3044 Software Development courses

This course follows a hands-on, project-based approach to learning the Arduino platform catered to all levels of experience, including some projects such as building an Arduino car, an Arduino phone, a Universal Arduino Remote, an Arduino Online Weather Station, an Arduino game projects using light, sound, and joysticks, and more with no prior knowledge.

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

How to be a Great Executive Sponsor: Virtual In-House Training This three-hour course provides key tips and techniques for becoming an actively engaged, and impactful, Executive Sponsor of projects and programs. It will explain not just what your role is, but the very specific actions you can, and must, take to increase your project's probability of success. This three-hour course provides key tips and techniques for becoming an actively engaged, and impactful, Executive Sponsor of projects and programs. It will explain not just what your role is, but the very specific actions you can, and must, take to increase your project's probability of success. And, it will highlight the key personality and other traits that are found in successful Sponsors. Regardless if you're sponsoring an Agile software development project, a construction megaproject, or any other type of project in between, this course will help get you 'hit the ground running' and being an 'impact player' on day one. Various activities and discussions will acquaint you with this important role and what you need to do to become a great executive sponsor. What you Will Learn At the end of this program, you will be able to: Define project success so everyone is 'singing from the same sheet of music' Immediately apply the ten key attributes of a great sponsor on your project Recognize great sponsorship and determine if you're the right fit for the role Practice Sponsorship over the course of the project life cycle by engaging in very specific actions and activities Be a better investment manager by analyzing the behaviors of successful activist investors Foundation Concepts The quantifiable benefits of being an actively engaged Sponsor Sponsor defined Clarence Kelly Johnson and the SR-71 Blackbird: An example of the power of Sponsorship Defining Project Success Project success: More than meeting the triple constraints Benefits management: The Sponsor's focus The Investment - Life-cycle vs. the Project Life-cycle The three questions Sponsors need to ask to define project success 10 Key Attributes of a Great Sponsor 10 Key Attributes of a Great Sponsor The Makings of a Great Sponsor The most important skills and competencies of an executive sponsor What great Sponsors do and when Four Things a Great Sponsor Can Learn from an Activist Investor The story of Outerwall, Inc. and Glen Welling of Engaged Capital, LLC Sponsors and Activist Investors Sponsorship of the 2nd Avenue Subway in Manhattan: A classic textbook example

Learn about the Raspberry Pi, build a DIY Google Home Clone and RetroPie Gaming System, work with GPIO pins, and much more.

Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now With a single payment you will gain access to Agile including 10 Career development courses, original hardcopy certificate, transcript and a student ID card which will allow you to get discounts on things like music, food, travel and clothes etc. Don't be left behind in the world of Project Management. Learn to embrace Agile principles and software and lead the pack. This certificated Agile course will tutor you in the expert use of Agile practises and learn how to harness the collective power of your team. If you are confused by the use or terminology of Kanban and Waterfall, this course delivers all of the training that you'll need to incorporate their methodologies into your working routines. By adopting these proven Project Management philosophies, you will rapidly see a change in your department's productivity and work ethics. Take this course anywhere and at any time. Don't let your lifestyle limit your learning or your potential. Agile will provide you with the CPD certificate that you'll need to succeed. Gain experience online and interact with experts. This can prove to be the perfect way to get noticed by a prospective employer and stand out from the crowd. Agile has been rated and reviewed highly by our learners and professionals alike. We have a passion for teaching, and it shows. All of our courses have interactive online modules that allow studying to take place where and when you want it to. The only thing you need to take Agile is Wi-Fi and a screen. You'll never be late for class again. Experienced tutors and mentors will be there for you whenever you need them, and solve all your queries through email and chat boxes. What other courses are included with this Agile? Level 3- Project Management Microsoft Teams Applied Business Analysis Diploma Working from Home Essentials Mental Health and Working from Home Online Meeting Management Effective Communication Skills Time Management Leadership & Management Diploma Emotional