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Linux fundamentals training course description An introduction to using the Linux operating system with a focus on the command line. Appropriate for all versions of Linux. The starting point for all Linux work, we concentrate on the technical aspects rather than issues such as using browsers. The course is heavily practical in nature. The course can be run on any Linux distribution you wish. What will you learn Describe Linux. Log in and use Linux commands to perform a variety of tasks from manipulating and printing files to looking at and killing processes. Create and edit files with vi. Recognise the role of the administrator. Write simple shell scripts. Customise the user environment. Linux fundamentals training course details Who will benefit: Anybody who needs to use a Linux system. Prerequisites: None. Duration 3 days Linux fundamentals training course contents What is Linux? Operating systems, Linux flavours, Linux distributions, open source software. Getting started Logging in, changing passwords, logging out. Linux basics Command structure. The Linux manuals, basic commands (who, date, tty, uname, echo, banner...) Filesystem commands Home directories, manipulating files and directories, Filesystem layout, Pathnames, hard and symbolic links. Viewing files. The Linux editors ed, vi, shell escapes, .exrc Extracting data from files grep, find, cut, sort and paste... Permissions Theory, chmod, chown, newgrp.. Processes ps, kill, background processes, at, exec, priorities. Managing Linux log files. The Shell Metacharacters, piping and redirection. Basic shell scripting What are shell scripts? Simple scripts, control structures. Variables. Arguments. Customising your environment Environmental variables, stty, .profile and other startup files More shell features Bash and other shells, the history facility, command line editing, aliases, job control, miscellaneous features. Introduction to administration The root user, su. Managing users and groups Archiving files Backups, tar, cpio, dd, gzip. Linux and hardware Main hardware components, Linux device drivers. Connecting to a network IP configuration, ifconfig, ping, netstat, traceroute, dig.

Dive into the world of project management with our comprehensive course! Master the fundamentals, explore advanced tools such as Jira, Microsoft Teams, and Trello, and gain real-world insights. From Agile methodologies to effective communication strategies, this course equips you with the skills to excel as a confident and successful project manager.

Welcome to this dual-phase course. In the first segment, we delve into neural networks and deep learning. In the second, ascend to mastering Generative Adversarial Networks (GANs). No programming experience required. Begin with the fundamentals and progress to an advanced level.

