1786 AI courses in Nottingham delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for Senior Consultants (both functional and technical) that aspire to be Solution Architects, or current Solution Architects that are new to the role. The Solution Architect is responsible for the successful design, implementation, deployment and adoption of an overall solution. The Solution Architect ensures that the solution meets the customer?s needs now and in the future. In this course, students will learn about decisions a Solution Architect makes during an implementation, covering security, integrations, Power Apps architecture, Power Automate architecture, and more. This course is designed to give you an introduction to the Solution Architect role. Becoming a Solution Architect/Getting to know your customer Define a Solution Architect Role of a Solution Architect on projects Project Methodology Getting to know your customer Group exercise - Getting to know your customer Conceptualizing the design from requirements How to lead the requirement collection effort Using fit gap analysis Pillars of good architecture Blueprinting the solution architecture Group exercise - Design from requirements Project governance and working as a team Solution Architect's role in project governance Techniques for keeping a project on track Scenarios that could cause a project to fail Group exercise - Project governance and working as a team Power Platform Architecture Key Power Platform architecture components Understand how platform design and limits influence solution architectures Updates and feature releases Understand how to communicate how the platform meets customer needs Data Modeling Data model influences Data model strategy Data types Data relationships Group exercise - Data modeling Analytics and artificial intelligence Planning and evaluating requirements Operational reporting Power BI Enterprise BI Pre-built insights and custom AI Power Apps Architecture Discuss options for apps and how to choose where to start Discuss app composition options Using components as part of your app architecture Considerations for including Portals as an app in your architecture Group exercise - Power Apps Architecture topics Application Lifecycle Management (ALM) Microsoft vision and Solution Architect's role in ALM Environment strategies Defning a solution structure for your deliverable Power Automate Architecture Discuss options for automation and custom logic Review considerations for using triggers and common actions Explore using Business Process Flows (BPF) to guide users through business processes Group Exercise - Evaluate scenarios for Power Automate usage Security Modeling Solution Architect's role in security modeling Discovery and learning your client's environment Controlling access to environments and resources Controlling access to CDS Data Group Exercise - Security Modeling Integration Solution Architects role in Integrations What is an integration and why do we need it Platform features that enable integration CDS Event Publishing Scenarios for group discussion Dynamics 365 Applications Architecture Solution Architect's role when deploying Dynamics 365 apps Architecture Considerations for primary apps Group Exercise - App specific working groups evaluate requirements Power Virtual Agents architecture Introduction Chatbot options Chatbot concepts Best practices Integrate chatbots Power Virtual Agents in Microsoft Teams Robotic Process Automation Introduction Power Automate Desktop Recording and editing tasks Running desktop flows Process advisor Testing and Go Live Solution Architect's role with testing and go live Planning for testing Planning for go live