Intelligence and Human Behaviour Course Curriculum of Agile Course Introduction Agile Overview Understanding Lean Software Development Understanding Kanban Introduction to Scrum Understanding XP Software Development Other Agile Models How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? There is no experience or previous qualifications required for enrolment on this Agile. It is available to all students of all academic backgrounds. Note: This is not a professional course. This course only covers theoretical knowledge about the topic. Requirements Our Agile is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having this CPD certificate will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Agile Project Management) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost

Duration 1 Days 6 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision makers who are interested in unlocking new business opportunities and augmenting existing business processes using generative AI. It's also a great starting point for any business professionals who want to investigate generative AI solutions for their own individual tasks and workflows. This course is also designed to assist students in preparing for the CertNexus GenAIBIZ (Exam GAZ-110) credential. Overview In this course, you will identify ways in which generative AI can bring significant value to the organization. You will: Describe the fundamentals of AI and generative AI. Generate text using AI. Generate code using AI. Generate images and video using AI. Generate audio using AI. Identify the challenges of generative AI. Implement organizational strategies for generative AI. This course is designed to demystify generative AI for business professionals, as well as to trace its power to actionable, real-world business goals. It will give you the essential knowledge of generative AI you'll need to elevate the organization in these exciting times. GenAIBIZÿoffers business professionals with the ability to describe the fundamentals of AI and generative AI; generate text, code, images, video, and audio using generative AI; identify the challenges of generative AI; and implement organizational strategies for generative AI. Exam voucher is included.This course may earn you a Credly badge. Lesson 1: AI Fundamentals Topic A: AI Concepts Topic B: Generative AI Concepts Lesson 2: Generating Text Using AI Topic A: Identify Text Generation Concepts Topic B: Solve Business Problems Using Text Generation Lesson 3: Generating Code Using AI Topic A: Identify Code Generation Concepts Topic B: Solve Business Problems Using Code Generation Lesson 4: Generating Images and Video Using AI Topic A: Identify Image and Video Generation Concepts Topic B: Solve Business Problems Using Image and Video Generation Lesson 5: Generating Audio Using AI Topic A: Identify Audio Generation Concepts Topic B: Solve Business Problems Using Audio Generation Lesson 6: Identifying Challenges of Generative AI Topic A: Identify Shortcomings of Generative AI Topic B: Identify Ethical Risks of Generative AI Topic C: Identify Business Concerns of Generative AI Lesson 7: Implementing Business Strategies for Generative AI Topic A: Apply Best Practices for Generative AI in the Organization Topic B: Evaluate the Results of Generative AI Projects

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Duration 4 Days 24 CPD hours This course is intended for Students in this course are interested in designing and implementing DevOps processes or in passing the Microsoft Azure DevOps Solutions certification exam. This course provides the knowledge and skills to design and implement DevOps processes and practices. Students will learn how to plan for DevOps, use source control, scale Git for an enterprise, consolidate artifacts, design a dependency management strategy, manage secrets, implement continuous integration, implement a container build strategy, design a release strategy, set up a release management workflow, implement a deployment pattern, and optimize feedback mechanisms Prerequisites Successful learners will have prior knowledge and understanding of: Cloud computing concepts, including an understanding of PaaS, SaaS, and IaaS implementations. Both Azure administration and Azure development with proven expertise in at least one of these areas. Version control, Agile software development, and core software development principles. It would be helpful to have experience in an organization that delivers software. AZ-104T00 - Microsoft Azure Administrator AZ-204T00: Developing Solutions for Microsoft Azure 1 - Introduction to DevOps What is DevOps? Explore the DevOps journey Identify transformation teams Explore shared goals and define timelines 2 - Choose the right project Explore greenfield and brownfield projects Decide when to use greenfield and brownfield projects Decide when to use systems of record versus systems of engagement Identify groups to minimize initial resistance Identify project metrics and key performance indicators (KPIs) 3 - Describe team structures Explore agile development practices Explore principles of agile development Define organization structure for agile practices Explore ideal DevOps team members Enable in-team and cross-team collaboration Select tools and processes for agile practices 4 - Choose the DevOps tools What is Azure DevOps? What is GitHub? Explore an authorization and access strategy Migrate or integrate existing work management tools Migrate or integrate existing test management tools Design a license management strategy 5 - Plan Agile with GitHub Projects and Azure Boards Link GitHub to Azure Boards Configure GitHub Projects Manage work with GitHub Project boards Customize Project views Collaborate using team discussions Agile Plan and Portfolio Management with Azure Boards 6 - Introduction to source control Explore DevOps foundational practices What is source control? Explore benefits of source control Explore best practices for source control 7 - Describe types of source control systems Understand centralized source control Understand distributed source control Explore Git and Team Foundation Version Control Examine and choose Git Understand objections to using Git Describe working with Git locally 8 - Work with Azure Repos and GitHub Migrate from TFVC to Git Use GIT-TFS Develop online with GitHub Codespaces 9 - Structure your Git Repo Explore monorepo versus multiple repos Implement a change log 10 - Manage Git branches and workflows Explore branch workflow types Explore feature branch workflow Explore Git branch model for continuous delivery Explore GitHub flow Explore fork workflow Version Control with Git in Azure Repos 11 - Collaborate with pull requests in Azure Repos Collaborate with pull requests Examine GitHub mobile for pull request approvals 12 - Identify technical debt Examine code quality Examine complexity and quality metrics Measure and manage technical debt Integrate other code quality tools Plan effective code reviews 13 - Explore Git hooks Implement Git hooks 14 - Plan foster inner source Explore foster inner source Implement the fork workflow Describe inner source with forks 15 - Manage Git repositories Work with large repositories Purge repository data Manage releases with GitHub Repos Automate release notes with GitHub 16 - Explore Azure Pipelines Explore the concept of pipelines in DevOps Describe Azure Pipelines Understand Azure Pipelines key terms 17 - Manage Azure Pipeline agents and pools Choose between Microsoft-hosted versus self-hosted agents Explore job types Explore predefined agent pool Understand typical situations for agent pools Communicate with Azure Pipelines Communicate to deploy to target servers Examine other considerations Describe security of agent pools Configure agent pools and understanding pipeline styles 18 - Describe pipelines and concurrency Understand parallel jobs Estimate parallel jobs Describe Azure Pipelines and open-source projects Explore Azure Pipelines and Visual Designer Describe Azure Pipelines and YAML 19 - Explore continuous integration Learn the four pillars of continuous integration Explore benefits of continuous integration Describe build properties Enable Continuous Integration with Azure Pipelines 20 - Implement a pipeline strategy Configure agent demands Implement multi-agent builds Explore source control types supported by Azure Pipelines 21 - Integrate with Azure Pipelines Describe the anatomy of a pipeline Understand the pipeline structure Detail templates Explore YAML resources Use multiple repositories in your pipeline 22 - Introduction to GitHub Actions What are Actions? Explore Actions flow Understand workflows Describe standard workflow syntax elements Explore events Explore jobs Explore runners Examine release and test an action 23 - Learn continuous integration with GitHub Actions Describe continuous integration with actions Examine environment variables Share artifacts between jobs Examine Workflow badges Describe best practices for creating actions Mark releases with Git tags Create encrypted secrets Use secrets in a workflow Implement GitHub Actions for CI/CD 24 - Design a container build strategy Examine structure of containers Work with Docker containers Understand Dockerfile core concepts Examine multi-stage dockerfiles Examine considerations for multiple stage builds Explore Azure container-related services Deploy Docker containers to Azure App Service web apps 25 - Introduction to continuous delivery Explore traditional IT development cycle What is continuous delivery? Move to continuous delivery Understand releases and deployments Understand release process versus release 26 - Create a release pipeline Describe Azure DevOps release pipeline capabilities Explore release pipelines Explore artifact sources Choose the appropriate artifact source Examine considerations for deployment to stages Explore build and release tasks Explore custom build and release tasks Explore release jobs Configure Pipelines as Code with YAML 27 - Explore release recommendations Understand the delivery cadence and three types of triggers Explore release approvals Explore release gates Use release gates to protect quality Control Deployments