43991 PE courses

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Those who will provide container orchestration management in the AWS Cloud including: DevOps engineers Systems administrators Overview In this course, you will learn to: Review and examine containers, Kubernetes and Amazon EKS fundamentals and the impact of containers on workflows. Build an Amazon EKS cluster by selecting the correct compute resources to support worker nodes. Secure your environment with AWS Identity and Access Management (IAM) authentication by creating an Amazon EKS service role for your cluster Deploy an application on the cluster. Publish container images to ECR and secure access via IAM policy. Automate and deploy applications, examine automation tools and pipelines. Create a GitOps pipeline using WeaveFlux. Collect monitoring data through metrics, logs, tracing with AWS X-Ray and identify metrics for performance tuning. Review scenarios where bottlenecks require the best scaling approach using horizontal or vertical scaling. Assess the tradeoffs between efficiency, resiliency, and cost and impact for tuning one over the other. Describe and outline a holistic, iterative approach to optimizing your environment. Design for cost, efficiency, and resiliency. Configure the AWS networking services to support the cluster. Describe how EKS/Amazon Virtual Private Cloud (VPC) functions and simplifies inter-node communications. Describe the function of VPC Container Network Interface (CNI). Review the benefits of a service mesh. Upgrade your Kubernetes, Amazon EKS, and third party tools Amazon EKS makes it easy for you to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. In this course, you will learn container management and orchestration for Kubernetes using Amazon EKS. You will build an Amazon EKS cluster, configure the environment, deploy the cluster, and then add applications to your cluster. You will manage container images using Amazon Elastic Container Registry (ECR) and learn how to automate application deployment. You will deploy applications using CI/CD tools. You will learn how to monitor and scale your environment by using metrics, logging, tracing, and horizontal/vertical scaling. You will learn how to design and manage a large container environment by designing for efficiency, cost, and resiliency. You will configure AWS networking services to support the cluster and learn how to secure your Amazon EKS environment. Module 0: Course Introduction Course preparation activities and agenda Module 1: Container Fundamentals Best practices for building applications Container fundamentals Components of a container Module 2: Kubernetes Fundamentals Container orchestration Kubernetes objects Kubernetes internals Preparing for Lab 1: Deploying Kubernetes Pods Module 3: Amazon EKS Fundamentals Introduction to Amazon EKS Amazon EKS control plane Amazon EKS data plane Fundamentals of Amazon EKS security Amazon EKS API Module 4: Building an Amazon EKS Cluster Configuring your environment Creating an Amazon EKS cluster Demo: Configuring and deploying clusters in the AWS Management Console Working with eksctl Preparing for Lab 2: Building an Amazon EKS Cluster Module 5: Deploying Applications to Your Amazon EKS Cluster Configuring Amazon Elastic Container Registry (Amazon ECR) Demo: Configuring Amazon ECR Deploying applications with Helm Demo: Deploying applications with Helm Continuous deployment in Amazon EKS GitOps and Amazon EKS Preparing for Lab 3: Deploying App Module 6: Configuring Observability in Amazon EKS Configuring observability in an Amazon EKS cluster Collecting metrics Using metrics for automatic scaling Managing logs Application tracing in Amazon EKS Gaining and applying insight from observability Preparing for Lab 4: Monitoring Amazon EKS Module 7: Balancing Efficiency, Resilience, and Cost Optimization in Amazon EKS The high level overview Designing for resilience Designing for cost optimization Designing for efficiency Module 8: Managing Networking in Amazon EKS Review: Networking in AWS Communicating in Amazon EKS Managing your IP space Deploying a service mesh Preparing for Lab 5: Exploring Amazon EKS Communication Module 9: Managing Authentication and Authorization in Amazon EKS Understanding the AWS shared responsibility model Authentication and authorization Managing IAM and RBAC Demo: Customizing RBAC roles Managing pod permissions using RBAC service accounts Module 10: Implementing Secure Workflows Securing cluster endpoint access Improving the security of your workflows Improving host and network security Managing secrets Preparing for Lab 6: Securing Amazon EKS Module 11: Managing Upgrades in Amazon EKS Planning for an upgrade Upgrading your Kubernetes version Amazon EKS platform versions Additional course details: Nexus Humans Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) 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 5 Days 30 CPD hours This course is intended for This introductory-level Python course is geared for experienced users who want to use Python in web development projects, or system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Basic familiarity with any programming or scripting language would be helpful, along with a working, user-level knowledge of Unix/Linux, Mac, or Windows. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to write essential Python scripts using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Create working Python scripts following best practices Use python data types appropriately Read and write files with both text and binary data Search and replace text with regular expressions Get familiar with the standard library and its work-saving modules Use lesser known but powerful Python data types Create 'real-world', professional Python applications Work with dates, times, and calendars Know when to use collections such as lists, dictionaries, and sets Understand Pythonic features such as comprehensions and iterators Write robust code using exception handling Mastering Python Programming is an introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar. Students will immediately be able to use Python to complete tasks in the real world. An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows Editors and IDEs Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Array types About array types (AKA sequences) Lists and list methods Tuples Indexing and slicing Iterating through a sequence Nested sequences Sequence functions, keywords, and operators List comprehensions Generator Expressions Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases An Introduction to Python Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings Using the Standard Library The sys module Launching external programs Math functions Random numbers Reading CSV data Dates and Times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the File System Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations Advanced Data Handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network Programming Using requests Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Reading input files a la Unix Parsing command-line options Detecting the current platform Implementing logging Additional course details: Nexus Humans Mastering Python Programming (TTPS4820) 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 Mastering Python Programming (TTPS4820) 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 security and network administrators who will be responsible for the installation, deployment, tuning, and day-to-day maintenance of the F5 Advanced Web Application Firewall. In this 4 day course, students are provided with a functional understanding of how to deploy, tune, and operate F5 Advanced Web Application Firewall to protect their web applications from HTTP-based attacks. The course includes lecture, hands-on labs, and discussion about different F5 Advanced Web Application Firewall tools for detecting and mitigating threats from multiple attack vectors such web scraping, Layer 7 Denial of Service, brute force, bots, code injection, and zero day exploits. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Leveraging F5 Support Resources and Tools Module 2: Traffic Processing with BIG-IP Identifying BIG-IP Traffic Processing Objects Overview of Network Packet Flow Understanding Profiles Overview of Local Traffic Policies Visualizing the HTTP Request Flow Module 3: Web Application Concepts Overview of Web Application Request Processing Web Application Firewall: Layer 7 Protection F5 Advanced WAF Layer 7 Security Checks Overview of Web Communication Elements Overview of the HTTP Request Structure Examining HTTP Responses How F5 Advanced WAF Parses File Types, URLs, and Parameters Using the Fiddler HTTP Proxy Module 4: Common Web Application Vulnerabilities A Taxonomy of Attacks: The Threat Landscape What Elements of Application Delivery are Targeted? Common Exploits Against Web Applications Module 5: Security Policy Deployment Defining Learning Comparing Positive and Negative Security Models The Deployment Workflow Policy Type: How Will the Policy Be Applied Policy Template: Determines the Level of Protection Policy Templates: Automatic or Manual Policy Building Assigning Policy to Virtual Server Deployment Workflow: Using Advanced Settings Selecting the Enforcement Mode The