period of 12 months. On completion of the qualification candidates can upgrade or renew their CSCS Card to the full 5 year card.
The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales, or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms.