5713 Computing & IT courses

Duration 1 Days 6 CPD hours This course is intended for This introductory-level course is great for experienced technical professionals working in a wide range of industries, such as software development, data science, marketing and advertising, finance, healthcare, and more, who are looking to use the latest AI and machine learning techniques in their day to day. The hands-on labs in this course use Python, so you should have some familiarity with Python scripting basics. Overview Working in an interactive learning environment, led by our engaging OpenAI expert you'll: Understand the capabilities and products offered by OpenAI and how to access them through the OpenAI API. set up an OpenAI environment on Azure, including creating an Azure virtual machine and configuring the environment to connect to Azure resources. Gain hands-on experience building a GPT-3 based chatbot on Azure and implement advanced natural language processing capabilities. Use the OpenAI API to access GPT-3 and generate high-quality text Learn how to use Whisper to improve the quality of text generation. Understand the capabilities of DALL-E and use it to generate images for unique and engaging visuals. Geared for technical professionals, Quick Start to Azure AI Basics for Technical Users is a fun, fast paced course designed to quickly get you up to speed with OpenAI?s powerful tools and functionality, and to provide hands-on experience in setting up an OpenAI environment on Azure. Guided by our AI expert, you?ll explore the capabilities of OpenAI's GPT-3, Whisper and DALL-E, and build a chatbot on Azure. It will provide you with the knowledge and resources to continue your journey in AI and machine learning and have a good understanding of the potential of OpenAI and Azure for your projects. First, you?ll dive into the world of OpenAI, learning about its products and the capabilities they offer. You'll also discover how Azure's offerings for AI and machine learning can complement OpenAI's tools and resources, providing you with a powerful combination for your projects. And don't worry if you're new to Azure, we'll walk you through the process of setting up an account and creating a resource group. As you progress through the course, you'll get the chance to work with OpenAI's GPT-3, one of the most advanced large language models available today. You'll learn how to use the OpenAI API to access GPT-3 and discover how to use it to generate high-quality text quickly and easily. And that's not all, you'll also learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to implement advanced natural language processing capabilities in your chatbot projects. The course will also cover OpenAI Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. And you will learn about OpenAI DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Introduction to OpenAI and Azure Explore OpenAI and its products, as well as Azure's offerings for AI and Machine Learning, allowing you to understand the tools and resources available to you for your AI projects. Explore OpenAI and its products Explore Azure and its offerings for AI and Machine Learning Get Hands-On: Setting up an OpenAI environment on Azure Walk through the process of setting up an OpenAI environment on Azure, giving you the hands-on experience needed to start building your own projects using OpenAI and Azure. Create an Azure virtual machine and installing the OpenAI SDK Configure the OpenAI environment and connecting to Azure resources Explore OpenAI GPT-3 Learn about GPT-3, one of OpenAI's most powerful language models, and how to use it to generate high quality text, giving you the ability to create natural language content quickly and easily. Review GPT-3 and its capabilities Use the OpenAI API to access GPT-3 Get Hands-on: Building a GPT-3 based chatbot on Azure Learn how to build a GPT-3 based chatbot on Azure, giving you the opportunity to learn how to implement advanced natural language processing capabilities in your chatbot projects. Setup an Azure Function and creating a chatbot Integrate GPT-3 with the chatbot OpenAI Whisper Explore Whisper, an OpenAI tool that can improve the quality of text generation, allowing you to create more coherent and natural language content. Explore Whisper and its capabilities Use Whisper to improve the quality of text generation OpenAI DALL-E Explore DALL-E, an OpenAI tool that can generate images, giving you the ability to create unique and engaging visuals to enhance your content and projects. Explore DALL-E and its capabilities Use the OpenAI API to access DALL-E What?s Next: Keep Going! Other ways OpenAI can impact your day to day Explore great places to check for expanded tools and add-ons for Azure OpenAI Where to go for help and support Quick Look at Generative AI and its Business Implications Understanding Generative AI Generative AI in Business Ethical considerations of Generative AI