Importance of Application Language Configure Server Technologies Verify Attack Signature Staging Viewing Requests Security Checks Offered by Rapid Deployment Defining Attack Signatures Using Data Guard to Check Responses Module 6: Policy Tuning and Violations Post-Deployment Traffic Processing Defining Violations Defining False Positives How Violations are Categorized Violation Rating: A Threat Scale Defining Staging and Enforcement Defining Enforcement Mode Defining the Enforcement Readiness Period Reviewing the Definition of Learning Defining Learning Suggestions Choosing Automatic or Manual Learning Defining the Learn, Alarm and Block Settings Interpreting the Enforcement Readiness Summary Configuring the Blocking Response Page Module 7: Attack Signatures & Threat Campaigns Defining Attack Signatures Attack Signature Basics Creating User-Defined Attack Signatures Defining Simple and Advanced Edit Modes Defining Attack Signature Sets Defining Attack Signature Pools Understanding Attack Signatures and Staging Updating Attack Signatures Defining Threat Campaigns Deploying Threat Campaigns Module 8: Positive Security Policy Building Defining and Learning Security Policy Components Defining the Wildcard Defining the Entity Lifecycle Choosing the Learning Scheme How to Learn: Never (Wildcard Only) How to Learn: Always How to Learn: Selective Reviewing the Enforcement Readiness Period: Entities Viewing Learning Suggestions and Staging Status Violations Without Learning Suggestions Defining the Learning Score Defining Trusted and Untrusted IP Addresses How to Learn: Compact Module 9: Cookies and Other Headers F5 Advanced WAF Cookies: What to Enforce Defining Allowed and Enforced Cookies Configuring Security Processing on HTTP headers Module 10: Reporting and Logging Overview: Big Picture Data Reporting: Build Your Own View Reporting: Chart based on filters Brute Force and Web Scraping Statistics Viewing F5 Advanced WAF Resource Reports PCI Compliance: PCI-DSS 3.0 The Attack Expert System Viewing Traffic Learning Graphs Local Logging Facilities and Destinations How to Enable Local Logging of Security Events Viewing Logs in the Configuration Utility Exporting Requests Logging Profiles: Build What You Need Configuring Response Logging Module 11: Lab Project 1 Lab Project 1 Module 12: Advanced Parameter Handling Defining Parameter Types Defining Static Parameters Defining Dynamic Parameters Defining Dynamic Parameter Extraction Properties Defining Parameter Levels Other Parameter Considerations Module 13: Automatic Policy Building Overview of Automatic Policy Building Defining Templates Which Automate Learning Defining Policy Loosening Defining Policy Tightening Defining Learning Speed: Traffic Sampling Defining Track Site Changes Lesson 14: Web Application Vulnerability Scanner Integration Integrating Scanner Output Importing Vulnerabilities Resolving Vulnerabilities Using the Generic XML Scanner XSD file Lesson 15: Deploying Layered Policies Defining a Parent Policy Defining Inheritance Parent Policy Deployment Use Cases Lesson 16: Login Enforcement and Brute Force Mitigation Defining Login Pages for Flow Control Configuring Automatic Detection of Login Pages Defining Session Tracking Brute Force Protection Configuration Source-Based Brute Force Mitigations Defining Credentials Stuffing Mitigating Credentials Stuffing Lesson 17: Reconnaissance with Session Tracking Defining Session Tracking Configuring Actions Upon Violation Detection Lesson 18: Layer 7 DoS Mitigation Defining Denial of Service Attacks Defining the DoS Protection Profile Overview of TPS-based DoS Protection Creating a DoS Logging Profile Applying TPS Mitigations Defining Behavioral and Stress-Based Detection Lesson 19: Advanced Bot Protection Classifying Clients with the Bot Defense Profile Defining Bot Signatures Defining Proactive Bot Defense Defining Behavioral and Stress-Based Detection Defining Behavioral DoS Mitigation Lesson 20: Form Encryption using DataSafe Targeting Elements of Application Delivery Exploiting the Document Object Model Protecting Applications Using DataSafe The Order of Operations for URL Classification Lesson 21: Review and Final Labs Review and Final Labs

Duration 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient, maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects, adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples Additional course details: Nexus Humans Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 Fast Track to Scala Programming Essentials for OO / Java Developers (TTSCL2104) 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 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.