Learn how to create an automated trading bot using Python with this comprehensive course. Master Python basics, understand trading fundamentals, build and integrate the bot with a broker API, and run it effectively. Learning Outcomes: Gain proficiency in Python programming for trading purposes. Understand the fundamental concepts of trading and market dynamics. Build a structured trading bot using Python and Github version control. Integrate the bot with a broker API for real-time trading functionality. Successfully run and manage the automated trading bot for efficient execution. Why buy this Making Automated Trading Bot Using Python? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Making Automated Trading Bot Using Python there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Making Automated Trading Bot Using Python course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Making Automated Trading Bot Using Python does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Making Automated Trading Bot Using Python was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Making Automated Trading Bot Using Python is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction About the course structure 00:05:00 Why working is important? 00:04:00 The free and perfect tools 00:07:00 Our editor: Atom 00:04:00 Version control: Github 00:07:00 Python download (Mac) 00:05:00 Python download (Windows) 00:02:00 Section 02: Python Basics for Trading Introduction 00:03:00 Python Libraries 00:05:00 Iterators: for 00:08:00 Iterators: while 00:08:00 Conditionals: if & else 00:10:00 Logic gates: and & or 00:09:00 Error handling: try & except 00:09:00 Functions and calls to libraries 00:13:00 Objects and classes (1) 00:10:00 Objects and classes (2) 00:07:00 Debugging the code 00:12:00 Closing and wrap up 00:01:00 Section 03: Trading Basics Introduction 00:03:00 Fundamental vs Technical Analysis 00:04:00 Stocks vs CFDs 00:05:00 Long and Short positions 00:04:00 Takeprofit and Stoploss 00:03:00 Setting a real Stoploss 00:08:00 Limit and Market orders 00:10:00 Don't forget the spread 00:04:00 Stock data visualisation: candles 00:08:00 Technical Indicators: about 00:05:00 Exponential Moving Average 00:08:00 EMA use and interpretation 00:06:00 Relative Strength Index 00:07:00 Stochastic Oscillator 00:09:00 Closing and wrap up 00:01:00 Section 04: Bot Code General Structure Introduction 00:02:00 Overview 00:08:00 The Entry Strategy 00:10:00 About Tradingview 00:12:00 When to enter (1) 00:08:00 When to enter (2) 00:08:00 Open and hold a position 00:12:00 Closing a position 00:08:00 Review (1) 00:06:00 Review (2) 00:13:00 Closing 00:02:00 Section 05: Github Basics Introduction 00:04:00 Download and install Github 00:01:00 Create a repo 00:10:00 Working with branches 00:13:00 Section 06: Building Your Bot Introduction 00:05:00 Create the first bot file 00:07:00 Building the bot scheme 00:08:00 Complete your code scheme (1) 00:11:00 Complete your code scheme (2) 00:11:00 Complete your code scheme (3) 00:18:00 A logger to remember (1) 00:14:00 A logger to remember (2) 00:14:00 Organising your code 00:07:00 Main function: run bot 00:23:00 Link the bot and the library 00:08:00 Traderlib control functions (1) 00:12:00 Traderlib control functions (2) 00:13:00 Check if tradable function 00:06:00 Set stoploss function 00:10:00 Set takeprofit function 00:04:00 Load historical data function 00:01:00 Get open positions function 00:04:00 Submit and cancel order functions 00:04:00 Check positions function 00:09:00 The Tulipy libraries 00:07:00 Importing all the libraries 00:03:00 First filter: get general trend 00:19:00 Second filter: get instant trend 00:14:00 Third filter: RSI 00:08:00 Fourth filter: Stochastic Oscillator 00:14:00 Enter position (1) 00:13:00 Enter position (2) 00:11:00 Enter position (3) 00:15:00 Enter position (4) 00:08:00 Last check before opening 00:13:00 Exit position and get out 00:10:00 Linking everything (1) 00:12:00 Linking everything (2) 00:12:00 Linking everything (3) 00:15:00 Fixing a mistake: going Short 00:05:00 Handling all your variables 00:18:00 Closing and wrap up 00:01:00 Run function scheme clarification and rebuild 00:13:00 Section 07: Integrating the Broker API Introduction 00:03:00 The Alpaca Python API Wrapper 00:07:00 Initialising the REST API 00:09:00 Running the program (crash!) 00:06:00 Integration with check account (1) 00:08:00 Integration with check account (2) 00:05:00 Clean open orders function 00:10:00 Importing the trading library 00:04:00 Running the main 00:05:00 Check position function 00:09:00 Check if asset exists function 00:08:00 Fetching barset data (theory) 00:07:00 Fetching barset data (practice) 00:12:00 Updating the code for the Alpaca API V2 (explanation) 00:03:00 Updating the code for the Alpaca API V2 (implementation) 00:08:00 Organizing data with Pandas 00:06:00 Get general trend function (1) 00:08:00 Reframing the timeframe with Pandas 00:23:00 Get general trend function (2) 00:13:00 Get instant trend function 00:08:00 Get RSI function 00:06:00 Get Stochastic function 00:10:00 Get current price function 00:05:00 Finishing get shares amount 00:09:00 Opening a position (1) 00:12:00 Opening a position (2) 00:09:00 Check the open position 00:07:00 Cancelling the order (1) 00:20:00 Cancelling the order (2) 00:08:00 Making sure we cancelled 00:03:00 Get average entry price function 00:10:00 Fixing bugs when getting price 00:18:00 Check Stochastic crossing 00:02:00 Holding an open position 00:11:00 Submitting the exit order 00:08:00 Closing position and out (1) 00:08:00 Closing position and out (2) 00:10:00 Closing and wrap up 00:01:00 Section 08: Running the Trading Bot Introduction 00:03:00 Filtering asset by price and volume 00:07:00 Get the bot ready to trade 00:04:00 Running the Trading Bot with AAPL 00:09:00 A real open position 00:08:00 Debugging and bug fixing 00:12:00 Fixing one (last) bug 00:02:00 Running the bot with TSLA 00:10:00 Discussing EMA implementations 00:12:00 Closing and wrap up 00:02:00

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

Teaching Assistant Level 1, 2 & 3 Diploma – CPD Accredited Become a skilled and confident Teaching Assistant with this CPD-accredited course! Learn essential classroom support techniques, child development strategies, SEN support, and subject-specific teaching skills. Progress from beginner to advanced levels and boost your career in education. Study online at your own pace! 🚀 Enroll now & make a difference in children's education!

Advanced Kibana training course description This training course is aimed at users who already have some experience with Kibana, who are looking to further their knowledge. What will you learn Lens Timelion Maps Custom Visualisations with Vega Canvas Filters and Controls Drilldown and Dashboards KQSL and ElasticQueries Scripted and RunTime Fields Alerts and Alarms Advanced Kibana training course details Who will benefit: Users who already have some experience with Kibana, who are looking to further their knowledge. Prerequisites: None Duration 1 day Advanced Kibana training course contents Topics Lens Visualisation types (tables,bars,charts) Category breakdown Adding multiple metrics Using formulas in metrics Labels Adding reference layer Limitations Visualise Library Timeseries, Metrics Different types of aggregations Maps GeoMapping Heat Maps Using ES index as data source Visualisation, tool tips Custom Visualisations with Vega Introduction to vega scripting Canvas Widgets and Texts Elasticsearch SQL Canvas Expressions Filters and Controls Dropdown filters Ad-hoc filters Searchbar filters Drilldown Dashboards Linking one dashboard to another KQSL and ElasticQueries Bool Query AND/OR Phrase Part match vs keyword search Wildcard search Scripted and RunTime Fields Creating ad-hoc calculated fields using scripts Performance issues Alerts and Alarms Query Based Formatting output Connector types(email,index,teams etc)

PRINCE2® Practitioner : In-House Training Projects fail for a variety of reasons including poor planning, lack of defined quality criteria, poor understanding of the business drivers, inadequate control, and lack of senior management involvement in other words, lack of a structured best practice approach to project delivery. PRINCE2® (6th Edition is the current version) is a structured, process-based approach for project management providing a methodology which can be easily tailored and scaled to suit all types of projects. It is the de facto standard for project management in the UK Government and is also used extensively in more than 150 countries worldwide with in excess of 20,000 organizations already benefitting from its powerful approach. It can be used easily in combination with PMI®'s PMBOK® Guide to provide a robust project methodology, or to augment an existing PMBOK®-based methodology with additional rigor around areas such as Quality, Organization, and Benefits Realization. The goals of this course are to take participants to the next level of understanding and application of the PRINCE2® methodology and to prepare them to sit the Practitioner exam. Using APMG provided sample exam papers and additional project case studies, participants will learn how to apply what they learned during the Foundation course and how to approach the OTE Practitioner exam, which is aimed at testing their ability to apply PRINCE2® in an actual project environment simulated via a case study provided as part of the exam. What you will Learn You'll learn how to: Tailor and apply the principles, themes, process structure, techniques, and management products of PRINCE2® within a work environment, via carefully selected case studies Define the PRINCE2® 6th Edition method at the Practitioner level Prepare for and take the Practitioner exam Getting Started Introductions Course structure Course goals and objectives Tailoring PRINCE2® Tailoring PRINCE2® Adopting PRINCE2® Tailoring PRINCE2® to suit different projects Adopting PRINCE2® in an organizational environment Controlled Start Recap management products Study business case and risk Study activities and responsibilities in: Starting up a project Initiating a project Controlled Progress Study management products and risk Study activities and responsibilities in: Getting work done Monitoring and reporting Issues and escalation Controlled Close Study Activities and Responsibilities in Closing a Project Activities and roles Roles and Responsibilities Principles Exercise Product-basedPlanning Producing a product breakdown structure (PBS) Producing a product flow diagram (PFD) Linking product breakdown structures and product flow diagrams to product descriptions

Coaching, Workplace coaching, Floor walking coaching, Organisational coaching,

This course offers everything you need to become a React developer, from basic to advanced concepts. The course delves deep into custom hooks, Tailwind CSS, React Router, Redux, Firebase, and React Skeleton. You will learn to build real-world apps with React (eCommerce, Movie Informer, Todolist Manager, Blog, and Word Counter).