1699 Computing courses in Chigwell delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

Regular expressions training course description Regular expressions are an extremely powerful tool for manipulating text and data. They are now standard features in a wide range of languages and popular tools, including Python and MySQL. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them. What will you learn Use Regular Expressions. Troubleshoot Regular Expressions. Compare RE features among different versions. Explain how the regular expression engine works. Optimize REs. Match what you want, not what you don't want. Regular expressions training course details Who will benefit: Anyone looking to use regular expressions. Prerequisites: None. Duration 1 day Regular expressions training course contents Introduction to Regular Expressions Solving real problems, REs as a language, the filename analogy, language analogy, RE frame of mind, searching text files: egrep, egrep metacharacters, start and end of the line, character classes, matching any character with dot, alternation, ignoring differences in capitalization, word boundaries, optional items, other quantifiers: repetition, parentheses and backreferences, the great escape, expanding the foundation, linguistic diversification, the goal of a RE, more examples, RE nomenclature, Improving on the status quo. Extended introductory examples A short introduction to Perl, matching text with regular expressions, toward a more real-world example, side effects of a successful match, Intertwined regular expression, intermission, modifying text with regular expressions, example: form letter, example: prettifying a stock price, automated editing, a small mail utility, adding commas to a number with lookaround, text-to-HTML conversion, that doubled-word thing. Regular expression features and flavours The regex landscape, origins of REs, care and handling of REs, Integrated handling, procedural and object-oriented handling, search-and-replace example. strings character encodings and modes, strings as REs, character-encoding issues, unicode, regex modes and match modes, common metacharacters and features, character representations, character classes and class-like constructs, anchors and other 'zero-width assertions', comments and mode modifiers, grouping capturing conditionals and control. The mechanics of expression processing Two kinds of engines, new standards, regex engine types, from the department of redundancy department, testing the engine type, match basics, about the examples, rule 1: the match that begins earliest wins, engine pieces and parts, rule 2: the standard quantifiers are greedy, regex-directed versus text-directed, NFA engine: regex-directed, DFA engine: text-directed, first thoughts: NFA and DFA in comparison, backtracking, two important points on backtracking, saved states, backtracking and greediness, more about greediness and backtracking, problems of greediness, multi-character 'quotes', lazy quantifiers, greediness and laziness, laziness and backtracking, possessive quantifiers and atomic grouping, possessive quantifiers ?, +, *+, ++ and {m,n}+, the backtracking of lookaround, is alternation greedy? taking advantage of ordered alternation, NFA DFA and posix, the longest-leftmost', posix and the longest-leftmost rule, speed and efficiency. Practical regex techniques Continuation lines, matching an IP address, working with filenames, matching balanced sets of parentheses, watching out for unwanted matches, matching delimited text, knowing your data and making assumptions, stripping leading and trailing whitespace, matching and HTML tag, matching an HTML link, examining an HTTP URL, validating a hostname, plucking a hostname, plucking a URL, parsing CSV files. Crafting an efficient expression Efficiency vs. correctness, localizing greediness, global view of backtracking, more work for POSIX NFA, work required during a non-match, being more specific, alternation can be expensive, benchmarking, know what you re measuring, benchmarking with Python, common optimisations, the mechanics of regex application, pre-application optimizations, optimizations with the transmission, optimization of the regex itself, techniques for faster expressions, common sense techniques, expose literal text, expose anchors, lazy versus greedy: be specific, split into multiple REs, mimic initial-character discrimination, use atomic grouping and possessive quantifiers, lead the engine to a match, unrolling the loop, observations, using atomic grouping and possessive quantifiers, short unrolling examples, unrolling C comments, the free flowing regex, a helping hand to guide the match, a well-guided regex is a fast regex.

DevOps demystified training course description This course is an introduction to DevOps. The course emphasizes communication, collaboration , integration, and automation to improve the workflow between developers and IT operations professionals. Improved workflows lead to more opportunities to design software and services in a more agile fashion. This course is a basis for discovering the most important DevOps concepts and to understand the principles and methods behind this. The course will leave you with the inspiration to be the advocate of change. What will you learn Explain DevOps principles. Describe the relationship between Agile , Lean and IT Service Management ( ITSM). Describe methods for automation and technology factors. Describe considerations when changing. Describe challenges, risks and critical success factors. DevOps demystifieds training course details Who will benefit: Non-technical staff involved with DevOps. Prerequisites: None. Duration 1 day DevOps demystified training course contents Why DevOps? From a business perspective From an IT perspective Stereotypes of Dev and Ops: perception and reality What is DevOps? Introduction DevOps Goals DevOps Added value of DevOps Proven Results DevOps for businesses DevOps principles (The Three Ways) DevOps and other frameworks DevOps and Agile DevOps and Lean DevOps and IT Service Management DevOps culture Characteristics of a DevOps culture Organizational Considerations DevOps DevOps stakeholders DevOps roles DevOps teams DevOps organizational structures DevOps methods Continuous Integration Continuous delivery Continuous deployment Value stream mapping Kanban Theory of Constraints Improvement Kata Deming's quality circle ITSM processes DevOps and Automation Methods for DevOps automation Longevity and tools categories DevOps applications Transitioning to a DevOps culture Implementation Challenges, risks and critical success factors Measuring DevOps successes

Learn user experience fundamentals and master the design process with a user-centered approach. This UX Design Course has been designed to fully equip you with all the tools and methodologies you need to succeed as a UX designer.