Duration 0.5 Days 3 CPD hours This course is intended for Individuals and organizations seeking a foundational understanding of DevOps Overview Please refer to Overview This course brings a high-level understanding of DevOps, the cultural and professional movement that stresses communication, collaboration, integration, and automation to improve the flow of work between software developers and IT operations professionals. Course introductionWhat is DevOps? Why Now?Emerging DevOps PracticesCultureAutomationLeanMeasurement and MetricsSharingGetting Started: Implementing DevOpsNext Steps

Duration 1 Days 6 CPD hours This course is intended for This course provides an introductory overview of the CMMC program for organizational decision makers. Business and IT leaders and IT staff might consider taking this course to learn about the CMMC Model to get a sense of what's required for a successful assessment, and the various ways they can start preparing. Overview In this course, you will identify the key elements and potential impacts of the Cybersecurity Maturity Model Certification (CMMC) program. You will: Identify the crucial elements that are driving the CMMC initiative. Describe the architecture of the CMMC Model and the rationale behind it. Prepare your organization for a successful CMMC Assessment. Identify the roles and responsibilities in the CMMC ecosystem and describe the phases of an Assessment. The Cybersecurity Maturity Model Certification (CMMC), managed by The Cyber AB (formerly known as the CMMC Accreditation Body or the CMMC-AB), is a program through which an organization's cybersecurity program maturity is measured by their initial and ongoing compliance with applicable cybersecurity practices. This course provides a complete review of the key elements of this important program and will entitle you to a CMMC Trailblazer badge.Important: This curriculum product is not considered CMMC-AB Approved Training Material (CATM). This course is not intended as certification preparation and does not qualify students to sit for the CMMC CP certification exam. Identifying What's at Stake Topic A: Identify the Threats and Regulatory Responses Topic B: Identify Sensitive Information Describing CMMC Topic A: Describe the CMMC Model Architecture Topic B: Describe the CMMC Program Getting Ready for a CMMC Assessment Topic A: Scope Your Environment Topic B: Analyze the CMMC Assessment Guides Topic C: Foster a Mature Cybersecurity Culture Topic D: Identify Helpful Documents Topic E: Evaluate Your Readiness Interacting with the CMMC Ecosystem Topic A: Identify the CMMC Ecosystem Topic B: Describe a CMMC Assessment

Duration 1 Days 6 CPD hours This course is intended for This course is intended for those responsible for ITAD programs and other IT professionals involved in Asset Management, resource budgeting, finance, software licensing, contract management and strategic planning. Overview Students will learn the best practices in an IT Asset Management Program and align those processes with their organizations' business practices. They will be able to manage overall ITAM programs and demonstrate in-depth knowledge, operational knowledge and competence in asset disposal and process development. The IAITAM Certified IT Asset Disposition (CITAD) course prepares individuals to manage the IT asset disposal process within an organization. Best practices in IT Asset Disposition (ITAD) are broken down from policy management, data security to chain of custody transitioning. Attendees whose job responsibilities include ITAD will take away the knowledge of how to avoid risk of data loss and public exposure that surround a breakdown in ITAD process management. ITAD best practices, financial return, data security global implications and the importance of vendor management are just a few of the topics incorporated in the CITAD course. This course exposes the attendee to numerous concepts for ITAM that are relevant for both direct application and as a means of discussion for those persons who will implement, manage and direct ITAM initiatives for their organizations. This course includes the exam for CITAD certification. Course Outline Disposition Overview Disposition and ITAM Organizational Goals for Disposition ITAM Goals for Disposition Governance of Electronic Disposal Composition of E-Scrap Waste Management Laws Foundation for Disposal Management Policy Topics Relevant to Disposition Asset Standards Benefit Disposal The Role of Automation Data Security Governance Working with Vendors Selecting Vendors Due Diligence The Removal Process Software During Disposition Decision Factors for Retirement The Disposition Processes Financial Management & Measurement Additional course details: Nexus Humans Certified IT Asset Disposal (CITAD) 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 Certified IT Asset Disposal (CITAD) 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.

