Duration 5 Days 30 CPD hours This course is intended for This beginning DB2 basic course is for z/OS database administrators who need to acquire the basic skills required to administer a DB2 database in a z/OS environment. Overview Describe several services provided in a z/OS environmentExplain workloads in the batch environmentExplain workloads in the online environmentDescribe job roles in a z/OS environmentLog On to TSO/ENavigate TSO/E and ISPFUse TSO commandsSetup and utilize JCL (Job Control Language)Utilize SDSFDescribe the different types of data sets in a z/OS environmentAllocate data sets and list data set information and contentCreate and modify data set contentGive an overview of the DB2 9 environmentDescribe and utilize DB2 ObjectsDescribe and utilize several DB2 UtilitiesDescribe the DB2I (DB2 Interactive Facility) environmentUse SPUFI (SQL Processing Using File Input) to compose and execute SQLSetup and execute DB2 CommandsUnderstand DB2 LoggingDescribe DB2 program preparation processUnderstand DB2 startup and shutdownUnderstand and utilize DB2 recovery strategies This course is intended for students looking to develop fundamental skills or recognition through lectures and hands-on exercises of TSO/E and ISPF, data sets, DB2 objects, Structured Query Language, DB2 commands, JCL and SDSF. Day 1 Welcome Unit 1: Introduction Unit 2: TSO/E and ISPF Exercise 1: TSO and ISPF Exercise 1 Review Unit 3: Data Sets (Data Sets and Sequential Data Sets) Exercise 2: Sequential Data Sets Exercise 2 Review Day 2 Unit 3: Data Sets (Partitioned Data Sets) Exercise 3: Partitioned Data Sets Exercise 3 Review Unit 3: Data Sets (VSAM Data Sets) Exercise 4: VSAM Data Sets Exercise 4 Review Unit 4: JCL and SDSF Exercise 5: JCL and SDSF Exercise 5 Review Day 3 Unit 5: DB2 Relational Database Concepts Unit 6: Structured Query Language (SQL) and SPUFI Exercise 6: SQL and SPUFI Exercise 6 Review Unit 7: DB2 Objects (Databases and Table Spaces) Exercise 7: Databases and Table Spaces Exercise 7 Review Unit 7: DB2 Objects (Tables, Indexes, and Views) Exercise 8: Tables, Indexes, and Views Exercise 8 Review Day 4 Unit 7: DB2 Objects (Qualified Names, Implicit Object Creation, and SQL Statements) Exercise 9: Qualified Names, Implicit Object Creation, and SQL Statements Exercise 9 Review Unit 8: The DB2 System Exercise 10: The DB2 System Exercise 10 Review Unit 9: DB2 Commands and Program Preparation Exercise 11: DB2 Commands Exercise 11 Review Day 5 Unit 10: DB2 Utilities Exercise 12: DB2 Utilities Exercise 12 Review Unit 11: DB2 Shutdown, Startup, and Recovery Exercise 13: DB2 Recovery Exercise 13 Review Unit 12: Course Summary Additional course details: Nexus Humans CV041 IBM z/OS and DB2 Basics for DB2 for z/OS DBA Beginners 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 CV041 IBM z/OS and DB2 Basics for DB2 for z/OS DBA Beginners 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 3 Days 18 CPD hours This course is intended for This course is for Network, IT security, and systems administration professionals in a Security Operations position who are tasked with configuring optimum security settings for endpoints protected by Symantec Endpoint Protection 14. Overview At the completion of the course, you will be able to: Protect against Network Attacks and Enforcing Corporate Policies using the Firewall Policy. Blocking Threats with Intrusion Prevention. Introducing File-Based Threats. Preventing Attacks with SEP. Layered Security. Securing Windows Clients. Secure Mac Clients. Secure Linux Clients. Controlling Application and File Access. Restricting Device Access for Windows and Mac Clients. Hardening Clients with System Lockdown. Customizing Policies based on Location. Managing Security Exceptions. This course is designed for the network, IT security, and systems administration professionals in a Security Operations position who are tasked with configuring optimum security settings for endpoints protected by Symantec Endpoint Protection 14. Introduction Course environment Lab environment Introducing Network Threats Describing how Symantec Endpoint Protection protects each layer of the network stack Discovering the tools and methods used by attackers Describing the stages of an attack Protecting against Network Attacks and Enforcing Corporate Policies using the Firewall Policy Preventing network attacks Examining Firewall Policy elements Evaluating built-in rules Creating custom firewall rules Enforcing corporate security policy with firewall rules Blocking network attacks using protection and stealth settings Configuring advanced firewall feature Blocking Threats with Intrusion Prevention Introducing Intrusion Prevention technologies Configuring the Intrusion Prevention policy Managing custom signatures Monitoring Intrusion Prevention events Introducing File-Based Threats Describing threat