Duration 5 Days 30 CPD hours This course is intended for This introductory-level, fast-paced course is for skilled web developers new to React who have prior experienced working HTML5, CSS3 and JavaScript. Overview Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore: A basic and advanced understanding of React components An advanced, in-depth knowledge of how React works A complete understanding of using Redux How to build, validate, and populate interactive forms How to use inline styles for perfect looking components How to test React components How to build and use components How to get control of your build process A deep understanding of data-driven modeling with props and state How to use client-side routing for pages in your apps How to debug a React application Mastering React is a comprehensive hands-on course that aims to be the single most useful resource on getting up to speed quickly with React. Geared for more experienced web developers new to React, this course provides students with the core knowledge and hands-on skills they require to build reliable, powerful React apps. After the first few modules, you?ll have a solid understanding of React?s fundamentals and will be able to build a wide array of rich, interactive web apps with the framework. The first module is an introduction to the new functionality in ECMAScript 6 (JavaScript). Client-side routing between pages, managing complex state, and heavy API interaction at scale are also covered. This course consists of two parts. In the first part of the course students will explore all the fundamentals with a progressive, example-driven approach. You?ll create your first apps, learn how to write components, start handling user interaction, and manage rich forms. We end the first part by exploring the inner workings of Create React App (Facebook?s tool for running React apps), writing automated unit tests, and building a multi-page app that uses client-side routing. The latter part of the course moves into more advanced concepts that you?ll see used in large, production applications. These concepts explore strategies for data architecture, transport, and management: Redux is a state management paradigm based on the Flux architecture. Redux provides a structure for large state trees and allows you to decouple user interaction in your app from state changes. GraphQL is a powerful, typed, REST API alternative where the client describes the data it needs. Hooks is the powerful, new way to maintain state and properties with functional components and the future of React according to Facebook. ES6 Primer (Optional) Prefer const and let over var Arrow functions Modules Object.assign() Template literals The spread operator and Rest parameters Enhanced object literals Default arguments Destructuring assignments Your first React Web Application Setting up your development environment JavaScript ES6 /ES7 Getting started What?s a component? Our first component Building the App Making the App data-driven Your app?s first interaction Updating state and immutability Refactoring with the Babel plugin transform-class-properties JSX and the Virtual DOM React Uses a Virtual DOM Why Not Modify the Actual DOM? What is a Virtual DOM? Virtual DOM Pieces ReactElement JSX JSX Creates Elements JSX Attribute Expressions JSX Conditional Child Expressions JSX Boolean Attributes JSX Comments JSX Spread Syntax JSX Gotchas JSX Summary Components A time-logging app Getting started Breaking the app into components The steps for building React apps from scratch Updating timers Deleting timers Adding timing functionality Add start and stop functionality Methodology review Advanced Component Configuration with props, state, and children ReactComponent props are the parameters PropTypes Default props with getDefaultProps() context state Stateless Components Talking to Children Components with props.children Forms Forms 101 Text Input Remote Data Async Persistence Redux Form Modules Unit Testing & Jest Writing tests without a framework What is Jest? Using Jest Testing strategies for React applications Testing a basic React component with Enzyme Writing tests for the food lookup app Writing FoodSearch.test.js Routing What?s in a URL? React Router?s core components Building the components of react-router Dynamic routing with React Router Supporting