Duration 2 Days 12 CPD hours This course is intended for Network Video Engineer Voice/UC/Collaboration/Communications Engineer Collaboration Tools Engineer Collaboration Sales/Systems Engineer Overview Install, Configure, and Implement Cisco Emergency Responder (Cisco ER). Configure CUCM for CER Configure Emergency Response Locations (ERLs) Configure Emergency Location Identification Numbers (ELINs) Configure PSAP calls and PSAP CallBack Configure Users and onsite Security Management This is a 2-day hands-on course, where students will Install, Deploy, and Configure Cisco Emergency Responder (Cisco ER) 12.5. Student will also integrate emergency communication system with Cisco Unified Communications Manager. Students will learn how Cisco ER automatically notifies and routes calls to the local public safety answering point (PSAP) operator. Students will configure emergency response locations (ERLs) and emergency location identification numbers (ELINs) in CER to properly route enhanced 911 (E911) calls. You will also examine CER disaster recovery and user management. Cisco Emergency Responder Overview PSAP/ Emergency Calling Overview National Emergency Number Association Legislation and Regulation Service Provider ALI Automatic Number Identification (ANI) Automatic Location Identification (ALI) NENA Emergency Response Location NENA Guidelines for ERLs NENA Emergency Location Identification Number (ELIN) E911 Preparation Cisco Emergency Call Handler Cisco Emergency Responder 11.x Enhancements License Management Emergency Responder Redundancy Clustering CER over the WAN Integration with UC Manager Intrado Architecture CER Wireless Features Overview Installing Cisco Emergency Responder Supported Hardware Platforms CER Virtual Server Requirements Deploy Cisco CER OVF/OVA Installation of CER CER CLI Interface Reset Application Administrator Password Add 2nd CER Server - Subscriber Upgrade VMware Tools on Cisco Emergency Responder Server CER Backup and Restore CER PLM Licensing Unified Communication Manager CER Configuration Cisco Unified Communications Manager Administrator Interfaces Cisco Unified Communications Manager Required Services for CER CUCM SNMP Settings Phone Partition and Calling Search Spaces Partitions for 911 Services CER CUCM Configuration for CTI Route Points and CTI Ports Configure CER Route Patterns for 911 and Security Personal Create Translation Patterns for ELINs Create Emergency Responder Cisco Unified Communications Manager User Location Awareness Overview Configure Wireless Endpoint Tracking Feature on UCM 11.5 Cisco Emergency Responder (CER) Configuration Emergency Responder Interface E.164 Dial Plan Support Cisco Emergency Responder Groups Setup CER Groups CER Telephony Settings for CER Cisco CER License Manager Cisco CER Email Settings Cisco CER - Add Subscriber Onsite Security Alerts for Security Personnel Pager Alert Configuration Configure Emergency Response Location (ERL) Configure Emergency Location Identification Number (ELIN) ERL Migration Tool Configure SNMP Configure Phone Tracking Configure LAN Switch Tracking Configuring IP Subnet-based ERLs Configuring Manual Phone Tracking Emergency Responder User Management Manage Onsite Alerts, ERLs, and ALI Data User and Security Logins CER - Web Alerts CER - ERL Audit Trail Export PS-ALI Records ERL Debug Tool

Artificial Intelligence brings exciting new opportunities to the field of Conversational User Interfaces (CUI). Learn key concepts and proven design methods to deliver cutting-edge experiences and reach better business outcomes. Silvia Podesta is a Designer in the Client Engineering Team at IBM Nordics. She leverages design thinking, service and UX design to help clients identify opportunities for innovation and pioneer transformational experiences through IBM technology.