types Discovering how attackers disguise their malicious applications Describing threat vectors Describing Advanced Persistent Threats and a typical attack scenario Following security best practices to reduce risks Preventing Attacks with SEP Layered Security Virus and Spyware protection needs and solutions Describing how Symantec Endpoint Protection protects each layer of the network stack Examining file reputation scoring Describing how SEP protects against zero-day threats and threats downloaded through files and email Describing how endpoints are protected with the Intelligent Threat Cloud Service Describing how the emulator executes a file in a sandbox and the machine learning engine?s role and function Securing Windows Clients Platform and Virus and Spyware Protection policy overview Tailoring scans to meet an environment?s needs Ensuring real-time protection for clients Detecting and remediating risks in downloaded files Identifying zero-day and unknown threats Preventing email from downloading malware Configuring advanced options Monitoring virus and spyware activity Securing Mac Clients Touring the SEP for Mac client Securing Mac clients Monitoring Mac clients Securing Linux Clients Navigating the Linux client Tailoring Virus and Spyware settings for Linux clients Monitoring Linux clients Providing Granular Control with Host Integrity Ensuring client compliance with Host Integrity Configuring Host Integrity Troubleshooting Host Integrity Monitoring Host Integrity Controlling Application and File Access Describing Application Control and concepts Creating application rulesets to restrict how applications run Monitoring Application Control events Restricting Device Access for Windows and Mac Clients Describing Device Control features and concepts for Windows and Mac clients Enforcing access to hardware using Device Control Discovering hardware access policy violations with reports, logs, and notifications Hardening Clients with System Lockdown What is System Lockdown? Determining to use System Lockdown in Whitelist or Blacklist mode Creating whitelists for blacklists Protecting clients by testing and Implementing System Lockdown Customizing Policies based on Location Creating locations to ensure the appropriate level of security when logging on remotely Determining the criteria and order of assessment before assigning policies Assigning policies to locations Monitoring locations on the SEPM and SEP client Managing Security Exceptions Creating file and folder exceptions for different scan types Describing the automatic exclusion created during installation Managing Windows and Mac exclusions Monitoring security exceptions
Duration 5 Days 30 CPD hours This course is intended for Senior Red Hat Enterprise Linux system administrators responsible for the management of multiple servers Overview - Verify a Red Hat Satellite 6.6 installation. - Regulate Red Hat Satellite with organizations, locations, users, and roles. - Manage software with Red Hat Satellite environments and content views. - Use Red Hat Satellite to configure hosts with Ansible playbooks and roles. - Provision hosts with integrated software and configuration management. - Implement Metal-as-a-Service (MaaS) with Satellite discovery and provisioning of unprovisioned hosts. Red Hat Satellite 6 Administration (RH403) is a lab-based course that explores the concepts and methods necessary for successful large-scale management of Red Hat© Enterprise Linux© systems. You will learn how to configure Red Hat Satellite 6 on a server and populate it with software packages. You will use Red Hat Satellite to manage the software development life cycle of a subscribed host and its configuration, and learn how to provision hosts integrated with software and Ansible© configuration management upon deployment. This course is based on Red Hat Enterprise Linux 8 and Red Hat Satellite 6.6. 1 - Plan and deploy Red Hat Satellite Plan and deploy Red Hat Satellite Plan a Red Hat Satellite deployment, then perform installation and initial configuration of Red Hat Satellite servers. 2 - Manage software life cycles Create and manage Red Hat software deployment life cycle environments. 3 - Register hosts Register and configure your Red Hat Enterprise Linux systems to use Red Hat Satellite, then organize those systems into groups for easier management. 4 - Deploy software to hosts Manage software deployment to registered hosts of your Red Hat Satellite infrastructure and practice managing environment paths, life cycle environments, and content views. 5 - Deploy custom software Create, manage, and deploy custom software products and repositories. 6 - Deploy Satellite capsule servers Perform installation and initial configuration of Red Hat Satellite capsule servers as components of a deployment plan. 7 - Run remote execution commands Configure the ability to run ad hoc and scheduled tasks on managed hosts using a variety of configuration management tools. 