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

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Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is any IT, facilities or data centre professional who works in and around the data centre and has the responsibility to achieve and improve efficiency and environmental sustainability, whilst maintaining the availability and manageability of the data centre. Overview After completion of the course the participant will be able to: Understand the impact of data centres on the environment Describe the various environmental/energy management standards Understand the purpose and goals of the legally binding international treaties on climate change Implement various sustainable performance metrics and how to use them in the data centre environment Manage data centre environmental sustainability using international standards Set up the measurement, monitoring and reporting of energy usage Use power efficiency indicators in a variety of data centre designs Use best practices for energy savings in the electrical infrastructure and in the mechanical (cooling) infrastructure Use best practices for energy savings for the ICT equipment and data storage Understand the importance of water management and waste management Understand the different ways to use sustainable energy in the data centre Get practical tips and innovative ideas to make a data centre more sustainable The CDESS© course is aimed at providing knowledge of the standards and guidelines related to environmental sustainability, and how to move your data centre (existing or new) to a more environmentally sustainable design and operations. Impact of Data Centres on the Environment Predictions in 2010 Current situation Outlook and commitments What is Environmental Sustainability The importance of sustainability Senior management commitment Environmental sustainability framework Sustainability policies Performance standards and metrics Information policies Transparency Awareness Service charging models Environmental Management Environmental sustainability framework (ISO 14001) Standards and guidelines ? ISO 50001 / ISO 30134 Measurement and categories Baselining Trend analysis Reporting Power Effiðciency Indicators Various eðfficiency indicators Power Usage Effectiveness (PUE) PUE measurement levels Factors affecting PUE Measurement points and intervals PUE in mixed source environments Measuring PUE in a mixed-use building PUE reporting Impact of PUE after optimising IT load Electrical Energy Savings (Electrical) Identifying the starting point for saving energy Sizing of power DC power Generators UPS systems Power Factor (PF) Energy savings on lighting Electrical Energy Savings (Mechanical) Energy savings on the cooling infrastructure Temperature and humidity setpoints Various energy eðcient cooling technologies Energy savings on the airflow Liquid cooling Energy reusage PUE, ERE/ERF and Control Volume Electrical Energy Savings (ICT) Procurement IT equipment energy eðfficiency ITEEsv, SMPE, SMPO IT equipment utilisation Server virtualisation Open compute project Electrical Energy Savings (Data Storage) Data management Data storage management Data storage equipment effiðciency Water Management Water Usage Effectiveness (WUE) Improving WUE Water usage at the power generation source Energy Water Intensity Factor (EWIF) Waste Management Waste management policies Life-cycle assessment (Cradle to the grave) 3 R?s for waste management Reduce Reuse Second-hand market Recycle Sustainable Energy Usage Sustainable energy sources Power purchase agreements Energy attribute certificates Renewable Energy Factor (REF) Matching renewable energy supply and demand Sustainable energy storage Carbon trading Automated Environmental Management Systems Use of AI and machine learning Load migration Data Centre Infrastructure Management (DCIM) solutions

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is as follows: IT Solution Architects Network Security Architects Networking Admin and Operations Networking Field Engineers In this workshop you will learn why we are implementing Assurance, and what does looks like and key features. We will also discuss the Cisco DNA center appliance and workflow and tasks associated with an implementation. Module 1: Introduction to Cisco DNA Center Assurance Introduction to DNA Center System Architecture Key Features and Use Cases Introduction to Cisco ISE and DNAC-ISE integration Module 2: Design Network design options Sites Creating Enterprise and Sites Hierarchy Configuring General Network Settings Loading maps into the GUI IP Address Management Software Image Management ? Lab on Day 5 Network Device Profiles AAA SNMP Syslog IP address pools Creating Enterprise and Guest SSIDs ? Lab on Day 2 Creating the wireless RF Profile Cresting the Guest Portal for the Guest SSIDs Network profiles ? Lab on Day 2 Authentication templates Module 3: Discovery and Provision Device Discovery and Protocols Devices Onboarding Assigning Devices to a site Provisioning device with profiles Plug and Play Templates Templates for Day-0 Templates for Day-N operations Module 4: Monitoring Device, Client, and Application Health DNAC Telemetry Monitoring Network Device Health and Performance Monitoring Wired and Wireless Client Health and Performance Monitoring Application Health and Performance Module 5: Application Visibility and DNAC Integration with Umbrella Monitoring Application Visibility in DNA Center Umbrella Introduction DNA Center Umbrella Integration and Use Cases Module 6: Troubleshooting Issues, Observing Insights and Trends Detect Issues, Insights, and Trends in the Network DNA Center Integration with other tools for Monitoring and Management Module 7: Troubleshooting using Cisco DNA Center Assurance Tools DNAC Assurance Troubleshooting Tools Using Sensor Tests Using Intelligent Capture Spectrum Analysis Module 8: DNAC and Thousand Eyes Introduction to ThousandEyes ThousandEyes Use Cases DNA Center and ThousandEyes Integration Module 9: AI Analytics and Machine Learning in DNA Center Overview of AI Analytics and ML (Machine Learning) DNA Center AI and ML Use Cases Module 10: DNA Center Maintenance DNA Center Reports DNA Center Backup and Restore