using Release Gates 28 - Provision and test environments Provision and configure target environments Configure automated integration and functional test automation Understand Shift-left Set up and run availability tests Explore Azure Load Testing Set up and run functional tests 29 - Manage and modularize tasks and templates Examine task groups Explore variables in release pipelines Understand variable groups 30 - Automate inspection of health Automate inspection of health Explore events and notifications Explore service hooks Configure Azure DevOps notifications Configure GitHub notifications Explore how to measure quality of your release process Examine release notes and documentation Examine considerations for choosing release management tools Explore common release management tools 31 - Introduction to deployment patterns Explore microservices architecture Examine classical deployment patterns Understand modern deployment patterns 32 - Implement blue-green deployment and feature toggles What is blue-green deployment? Explore deployment slots Describe feature toggle maintenance 33 - Implement canary releases and dark launching Explore canary releases Examine Traffic Manager Understand dark launching 34 - Implement A/B testing and progressive exposure deployment What is A/B testing? Explore CI-CD with deployment rings 35 - Integrate with identity management systems Integrate GitHub with single sign-on (SSO) Explore service principals Explore Managed Identity 36 - Manage application configuration data Rethink application configuration data Explore separation of concerns Understand external configuration store patterns Examine Key-value pairs Examine App configuration feature management Integrate Azure Key Vault with Azure Pipelines Manage secrets, tokens and certificates Examine DevOps inner and outer loop Integrate Azure Key Vault with Azure DevOps Enable Dynamic Configuration and Feature Flags 37 - Explore infrastructure as code and configuration management Explore environment deployment Examine environment configuration Understand imperative versus declarative configuration Understand idempotent configuration 38 - Create Azure resources using Azure Resource Manager templates Why use Azure Resource Manager templates? Explore template components Manage dependencies Modularize templates Manage secrets in templates Deployments using Azure Bicep templates 39 - Create Azure resources by using Azure CLI What is Azure CLI? Work with Azure CLI 40 - Explore Azure Automation with DevOps Create automation accounts What is a runbook? Understand automation shared resources Explore runbook gallery Examine webhooks Explore source control integration Explore PowerShell workflows Create a workflow Examine checkpoint and parallel processing 41 - Implement Desired State Configuration (DSC) Understand configuration drift Explore Desired State Configuration (DSC) Explore Azure Automation State configuration (DSC) Examine DSC configuration file Explore hybrid management Implement DSC and Linux Automation on Azure 42 - Implement Bicep What is Bicep? Install Bicep Understand Bicep file structure and syntax 43 - Introduction to Secure DevOps Describe SQL injection attack Understand DevSecOps Explore Secure DevOps Pipeline Explore key validation points Explore continuous security validation Understand threat modeling 44 - Implement open-source software Explore how software is built What is open-source software Explore corporate concerns with open-source software components Explore common open-source licenses Examine license implications and ratings 45 - Software Composition Analysis Inspect and validate code bases for compliance Explore software composition analysis (SCA) Integrate Mend with Azure Pipelines Implement GitHub Dependabot alerts and security updates Integrate software composition analysis checks into pipelines Examine tools for assess package security and license rate Interpret alerts from scanner tools Implement security and compliance in an Azure Pipeline 46 - Static analyzers Explore SonarCloud Explore CodeQL in GitHub Manage technical debt with SonarCloud and Azure DevOps 47 - OWASP and Dynamic Analyzers Plan Implement OWASP Secure Coding Practices Explore OWASP ZAP penetration test Explore OWASP ZAP results and bugs 48 - Security Monitoring and Governance Implement pipeline security Explore Microsoft Defender for Cloud Examine Microsoft Defender for Cloud usage scenarios Explore Azure Policy Understand policies Explore initiatives Explore resource locks Explore Azure Blueprints Understand Microsoft Defender for Identity 49 - Explore package dependencies What is dependency management? Describe elements of a dependency management strategy Identify dependencies Understand source and package componentization Decompose your system Scan your codebase for dependencies 50 - Understand package management Explore packages Understand package feeds Explore package feed managers Explore common public package sources Explore self-hosted and SaaS based package sources Consume packages Publish packages Package management with Azure Artifacts 51 - Migrate consolidating and secure artifacts Identify existing artifact repositories Migrate and integrating artifact repositories Secure access to package feeds Examine roles Examine permissions Examine authentication 52 - Implement a versioning strategy Understand versioning of artifacts Explore semantic versioning Examine release views Promote packages Explore best practices for versioning 53 - Introduction to GitHub Packages Publish packages Install a package Delete and restore a package Explore package access control and visibility 54 - Implement tools to track usage and flow Understand the inner loop Explore Azure Monitor and Log Analytics Examine Kusto Query Language (KQL) Explore Application Insights Implement Application Insights Monitor application performance with Application Insights 55 - Develop monitor and status dashboards Explore Azure Dashboards Examine view designer in Azure Monitor Explore Azure Monitor workbooks Explore Power BI Build your own custom application 56 - Share knowledge within teams Share acquired knowledge within development teams Integrate with Azure Boards Share team knowledge using Azure Project Wiki 57 - Design processes to automate application analytics Explore rapid responses and augmented search Integrate telemetry Examine monitoring tools and technologies 58 - Manage alerts, blameless retrospectives and a just culture Examine when get a notification Explore how to fix it Explore smart detection notifications Improve performance Understand server response time degradation Reduce meaningless and non-actionable alerts Examine blameless retrospective Develop a just culture

About this training course Gas-lift is one of the predominant forms of artificial lift used for lifting liquids from conventional, unconventional, onshore and offshore assets. Gas-lift and its various forms (intermittent lift, gas-assisted plunger lift) allows life of well lift-possibilities when selected and applied properly. This 5-day training course is designed to give participants a thorough understanding of gas-lift technology and related application concepts. This training course covers main components such as application envelope, relative strengths and weaknesses of gas-lift and its different forms like intermittent lift, gas-assisted plunger lift. Participants solve examples and class problems throughout the course. Animations and videos reinforce the concepts under discussion. Unique Features: Hands-on usage of SNAP Software to solve gas-lift exercises Discussion on digital oil field Machine learning applications in gas-lift optimization Training Objectives After the completion of this training course, participants will be able to: Understand the fundamental theories and procedures related to Gas-Lift operations Easily recognize the different components of the gas-lift system and their basic structural and operational features Be able to design a gas-lift installation Comprehend how digital oilfield tools help address ESP challenges Examine recent advances in real-time approaches to the production monitoring and lift management Target Audience This training course is suitable and will greatly benefit the following specific groups: Production, reservoir, completion, drilling and facilities engineers, analysts, and operators Anyone interested in learning about implications of gas-lift systems for their fields and reservoirs Course Level Intermediate Advanced Training Methods The training instructor relies on a highly interactive training method to enhance the learning process. This method ensures that all participants gain a complete understanding of all the topics covered. The training environment is highly stimulating, challenging, and effective because the participants will learn by case studies which will allow them to apply the material taught in their own organization. Course Duration: 5 days in total (35 hours). Training Schedule 0830 - Registration 0900 - Start of training 1030 - Morning Break 1045 - Training recommences 1230 - Lunch Break 1330 - Training recommences 1515 - Evening break 1530 - Training recommences 1700 - End of Training The maximum number of participants allowed for this training course is 20. This course is also available through our Virtual Instructor Led Training (VILT) format. Prerequisites: Understanding of petroleum production concepts. Each participant needs a laptop/PC for solving class examples using software to be provided during class. Laptop/PC needs to have a current Windows operating system and at least 500 MB free disk space. Participants should have administrator rights to install software. Trainer Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA. Highlighted Work Experience: At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe. Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements. Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics. Developed a workshop on digital oilfield approaches for production engineers. Patents: Principal inventor: 'Smarter Slug Flow Conditioning and Control' Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells' Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution' Worldwide Experience in Training / Seminar / Workshop Deliveries: Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&T, Louisiana State, U of Southern California, and U of Houston. He has conducted seminars, bespoke trainings / workshops globally for practicing professionals: Companies: Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others. Countries: USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela. Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations

Get ready for an exceptional online learning experience with the Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security bundle! This carefully curated collection of 20 premium courses is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations. The Python & Data Science package is dynamic, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, the Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Securitypackage has something for everyone. As part of the Python & Data Science package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Python & Data Science bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth! This Bundle Comprises the Following Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security CPD-accredited courses: Course 01: Python Programming: Beginner To Expert Course 02: Data Science & Machine Learning with Python Course 03: Coding with Python 3 Course 04: Introduction to Coding With HTML, CSS, & Javascript Course 05: Python for Spatial Analysis in ArcGIS Course 06: Python Programming Bible | Networking, GUI, Email, XML, CGI Course 07: Business Intelligence and Data Mining Course 08: SQL for Data Science, Data Analytics and Data Visualization Course 09: Python Data Science with Numpy, Pandas and Matplotlib Course 10: Cloud Computing / CompTIA Cloud+ (CV0-002) Course 11: Cyber Security Awareness Training Course 12: Learn Ethical Hacking From A-Z: Beginner To Expert Course 13: Easy to Advanced Data Structures Course 14: R Programming for Data Science Course 15: GDPR UK Training Course 16: Career Development Plan Fundamentals Course 17: CV Writing and Job Searching Course 18: Learn to Level Up Your Leadership Course 19: Networking Skills for Personal Success Course 20: Ace Your Presentations: Public Speaking Masterclass What will make you stand out? Upon completion of this online Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security bundle, you will gain the following: CPD QS Accredited Proficiency with this Python & Data Science bundle After successfully completing the Python & Data Science bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities. Lifetime access to the whole collection of learning materials of this Python & Data Science bundle The online test with immediate results You can study and complete the Python & Data Science bundle at your own pace. Study for the Python & Data Science bundle using any internet-connected device, such as a computer, tablet, or mobile device. Each course in this Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Python & Data Science bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Embrace the future of learning with the Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security , a rich anthology of 30 diverse courses. Our experts handpick each course in the Python & Data Science bundle to ensure a wide spectrum of learning opportunities. This Python & Data Science bundle will take you on a unique and enriching educational journey. The Python & Data Science bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Python & Data Science bundle offers you the flexibility and convenience to learn at your own pace. Make the Python & Data Science package your trusted companion in your lifelong learning journey. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security bundle is perfect for: Beginners interested in technology: Individuals with little to no background in tech who are looking to start their careers in various IT domains. Aspiring Data Scientists and Analysts: Those aiming to build foundational and advanced skills in data science and machine learning. Future Software Developers: Individuals interested in learning Python and SQL for software development or database management. IT Security Enthusiasts: People who are keen on entering the field of cyber security and want to understand how to protect data in a digital environment. Cloud Computing Aspirants: Those looking to gain skills in cloud technologies and understand how to manage and deploy applications on the cloud. Requirements You are warmly invited to register for this Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment. Career path Upon Python, Data Science, Machine Learning, SQL, Cloud computing & Cyber Security course completion, you can expect to: Python Developer Data Analyst Machine Learning Engineer Database Administrator Cloud Solutions Architect Cyber Security Specialist Data Science Consultant Systems Analyst Network Security Engineer Research Scientist (AI/ML) Certificates 20 CPD Quality Standard Pdf Certificates Digital certificate - Included