About UX Academy: UX Academy provides live online hands-on training to help you take the next step in your career no matter what level you’re at. Offering Beginner, Intermediate UX courses, Product Design, Strategy and Voice Design developed in collaboration with Amazon.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Solutions Architects who are new to designing and building cloud architectures Data Center Architects who are migrating from on-premises environment to cloud architectures Other IT/cloud roles who want to understand how to design and build cloud architectures Overview In this course, you will learn how to: Make architectural decisions based on AWS architectural principles and best practices Use AWS services to make your infrastructure scalable, reliable, and highly available Use AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well Architected Framework to improve architectures with AWS solutions This course covers all aspects of how to architect for the cloud over four-and-a-half-days. It covers topics from Architecting on AWS and Advanced Architecting on AWS to offer an immersive course in cloud architecture. You will learn how to design cloud architectures, starting small and working to large-scale enterprise level designs-and everything in between. Starting with the Well-Architected Framework, you will learn important architecting information for AWS services including: compute, storage, database, networking, security, monitoring, automation, optimization, benefits of de-coupling applications and serverless, building for resilience, and understanding costs Module 1: Introduction The real story of AWS Well-Architected Framework Six advantages of the cloud Global infrastructure Module 2: The Simplest Architectures S3 Glacier Choosing your regions Hands-on lab: Static Website Module 3: Adding a Compute Layer EC2 Storage solutions for instances Purchasing options such as dedicated host vs instances Module 4: Adding a Database Layer Relational vs non-relational Managed databases RDS Dynamo DB Neptune Hands-on lab: Deploying a web application on AWS Module 5: Networking in AWS Part 1 VPC CIDR and subnets Public vs private subnets NAT and internet gateway Security groups Module 6: Networking in AWS Part 2 Virtual Private Gateway VPN Direct Connect VPC peering Transit Gateway VPC Endpoints Elastic Load Balancer Route 53 Hands-on lab: Creating a VPC Module 7: AWS Identity and Access Management (IAM) IAM Identity federation Cognito Module 8: Organizations Organizations Multiple account management Tagging strategies Module 9: Elasticity, High Availability, and Monitoring Elasticity vs inelasticity Monitoring with CloudWatch, CloudTrail, and VPC Flow Logs Auto scaling Scaling databases Hands-on lab: Creating a highly available environment Module 10: Automation Why automate? CloudFormation AWS Quick Starts AWS Systems Manager AWS OpsWorks AWS Elastic Beanstalk Module 11: Deployment Methods Why use a deployment method? Blue green and canary deployment Tools to implement your deployment methods CI/CD Hands-on lab: Automating infrastructure deployment Module 12: Caching When and why you should cache your data Cloudfront Elasticache (Redis/Memcached) DynamoDB Accelerator Module 13: Security of Your Data Shared responsibility model Data classification Encryption Automatic data security Module 14: Building Decoupled Architecture Tight coupling vs loose coupling SQS SNS Module 15: Optimizations and Review Review questions Best practices Activity: Design and architecture - two trues and one lie Module 16: Microservices What is a microservice? Containers ECS Fargate EKS Module 17: Serverless Why use serverless? Lambda API Gateway AWS Step Functions Hands-on lab: Implementing a serverless architecture with AWS Managed Services Module 18: Building for Resilience Using managed services greatly increases resiliency Serverless for resiliency Issues with microservices to be aware of DDoS Hands-on lab: Amazon CloudFront content delivery and automating WAF rules Module 19: Networking in AWS Part 3 Elastic Network Adapter Maximum transmission units Global Accelerator Site to site VPN Transit Gateway Module 20: Understanding Costs Simple monthly calculator Right sizing your instances Price sensitive architecture examples Module 21: Migration Strategies Cloud migration strategies Planning Migrating Optimizing Hands-on lab: Application deployment using AWS Fargate Module 22: RTO/RPO and Backup Recovery Setup Disaster planning Recovery options Module 23: Final Review Architecting advice Service use case questions Example test questions Additional course details: Nexus Humans Architecting on AWS - Accelerator 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 Architecting on AWS - Accelerator 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.

Duration 1 Days 6 CPD hours This course is intended for This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks. Overview After completing this course, you will be able to: Provision an Azure Databricks workspace and cluster Use Azure Databricks to train a machine learning model Use MLflow to track experiments and manage machine learning models Integrate Azure Databricks with Azure Machine Learning Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. Introduction to Azure Databricks Getting Started with Azure Databricks Working with Data in Azure Databricks Training and Evaluating Machine Learning Models Preparing Data for Machine Learning Training a Machine Learning Model Managing Experiments and Models Using MLflow to Track Experiments Managing Models Managing Experiments and Models Using MLflow to Track Experiments Managing Models Integrating Azure Databricks and Azure Machine Learning Tracking Experiments with Azure Machine Learning Deploying Models

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.