Duration 2 Days 12 CPD hours This course is intended for The target audience for the DevOps Foundation course includes Management, Operations, Developers, QA and Testing professionals such as: Individuals involved in IT development IT operations or IT service management. Individuals who require an understanding of DevOps principles. IT professionals working within, or about to enter, an Agile Service Design Environment The following IT roles: Automation Architects, Application Developers, Business Analysts, Business Managers, Business Stakeholders, Change Agents, Consultants, DevOps Consultants, DevOps Engineers, Infrastructure Architect, Integration Specialists, IT Directors, IT Managers, IT Operations, IT Team Leaders, Lean Coaches, Network Administrators, Operations Managers, Project Managers, Release Engineers, Software Developers, Software Tester/QA, System Administrators, Systems Engineers, System Integrators, Tool Providers. Overview The learning objectives for DevOps Foundation include an understanding of: DevOps objectives and vocabulary Benefits to the business and IT Principles and practices including Continuous Integration, Continuous Delivery, testing, security and the Three Ways DevOps relationship to Agile, Lean and ITSM Improved workflows, communication and feedback loops Automation practices including deployment pipelines and DevOps toolchains Scaling DevOps for the enterprise Critical success factors and key performance indicators Real-life examples and results The DevOps Foundation course provides a baseline understanding of key DevOps terminology to ensure everyone is talking the same language and highlights the benefits of DevOps to support organizational success. Learners will gain an 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. This course prepares you for the DevOps Foundation (DOFD) certification. Exploring DevOps Defining DevOps Why Does DevOps Matter? Core DevOps Principles The Three Ways The First Way The Theory of Constraints The Second Way The Third Way Chaos Engineering Learning Organizations Key DevOps Practices Continuous Testing, Integration, Delivery, Deployment Site Reliability & Resilience Engineering DevSecOps ChatOps Kanban Business and Technology Frameworks Agile ITSM Lean Safety Culture Learning Organizations Continuous Funding Culture, Behaviors & Operating Models Defining Culture Cultural Debt Behavioral Models Organizational maturity models Automation & Architecting DevOps Toolchains CI/CD Cloud, Containers, and Microservices AI and Machine Learning Automation DevOps Toolchains Measurement, Metrics, and Reporting The Importance of Measurement DevOps Metrics - Speed, Quality, Stability, Culture Change lead/cycle time Value Driven Metrics Sharing, Shadowing and Evolving DevOps in the Enterprise Roles DevOps Leadership Organizational Considerations Getting Started Challenges, Risks, and Critical Success Factors Additional course details: Nexus Humans DevOps Foundation (DevOps Institute) 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 DevOps Foundation (DevOps Institute) 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.

Join Us for a Webinar: Curious About AI – Empowering You Through Innovation We’re excited to invite you to an engaging virtual session, Curious About AI, where Boris Puncer will explore how artificial intelligence is transforming the way we work and unlocking new opportunities across the business. AI is more than just a technology shift—it’s a powerful enabler of change. Whether you're already familiar with AI or just starting to explore its potential, this session will provide valuable insights into how it can enhance your productivity and creativity. In this session, you’ll discover: How AI is being used to optimise everyday processes Ways AI can help enhance your personal productivity The role of AI in driving innovation across teams and functions How to leverage AI to create more time for strategic, creative thinking Real examples of how AI is already making an impact in our organisation Don’t miss this opportunity to learn how AI can empower you in your role and support a culture of innovation and efficiency. Date: Monday, 12th May Time: 10:00 – 11:00 Location: Virtual Register Now!

Duration 1 Days 6 CPD hours For the better part of every day, we are communicating to and with others. Whether it?s the speech you deliver in the boardroom, the level of attention you give your spouse when they are talking to you, or the look you give the cat, it all means something. This workshop will help participants understand the different methods of communication and how to make the most of each of them. 1 - Getting Started Icebreaker Housekeeping Items The Parking Lot Workshop Objectives 2 - The Big Picture What is Communication? How Do We Communicate? Other Factors in Communication 3 - Understanding Communication Barriers An Overview of Common Barriers Language Barriers Cultural Barriers Differences in Time and Place 4 - Paraverbal Communication Skills The Power of Pitch The Truth about Tone The Strength of Speed 5 - Non-Verbal Communication Understanding the Mehrabian Study All About Body Language Interpreting Gestures 6 - Speaking Like a STAR S = Situation T = Task A = Action R = Result Summary 7 - Listening Skills Seven Ways to Listen Better Today Understanding Active Listening Sending Good Signals to Others 8 - Asking Good Questions Open Questions Closed Questions Probing Questions 9 - Appreciative Inquiry The Purpose of AI The Four Stages Examples and Case Studies 10 - Mastering the Art of Conversation Level One: Discussing General Topics Level Two: Sharing Ideas and Perspectives Level Three: Sharing Personal Experiences Our Top Networking Tips 11 - Advanced Communication Skills Understanding Precipitating Factors Establishing Common Ground Using ?I? Messages 12 - Wrapping Up Words from the Wise Review of Parking Lot Lessons Learned Completion of Action Plans and Evaluations Additional course details: Nexus Humans Communication Strategies 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 Communication Strategies 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.