8 - Provision hosts Configure Satellite server for host deployment and perform host provisioning. 9 - Manage Red Hat Satellite using the API Integrate Red Hat Satellite functionality with custom scripts or external applications that access the API over HTTP. 10 - Plan a Red Hat Satellite deployment on a cloud platform Plan a Red Hat Satellite deployment, installation, and initial configuration on a cloud platform. 11 - Perform Red Hat Satellite server maintenance Manage Red Hat Satellite for security, recoverability, and growth. 12 - Comprehensive review Install and configure Red Hat Satellite Server, then provision content hosts. Additional course details: Nexus Humans Red Hat Satellite 6 Administration (RH403) 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 Red Hat Satellite 6 Administration (RH403) 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 intended for the following participants:Cloud professionals interested in taking the Data Engineer certification exam.Data engineering professionals interested in taking the Data Engineer certification exam. Overview This course teaches participants the following skills: Position the Professional Data Engineer Certification Provide information, tips, and advice on taking the exam Review the sample case studies Review each section of the exam covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate Connect candidates to appropriate target learning This course will help prospective candidates plan their preparation for the Professional Data Engineer exam. The session will cover the structure and format of the examination, as well as its relationship to other Google Cloud certifications. Through lectures, quizzes, and discussions, candidates will familiarize themselves with the domain covered by the examination, to help them devise a preparation strategy. Rehearse useful skills including exam question reasoning and case comprehension. Tips and review of topics from the Data Engineering curriculum. Understanding the Professional Data Engineer Certification Position the Professional Data Engineer certification among the offerings Distinguish between Associate and Professional Provide guidance between Professional Data Engineer and Associate Cloud Engineer Describe how the exam is administered and the exam rules Provide general advice about taking the exam Sample Case Studies for the Professional Data Engineer Exam Flowlogistic MJTelco Designing and Building (Review and preparation tips) Designing data processing systems Designing flexible data representations Designing data pipelines Designing data processing infrastructure Build and maintain data structures and databases Building and maintaining flexible data representations Building and maintaining pipelines Building and maintaining processing infrastructure Analyzing and Modeling (Review and preparation tips) Analyze data and enable machine learning Analyzing data Machine learning Machine learning model deployment Model business processes for analysis and optimization Mapping business requirements to data representations Optimizing data representations, data infrastructure performance and cost Reliability, Policy, and Security (Review and preparation tips) Design for reliability Performing quality control Assessing, troubleshooting, and improving data representation and data processing infrastructure Recovering data Visualize data and advocate policy Building (or selecting) data visualization and reporting tools Advocating policies and publishing data and reports Design for security and compliance Designing secure data infrastructure and processes Designing for legal compliance Resources and next steps Resources for learning more about designing data processing systems, data structures, and databases Resources for learning more about data analysis, machine learning, business process analysis, and optimization Resources for learning more about data visualization and policy Resources for learning more about reliability design Resources for learning more about business process analysis and optimization Resources for learning more about reliability, policies, security, and compliance Additional course details: Nexus Humans Preparing for the Professional Data Engineer Examination 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 Preparing for the Professional Data Engineer Examination 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 From Playgrounds to protocols?discover, explore, and demonstrate how to use the fundamental building blocks of the Swift programming language. This 2-day, hands-on course teaches you the basic concepts of Swift programming, including syntax, logic, structures, functions, and patterns. It also includes detailed explanations of language syntax