authenticated routes Intro to Flux and Redux Why Flux? Flux is a Design Pattern Flux implementations Redux & Redux?s key ideas Building a counter The core of Redux The beginnings of a chat app Building the reducer() Subscribing to the store Connecting Redux to React Intermediate Redux Using createStore() from the redux library Representing messages as objects in state Introducing threads Adding the ThreadTabs component Supporting threads in the reducer Adding the action OPEN_THREAD Breaking up the reducer function Adding messagesReducer() Defining the initial state in the reducers Using combineReducers() from redux React Hooks Motivation behind Hooks How Hooks Map to Component Classes Using Hooks Requires react 'next' useState() Hook Example useEffect() Hook Example useContext() Hook Example Using Custom Hooks Using Webpack with Create React App JavaScript modules Create React App Exploring Create React App Webpack basics Making modifications Hot reloading; Auto-reloading Creating a production build Ejecting Using Create React App with an API server When to use Webpack/Create React App Using GraphQL Your First GraphQL Query GraphQL Benefits GraphQL vs. REST GraphQL vs. SQL Relay and GraphQL Frameworks Chapter Preview Consuming GraphQL Exploring With GraphiQL GraphQL Syntax 101 . Complex Types Exploring a Graph Graph Nodes ; Viewer Graph Connections and Edges Mutations Subscriptions GraphQL With JavaScript GraphQL With React

Duration 5 Days 30 CPD hours Overview Upon completing this course, you will be able to meet the following objectives: SD-WAN Overview Cloud Concepts Cloud Technologies SD-WAN Direct Cloud Access (DCA) SD-WAN SaaS Cloud On-RAMP for IAAS (AWS) Cloud On-RAMP for IAAS (AZURE) Cloud Configuration for GCP Cloud On-RAMP for MULTI-CLOUD Cloud On-RAMP for CO-LOCATIONS This is a 5 day hands-on course on Cisco SD-WAN Cloud Configuration, Monitoring and Troubleshooting. This course provides the student with the knowledge to connect SD-WAN to SaaS Applications, as well as the ability to connect their Branches to AWS, AZURE, GCP Data Centers in the Cloud. Students will also learn how to Configure, Monitor, and Troubleshoot SD-WAN Co-Locations and SD-WAN Multicloud. SD-WAN Overview SD-WAN Controller SD-WAN WAN Edges supported in Cloud Instances Cloud Concepts Cloud Ops vs WAN Ops Cloud Connectivity Cloud Access Control Cloud Network Connectivity Cloud Regions Cloud Availability Zones Virtual Networks Cloud Routing Internet Gateways VS VPN Gateways VPC/VNET: IP Addressing Cloud Network Load Balancing Cloud Peering Cloud Transit Networks Cloud Technologies Azure Azure Basics Resource Groups vNets Availability zones Availability Set Workload and Public IP Network Virtual Appliance Load Balancer User Defined Routes Network Security Group VPN Gateway Express Routes Creating VNET for SDWAN AWS AWS Basics Region VPCs Availability zones Subnets EC2 Instance Elastic IPs Security Groups Internet Gateway NAT Gateway Route Table VPN Gateway Direct Connect Elastic Load Balancer Subscribe to Amazon machine images Setting AWS resource limits AWS Transit Gateways Creating VPC for SDWAN AWS IAM Role AWS Security Groups Service limits AWS SSH key pair Google Cloud GCP Basics Project Region Virtual Private Cloud Availability Zone Subnets Compute Engine Cloud Load Balancer Cloud DNS VPC Routing Cloud VPN & VPC peering VPC Firewall Rules SD-WAN Direct Cloud Access (DCA) DCA Prerequisites DNS on VPN 0 DIA Central Policy Configuration Match Traffic Set QOS Set External Access SD-WAN SaaS Supported Platforms and Versions SaaS Prerequisites DNS on VPN 0 DIA SaaS Access Methods Cloud Access through Direct Internet Access Links Cloud Access through a Gateway Site Hybrid Approach Supported SaaS Applications SaaS Security Options SaaS Configuration Common Scenarios for Using Cloud onRamp for SaaS Specify Office 365 Traffic Category Enable Cloud onRamp for SaaS, Cisco IOS XE SD-WAN Devices Configure Applications for Cloud onRamp for SaaS Using Cisco vManage Configure Sites for Cloud onRamp for SaaS Using Cisco vManage View Details of Monitored Applications Cloud On-RAMP for IAAS (AWS) Prerequisite AWS Configuration Verify prerequisites Configure AWS for Cisco SD-WAN Cloud On-RAMP for AWS Overview Define WAN Edge Type used Define Template Attach Devices to Template Deploy Cloud Onramp AWS IAM Role