Why Choose Unity 3D Game Design Training Course? Course Link Unity transforms ideas into reality, offering limitless possibilities for 2D and 3D games, VR, AR, and AI experiences. From films to architecture, training videos, and interactive tutorials, Unity revolutionizes industries with its interactive engagement, making it the top choice for solutions. Duration: 10 hrs Method: 1-on-1, Personalized attention Schedule: Tailor your own hours of your choice, available from Mon to Sat between 9 am and 7 pm Is Unity Good for Beginners? Definitely! Unity is an ideal starting point for beginners in game development. It offers an accessible platform to learn state logic and C# programming, making it popular among new programmers. Whether you choose self-guided or structured learning, Unity provides a strong foundation for 3D game development. Coding in Unity? Coding is optional in Unity, thanks to the visual scripting tool, Bolt. Users can implement ideas without coding using flow graphs and state graphs for low-level and high-level logic. Paid tools like PlayMaker and Adventure Creator offer more advanced gameplay and AI behaviors. How Does Unity's Game Engine Work? Unity operates as a versatile scene player, initializing settings for graphics, audio, and input devices at game start. It loads scenes with assets and game objects, executing a cycle that renders scenes, runs physics simulations, and handles events, providing a seamless and dynamic game experience. Is Unity Good for Beginners? Definitely! Unity is an ideal starting point for beginners in game development. It offers an accessible platform to learn state logic and C# programming, making it popular among new programmers. Whether you choose self-guided or structured learning, Unity provides a strong foundation for 3D game development. 10-hour Unity 3D Game Design Training Course: Module 1: Introduction to Unity 3D (2 hours) - What is Unity 3D and why use it for game design? - Understanding the Unity 3D interface - Creating and managing projects in Unity 3D - Importing and managing assets in Unity 3D - Understanding game objects and components in Unity 3D Module 2: Game Mechanics (2 hours) - Basic game mechanics and concepts - Player movement and camera control - Creating and controlling game objects - Working with physics and collision detection - Creating interactive environments Module 3: Scripting with C# (2 hours) - Introduction to C# scripting language - Understanding variables and data types in C# - Creating and using functions in C# - Controlling game objects with C# - Understanding game loops and events Module 4: User Interfaces and Audio (2 hours) - Designing user interfaces in Unity 3D - Creating and using buttons, sliders, and input fields - Audio import and editing in Unity 3D - Creating and controlling game sound effects and background music Module 5: Optimization and Deployment (2 hours) - Understanding game optimization in Unity 3D - Optimizing game performance with scripting - Building and testing games for desktop and mobile platforms - Publishing games on the web or app stores Introduction to Unity: - Introduction to gaming and the game development process - Unity Basics - Interface - Inspector - Project and Hierarchy Starting Making a Game: - Working with Projects - Creating Projects - Importing Geometry - Importing Textures - Using the terrain generator to make the terrain - Creating basic primitives in Unity Materials: - Working with materials 1 - Working with materials 2 - Finishing materials on all objects Lighting: - Creating lights - Adjusting Lights - Creating Sunlight Animation: - Animating objects - Animating lights - Adjusting Animations Audio: - Adding Sound - Interacting with sound - Modifying sound Programming Tools: - JavaScript - Editor for JavaScript - Variables and functions - Simple programming Testing: - Testing the game - Fixing bugs - Making changes in games Building the Game: - Game authoring Settings - Building the game for windows - Playing the game Utilize Unity Pro, the ultimate real-time development platform, to craft 3D, 2D, VR, and AR experiences across diverse industries. From games to auto, AEC, and film, Unity Pro empowers you to create immersive content with multi-platform support. Visit https://www.unity.com/ to kickstart your journey today, enabling faster iterations and business growth through unparalleled development capabilities.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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.