and coding exercises Introduction to Swift and Playgrounds Learn about the origin of Swift and some of its basic syntax Constants, Variables, and Data Types Learn how to define constants for values that don?t change and variables for values that do. Learn the data types that are included in Swift and how they can help you write better code Operators Learn about some of the operators in the Swift language, including basic math operators. Control Flow Learn how to use logical operators in Swift to check conditions; learn how to use control flow statements. Strings Learn how to create and store text using the string type. You'll learn a variety of string methods that allow you to compare two strings, access specific characters within a string, and insert and remove values Functions Learn how to declare functions with different parameters and return types Structures Learn how to create structures in Swift. Classes Learn what makes classes different from structures and when to use classes instead of structures. Also learn about inheritance, superclasses, and subclasses. Optionals Learn to use ?optionals? to properly handle situations when data may or may not exist Collections Learn about the various collection types available in Swift and how to choose the appropriate one for your program. Loops Learn how to create loops in Swift, control the conditions for looping, and specify when to stop. Type Casting Learn why some data can be expressed using only a broader type, and how you can test for specific kinds of data before using it. Guard Learn to use guard statements to better manage control flow. Scope Learn to write nicely structured code that's easy to read. You'll do this by properly scoping your constants and variables Enumerations Learn when enumerations are commonly used, how to define an enumeration, and how to work with enumerations using switch statements. Protocols Learn what protocols are, when to use them, and how to write your own. Learn how to enable objects to communicate with each other and how to extend protocols to provide shared functionality across multiple types Closures Learn about closures, how to define them, how to use them as function arguments, and how to use some of the common functions that take closures as arguments. Extensions Learn how to define an extension, as well as how and why to use extensions. Additional course details: Nexus Humans Introduction to Swift 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 Introduction to Swift 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 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions
Duration 5 Days 30 CPD hours This course is intended for To fully benefit from this course, you should have three to five years of experience designing and implementing applications that are built on top of Cisco platforms. This course is appropriate for: Network engineers expanding their skill-base to include software and automation Developers expanding expertise in automation and DevOps Solution architects moving to the Cisco ecosystem Infrastructure developers designing hardened production environments The job roles best suited to the material in this course are: Senior network automation engineer Senior software developer Senior system integration programmer Additional job roles that could find this course useful are: Senior infrastructure architect Senior network designer Senior test development engineer Students preparing for Cisco Certified DevNet Professional and Cisco Certified DevNet Specialist - Core certification will also find this material useful. Overview After taking this course, you should be able to: Describe the architectural traits and patterns that improve application maintainability Describe the architectural traits and patterns that improve application serviceability Identify steps to design and build a ChatOps application Implement robust Representational State Transfer (REST) API integrations with network error handling, pagination, and error flow control Describe the necessary steps for securing user and system data in applications Describe the necessary steps for securing applications Identify common tasks in automated application release process Describe best practices for application deployment Describe methodologies for designing distributed systems Describe the concepts of infrastructure configuration management and device automation Utilize Yet Another Next Generation (YANG) data models to describe network configurations and telemetry Compare various relational and nonrelational database types and how to select the appropriate type based on requirements In this course, you will learn how to implement network applications using Cisco© platforms as a base, from initial software design to diverse system integration, as well as testing and deployment automation. The course gives you hands-on