Select Region Select CPU and Memory Transit Networking IP Addresses Discover and Map Host VPCs AWS to SD-WAN Security Monitor Cisco Cloud Onramp for AWS Troubleshoot Cisco Cloud Onramp for AWS Interconnecting Cisco SD-WAN with AWS Transit Gateway (TGW) Cloud On-RAMP for IAAS (AZURE) Prerequisite AZURE Configuration Cloud On-RAMP for AZURE Configure AWS for Cisco SD-WAN Define WAN Edge Type used Define Template Attach Devices to Template Deploy Cloud Onramp Select Region Discover and Map Host VPCs Monitor Cisco Cloud Onramp for Azure Troubleshoot Cisco Cloud Onramp for AZURE Azure Virtual Wan (VWAN) Integration Cloud Configuration for GCP Prerequisite GCP Configuration SD-WAN Configuration Configure Google Cloud for SD-WAN Google Cloud GCP Basics Deploy cEdge Catalyst 8000V Edges Setup IPSEC Connections Setup BGP Connections Cloud On-RAMP for MULTI-CLOUD AWS Transit Gateway Microsoft vWAN Create Cisco Cloud GW Discover host VPCs/VNets Map Branch nets to VPCs Cloud On-RAMP for CO-LOCATIONS SD-WAN CO-LOCATIONS Overview Colocation facilities Cisco Colocation Equipment Cisco Cloud Services Platform 5444 Cisco Network Function Virtualization Infrastructure Software (NFVIS) Virtual Network Functions Network Fabric Cisco Catalyst 9500-48Y4C switch Cisco Catalyst 9500-40X switch Device Configuration and Connectivity Sizing the Colocation Solution Devices Cisco Colocation Manager Deploy Network Services at the Network Edge Colocation Solution?Deployment Workflow Monitor Cisco SD-WAN Colocation Devices Cisco Colocation Manager States for Switch Configuration Cisco Colocation Manager States and Transitions from Host Cisco Colocation Manager Notifications VM Alarms Cloud Services Platform Real-Time Commands Colocation High Availability Troubleshoot Cisco SD-WAN Cloud onRamp for Colocation Solution Troubleshoot Catalyst 9500 Issues Troubleshoot Cloud Services Platform Issues DHCP IP Address Assignment Troubleshoot Cisco Colo Manager Issues Troubleshoot Service Chain Issues Troubleshoot Physical Network Function Management Issues Log Collection from CSP Troubleshoot vManage Issues Additional course details: Nexus Humans Cisco SD-WAN Cloud (SDWAN-CLD-CT) 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 SD-WAN Cloud (SDWAN-CLD-CT) 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 4.375 Days 26.25 CPD hours This course is intended for The target audience for this course is all Oracle professionals. Among the specific groups for whom this course will be helpful are: Application designers and database developers Database administrators Web server administrators Overview This eTextbook begins with an explanation of the intent and usage of the PL/SQL programming language for database applications. Important reasons why one should incorporate PL/SQL modules within the application architecture right from the initial design and planning phase are presented. Next one learns how to begin building executable PL/SQL program units. One learns about each of the major segments of a working program and how these interact with each other during program execution, including the important error or exception handling capabilities of the language. The final section goes beyond the basics and begins to explore advanced topics that will be useful later in the Sideris Oracle PL/SQL developer textbook series. One learns techniques and features that allow modular and reusable programs to be developed, increasing productivity and maintainability of database applications. his eTextbook introduces one to Oracle database programming using the PL/SQL programming language. One will learn the syntax, structure and features of the language. This textbook will also lay the foundation for the entire Sideris Oracle PL/SQL programming series, allowing one to progress from introductory topics to advanced application design and programming and finally onto writing complex high-performance applications. his eTextbook introduces one to Oracle database programming using the PL/SQL programming language. One will learn the syntax, structure and features of the language. This textbook will also lay the foundation for the entire Sideris Oracle PL/SQL programming series, allowing one to progress from introductory topics to advanced application design and programming and finally onto writing complex high-performance applications.