Jamf 400, Jamf training course

Jamf Training, Jamf 300 course,

The Jamf 200 course offers a core understanding of Jamf Pro. It also provides enterprise-level knowledge of macOS and iOS platforms. Rely on our expert trainers to help you pass the Jamf 200 certification first time. Topics: Introduction to the Jamf Pro server. Building and managing content (.pkg, .mpkg, and .dmg packages) for deployment to macOS devices. Enrolling macOS and iOS devices using automated MDM enrollment. Setup and configuration of macOS and iOS devices. Configuring the user environment (Configuration Profiles, .plist). Security for macOS and iOS devices. Purchasing and distributing App Store apps using Apple Business Manager or Apple School Manager. Scripting overview (Bash). Initial setup and refreshing/reimaging macOS and iOS devices. Ownership and permissions (POSIX, ACE/ACL) on macOS devices. Prerequisites: Abundant hands-on experience with macOS and iOS. What’s Included: Four days (9am-5pm each day) of lab-style interaction. Proctored certification exam during the afternoon of the fourth day. All hardware and software required for the course. Printed course materials. Jamf Certified Tech badge on your Jamf Nation profile (upon successfully completing the exam with a passing score). Free £100 Apple technical training credit

Git and GitHub course description This course covers version control using Git but also using GUI frontends such as GitHub. The course starts with a tour of using GitHub but then quickly moves onto using git from the command line. All elements of git version control are covered including creation of repositories, adding and editing files, branches and merging, rewriting history and handling merge conflicts. Hands on sessions are used throughout the course. What will you learn Install git. Add and edit files in a repository. Create branches and perform merges. Handle merge conflicts. Git and GitHub course details Who will benefit: Anyone requiring version control. Prerequisites: None. Duration 1 day Git and GitHub course contents Introduction Version control for software, configuration management. Other uses. Version control systems. What is git? What is GitHub? Distributed version control. Comparison of git to other systems. GitHub Getting started, creating an account, account types, repositories, access control, bug tracking, feature requests. Alternatives to GitHub. Hands on Using GitHub. Installing git Linux install, Windows install, git config, levels, user.name, user.email. Hands on Installing and configuring git. Creating repositories git clone, github, git remote, git init. Hands on Creating a repository. Adding and editing files Staging and adding, git add, git commit, git push, git pull, git status, git log. Two stage process. File states: Working, staging, history, untracked. git mv, git rm, .gitignore, git diff, git difftool. Undoing changes. Hands on Adding and editing files in git. Branching and merging What is a branch, HEAD label, master branch, git branch, git checkout. Feature branches, bux fix branches, integration branches, production branches, fast forward merges, 3 way merges, git merge, git status, git log, tags. Hands on Making branches, merging. Rewriting history git reset, git rebase, advantages. Hands on Reset commits, rebase a branch. Merge conflicts What is a conflict, conflict resolution process, resolving merges, rebasing, git log, merge tools, configuring merge tools, avoiding conflicts. Hands on Merge resolution.

IPv6 demystified training course description IPv6 is the next generation Internet Protocol. This course looks at the benefits and features of the new protocol along with an assessment of the likely impact of the protocol and migration strategies. What will you learn Explain the benefits and disadvantages of IPv6 Recognise the impact of IPv6 on existing networks. Plan migration strategies for IPv6 Integrate IPv6 and IPv4 networks IPv6 demystified training course details Who will benefit: Sales staff, managers and other non technical staff. Prerequisites: None. Duration 1 day IPv6 demystified training course contents What's wrong with IPv4 IPv4 works, NAT, carrier grade NAT, addresses running out. Current state of IPv4 addressing. Why IPv6 Reasons for IPv6, what is IPv6? the origins of IPv6. IPv6 addressing IPv6 address allocation, address format, prefixes, address categories, scope zones, global unicast, link local. Plug and play. Migration techniques A migration plan, Dual stack, DNS, tunnelling, tunnel establishment, tunnel brokers, Tunnel types. IPv6 steps How IPv6 can affect the following: Firewalls, routers, switches!, DNS, Web services, Email. Current state of IPv6 IPv6 release 1996, 3G, World IPv6 day 2011, World IPv6 launch 2012.

BGP training course description A study of BGP for non engineers working in the Internet. The course starts with a review of the basics of routers and routing tables and then moves on to a simple overview of how BPG works with a focus on BGP metrics influencing the route traffic takes through the Internet. Hands on with routers follow the major sessions to reinforce the theory. Note these hands on sessions are more demonstrations by the trainer but some can be followed along and done by delegates (e.g. looking at Internet routing tables.) What will you learn Explain how routing tables influence Internet traffic. Describe how BGP works. Explain the methods BGP can use to influence Internet traffic. Use traceroute, peeringdb, route collectors and looking glasses to analyse traffic flows. Explain the difference between bi lateral and multilateral peering using a route server. BGP training course details Who will benefit: Non technical staff wishing to know more about BGP. Prerequisites: None. Duration 1 day BGP training course contents Networks, routers and routing tables What is a network, what is a router, routing tables, static routes, routing protocols. When an ISP uses static routes and when they use BGP. IP addresses, subnet masks, groups of IP addresses. IPv6. Hands on: Showing a full routing table. Seeing traceroute being used. Basic BGP What's BGP? BGP versus other routing protocols, ASs, AS numbers. RIPE database, peeringdb. Hands on: Finding AS numbers. Showing simple BGP configuration and routing tables in an EVENG example. How BGP works Simple walk through of BGP incremental updates and how routes change when links go down. Hands on: Showing packets and route changes when a link goes down/comes up. BGP path selection Transit, peering, routing policy and route filtering. Longest matching rule in routing tables, route selection order, Local preference, AS prepend, MEDs. Hands on: Seeing BGP influencing traffic. Looking at peering policies in RIPE and peeringdb. Route servers What are route servers? LINX route servers, route server policy control and communities, What are route collectors, Looking glasses. Hands on: Seeing the LINX route server details in peeringdb, using a looking glass.