experience solving real world problems using Cisco Application Programming Interfaces (APIs) and modern development tools. This course helps you prepare for Cisco DevNet Professional certification and for professional-level network automation engineer roles. COURSE OUTLINE DESIGNING FOR MAINTAINABILITY (SELF-STUDY) DESIGNING FOR SERVICEABILITY (SELF-STUDY) IMPLEMENTING CHATOPS APPLICATION DESCRIBING ADVANCED REST API INTEGRATION SECURING APPLICATION DATA (SELF-STUDY) SECURING WEB AND MOBILE APPLICATIONS (SELF-STUDY) AUTOMATING APPLICATION-RELEASE DEPLOYING APPLICATIONS UNDERSTANDING DISTRIBUTED SYSTEMS ORCHESTRATING NETWORK AND INFRASTRUCTURE MODELING DATA WITH YANG USING RELATIONAL AND NON-RELATIONAL DATABASES (SELF-STUDY) PLEASE NOTE:This class includes lecture sections and self-study sections. In instructor-led classes, lectures are delivered in real-time, either in person or via video conferencing. In e-learning courses, the lectures are on recorded videos. In both versions, you will need to review self-study sections on your own before taking the certification exam. Additional course details: Nexus Humans Cisco Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 Cisco Developing Applications Using Cisco Core Platforms and APIs v1.0 (DEVCOR) 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 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline 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 The Machine Learning Pipeline 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.
Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions
Duration 2 Days 12 CPD hours This course is intended for This course is recommended for technical professionals who automate, orchestrate, and troubleshoot Check Point secured environments. Overview Explain how automation and orchestration work together Understand the key drivers for incorporating automation and orchestration into security management Execute a shell script that demonstrates how to build a comprehensive Security Policy. Recognize how the Check Point API framework integrates with R80 Security Management to support automation and orchestration of daily tasks Describe Check Point API tools and demonstrate how they are used to manage Check Point Security Management solutions Demonstrate how to define new objects and modify existing ones by using the Check Point API The goal of this course is to provide an understanding of the advanced concepts and skills necessary to automate and orchestrate tasks relating to managing Check Point Security Policies Course Ouline Explain how automation and orchestration work together Understand the key drivers for incorporating automation and orchestration into security management Execute a shell script that demonstrates how to build a comprehensive Security Policy. Recognize how the Check Point API framework integrates with R80 Security Management to support automation and orchestration of daily tasks Describe Check Point API tools and demonstrate how they are used to manage Check Point Security Management solutions Demonstrate how to define new objects and modify existing ones by using the Check Point API Demonstrate how to create API commands to efficiently maintain the Check Point Security Management Server database Demonstrate how to use different methods to update the database with API commands Become familiar with client-side and server-side scripting and scripting languages Understand how to use the Bash shell to develop APIs Recognize and describe many of the open source tools that are available to assist with API development Demonstrate how to use a custom REST application to update the database of a Security Management Server Demonstrate how to use Postman to manage the Security Policy database through the Check Point API Understand what steps to take to troubleshoot and debug API scripts Demonstrate basic troubleshooting techniques by reviewing debugging messages in various forms Understand how to use self-service portal capabilities to provide general IT services Recognize how automation tools work with Check Point APIs to automate security management tasks and orchestrate workflow behind service portals Demonstrate common tasks that are automated in a Web portal to manage the Security Policy LAB Exercises Demonstrate Check Point automation and orchestration Manage objects using the Check Point API Create a management API shell script Use a variety of methods to execute API commands Use a custom REST tool for API calls Use Postman for API calls Debug the Check Point management API Automate tasks using a Check Point API enabled Web portal Additional course details: Nexus Humans CCAS Check Point Certified Automation Specialist 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 CCAS Check Point Certified Automation Specialist 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.