Duration 4 Days 24 CPD hours This course is intended for This is an introductory-level C++ programming course designed for developers with experience programming in C or other languages. Practical hands-on prior programming experience and knowledge is required. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in basic coding with C++, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn: Writing procedural programs using C++ Using private, public and protected keywords to control access to class members Defining a class in C++ Writing constructors and destructors Writing classes with const and static class members Overloading operators Implementing polymorphic methods in programs Writing programs using file I/O and string streams Using manipulators and stream flags to format output Using the keyword template to write generic functions and classes Writing programs that use generic classes and functions Writing programs that use algorithms and containers of the Standard Library Apply object-oriented design techniques to real-world programming problems Using algorithms and containers of the Standard Library to manipulate string data Understand how C++ protects the programmer from implementation changes in other modules of an application Using try() blocks to trap exceptions Using catch() blocks to handle exceptions Defining exceptions and using throw to trigger them Introduction to C++ Programming / C++ Essentials is a skills-focused, hands-on C++ training course geared for experienced programmers who need to learn C++ coupled with sounds coding skills and best practices for OO development. Students will leave this course armed with the required skills to put foundation-level C++ programming skills right to work in a practical environment. The central concepts of C++ syntax and style are taught in the context of using object-oriented methods to achieve reusability, adaptability and reliability. Emphasis is placed on the features of C++ that support abstract data types, inheritance, and polymorphism. Students will learn to apply the process of data abstraction and class design. Practical aspects of C++ programming including efficiency, performance, testing, and reliability considerations are stressed throughout. Comprehensive hands on exercises are integrated throughout to reinforce learning and develop real competency Moving from C to C++ (Optional) New Compiler Directives Stream Console I/O Explicit Operators Standard Libraries Data Control Capabilities Handling Data New Declaration Features Initialization and Assignment Enumerated Types The bool Type Constant Storage Pointers to Constant Storage Constant Pointers References Constant Reference Arguments Volatile Data Global Data Functions Function Prototypes and Type Checking Default Function Data Types Function Overloading Problems with Function Overloading Name Resolution Promotions and Conversions Call by Value Reference Declarations Call-by-Reference and Reference Types References in Function Return Constant Argument Types Conversion of Parameters Using Default Initializers Providing Default Arguments Inline Functions Operator Overloading Advantages and Pitfalls of Overloading Member Operator Syntax and Examples Class Assignment Operators Class Equality Operators Non-Member Operator Overloading Member and Non-Member Operator Functions Operator Precedence This Pointer Overloading the Assignment Operator Overloading Caveats Creating and Using Objects Creating Automatic Objects Creating Dynamic Objects Calling Object Methods Constructors Initializing Member consts Initializer List Syntax Allocating Resources in Constructor Destructors Block and Function Scope File and Global Scope Class Scope Scope Resolution Operator :: Using Objects as Arguments Objects as Function Return Values Constant Methods Containment Relationships Dynamic Memory Management Advantages of Dynamic Memory Allocation Static, Automatic, and Heap Memory Free Store Allocation with new and delete Handling Memory Allocation Errors Controlling Object Creation Object Copying and Copy Constructor Automatic Copy Constructor Conversion Constructor Streaming I/O Streams and the iostream Library Built-in Stream Objects Stream Manipulators Stream Methods Input/Output Operators Character Input String Streams Formatted I/O File Stream I/O Overloading Stream Operators Persistent Objects Introduction to Object Concepts The Object Programming Paradigm Object-Orientated Programming Definitions Information Hiding and Encapsulation Separating Interface and Implementation Classes and Instances of Objects Overloaded Objects and Polymorphism Declaring and Defining Classes Components of a Class Class Structure Class Declaration Syntax Member Data Built-in Operations Constructors and Initialization Initialization vs. Assignment Class Type Members Member Functions and Member Accessibility Inline Member Functions Friend Functions Static Members Modifying Access with a Friend Class Templates Purpose of Template Classes Constants in Templates Templates and Inheritance Container Classes Use of Libraries Strings in C++ Character Strings The String Class Operators on Strings Member Functions of the String Class Inheritance Inheritance and Reuse Composition vs. Inheritance Inheritance: Centralized Code Inheritance: Maintenance and Revision Public, Private and Protected Members Redefining Behavior in Derived Classes Designing Extensible Software Systems Syntax for Public Inheritance Use of Common Pointers Constructors and Initialization Inherited Copy Constructors Destructors and Inheritance Public, Protected, Private Inheritance Exceptions Types of Exceptions Trapping and Handling Exceptions Triggering Exceptions Handling Memory Allocation Errors C++ Program Structure Organizing C++ Source Files Integrating C and C++ Projects Using C in C++ Reliability Considerations in C++ Projects Function Prototypes Strong Type Checking Constant Types C++ Access Control Techniques Polymorphism in C++ Definition of Polymorphism Calling Overridden Methods Upcasting Accessing Overridden Methods Virtual Methods and Dynamic Binding Virtual Destructors Abstract Base Classes and Pure Virtual Methods Multiple Inheritance Derivation from Multiple Base Classes Base Class Ambiguities Virtual Inheritance Virtual Base Classes Virtual Base Class Information The Standard Template Library STL Containers Parameters Used in Container Classes The Vector Class STL Algorithms Use of Libraries

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies