442 Algorithm courses

Duration 5 Days 30 CPD hours This course is intended for This basic course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of Java and object-oriented programming concepts. Attendees might include: Technically-minded attendees who want or who want to begin the process of becoming an OO application developer Technical team members from non-development roles, re-skilling to move into software and application development roles within an organization Recent college graduates looking to apply their college experience to programming skills in a professional environment, or perhaps needing to learn the best practices and standards for programming within their new organization Technical managers tasked with overseeing programming teams, or development projects, where basic coding knowledge and exposure will be useful in project oversight or communications needs Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in basic coding with Java, 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: The steps involved in the creation and deployment of a computer program What OO programming is and what the advantages of OO are in today's world To work with objects, classes, and OO implementations The basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction The basic constructs that all programming languages share The basic Java constructs supporting processing as well as the OO orientation How to use Java exception handling About and how to use classes, inheritance and polymorphism About use collections, generics, autoboxing, and enumerations How to take advantage of the Java tooling that is available with the programming environment being used in the class Getting Started with Programming, OO and Java Basics for Non-Developers is a skills-focused, hands-on coding course that teaches students the fundamentals of programming object oriented (OO) applications with Java to a basic level, using sound coding skills and best practices for OO development. This course is presented in a way that enables interested students to embrace the fundamentals of coding as well as an introduction to Java, in a gentle paced environment that focuses on coding basics.Students are introduced to the application development cycle, structure of programs, and specific language syntax. The course introduces important algorithmic constructs, string and character manipulation, dynamic memory allocation, standard I/O, and fundamental object-oriented programming concepts. The course explains the use of inheritance and polymorphism early on so the students can practice extensively in the hands-on labs. Structured programming techniques and error handling are emphasized. The course includes the processing of command line arguments and environment variables, so students will be able to write flexible, user-friendly programs. Students will leave this course armed with the required skills to begin their journey as a Java programmer using modern coding skills and technologies. Introduction to Computer Programming Introduction to Programming Programming Tools Programming Fundamentals Thinking About Objects Program Basics Programming Constructs Java: A First Look The Java Platform Using the JDK The Eclipse Paradigm Writing a Simple Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Getting Started with Java Adding Methods to the Class Language Statements Using Strings Specializing in a Subclass Essential Java Programming Fields and Variables Using Arrays Java Packages and Visibility Advanced Java Programming Inheritance and Polymorphism Interfaces and Abstract Classes Exceptions Java Developer's Toolbox Utility Classes Enumerations and Static Imports Formatting Strings Collections and Generics Introduction to Generics Collections

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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 Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Blockchain Architects Blockchain DevelopersApplication Developers Blockchain System AdministratorsNetwork Security Architects Cyber Security ExpertsIT Professionals w/cyber security experience Overview Those who attend the Security for Blockchain Professionals course and pass the exam certification will have a demonstrated knowledge of:Identifying and differentiating between security threats and attacks on a Blockchain network.Blockchain security methods, best practices, risk mitigation, and more.All known (to date) cyber-attack vectors on the Blockchain.Performing Blockchain network security risk analysis.A complete understanding of Blockchain?s inherent security features and risks.An excellent knowledge of best security practices for Blockchain System/Network Administrators.Demonstrating appropriate Blockchain data safeguarding techniques. This course covers all known aspects of Blockchain security that exist in the Blockchain environment today and provides a detailed overview of all Blockchain security issues, including threats, risk mitigation, node security integrity, confidentiality, best security practices, advanced Blockchain security and more. Fundamental Blockchain Security Cryptography for the Blockchain Hash Functions Public Key Cryptography Elliptic Curve Cryptography A Brief Introduction to Blockchain The Blocks The Chains The Network Promises of the Blockchain Blockchain Security Assumptions Digital Signature Security Hash Function Security Limitations of Basic Blockchain Security Public Key Cryptography Review Real-Life Public Key Protection Cryptography and Quantum Computers Lab 1 (Tentative) Finding Hash Function Collisions Reversible hash function Hash function with poor non-locality Hash function with small search space Breaking Public Key Cryptography Brute Forcing a Short Private Key Brute Forcing a Poorly-Chosen Private Key Consensus in the Blockchain Blockchain Consensus and Byzantine Generals Blockchain Networking Review Byzantine Generals Problem Relation to Blockchain Byzantine Fault Tolerance Introduction to Blockchain Consensus Security Blockchain Consensus Breakthrough Proof of Work What is Proof of Work? How does Proof of Work Solve BGP? Proof of Work Security Assumptions Attacking Proof of Work Proof of Stake What is Proof of Stake? How does Proof of Stake Solve BGP? Proof of Stake Security Assumptions Attacking Proof of Stake General Attacks on Blockchain Consensus Other Blockchain Consensus Algorithms Lab 2 (Tentative) Attacking Proof of Work Performing a 51% Attack Performing a Selfish Mining Attack Attacking Proof of Stake Performing a XX% Attack Performing a Long-Range Attack Malleable Transaction Attacks Advanced Blockchain Security Mechanisms Architectural Security Measures Permissioned Blockchains Checkpointing Advanced Cryptographic Solutions Multiparty Signatures Zero-Knowledge Proofs Stealth Addresses Ring Signatures Confidential Transactions Lab 3 (Tentative) Permissioned Blockchains 51% on a Checkpointed Blockchain Data mining on a blockchain with/without stealth addresses Zero-Knowledge Proof Simulation Trying to fake knowledge of a ZKP Module 4: Blockchain for Business Introduction to Ethereum Security What is Ethereum Consensus in Ethereum Smart Contracts in Ethereum Ethereum Security Pros and Cons of Ethereum Blockchains Introduction to Hyperledger Security What is Hyperledger Consensus in Hyperledger Smart Contracts in Hyperledger Hyperledger Security Pros and Cons of Hyperledger Blockchains Introduction to Corda Security What is Corda Consensus in Corda Smart Contracts in Corda Corda Security Pros and Cons of Corda Blockchains Lab 4 Blockchain Risk Assessment What are the Risks of the Blockchain? Information Security Information Sensitivity Data being placed on blockchain Risks of disclosure Regulatory Requirements Data encryption Data control PII protection Blockchain Architectural Design Public and Private Blockchains Open and Permissioned Blockchains Choosing a Blockchain Architecture Lab 5 Exploring public/private open/permissioned blockchains? Basic Blockchain Security Blockchain Architecture User Security Protecting Private Keys Malware Update Node Security Configuring MSPs Network Security Lab 6 (TBD) Smart Contract Security Introduction to Smart Contracts Smart Contract Security Considerations Turing-Complete Lifetime External Software Smart Contract Code Auditing Difficulties Techniques Tools Lab 7 (Tentative) Try a couple of smart contract code auditing tool against different contracts with built-in vulnerabilities Module 8: Security Implementing Business Blockchains Ethereum Best Practices Hyperledger Best Practices Corda Best Practices Lab 8 Network-Level Vulnerabilities and Attacks Introduction to Blockchain Network Attacks 51% Attacks Denial of Service Attacks Eclipse Attacks Routing Attacks Sybil Attacks Lab 9 Perform different network-level attacks System-Level Vulnerabilities and Attacks Introduction to Blockchain System Vulnerabilities The Bitcoin Hack The Verge Hack The EOS Vulnerability Lab 10 Smart Contract Vulnerabilities and Attacks Introduction to Common Smart Contract Vulnerabilities Reentrancy Access Control Arithmetic Unchecked Return Values Denial of Service Bad Randomness Race Conditions Timestamp Dependence Short Addresses Lab 11 Exploiting vulnerable smart contracts Security of Alternative DLT Architectures What Are Alternative DLT Architectures? Introduction to Directed Acyclic Graphs (DAGs) DAGs vs. Blockchains Advantages of DAGs DAG Vulnerabilities and Security Lab 12 Exploring a DAG network

Duration 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering

Duration 3 Days 18 CPD hours This course is intended for The ideal audience for the RPA and UiPath Boot Camp is beginners in the field of RPA and individuals in roles such as developers, project managers, operation analysts, and tech enthusiasts looking to familiarize themselves with automation technologies. It's also perfectly suited for business professionals keen on understanding and implementing automated solutions within their organizations to optimize processes. 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 Automation Learning expert instructor, students will explore: Gain a thorough understanding of Robotic Process Automation (RPA) and its applications using UiPath, setting a solid foundation for future learning and application. Learn to record and play in UiPath Studio, a key skill that enables automating complex tasks in a user-friendly environment. Master the art of designing and controlling workflows using Sequencing, Flowcharting, and Control Flow, helping to streamline and manage automation processes effectively. Acquire practical skills in data manipulation, from variable management to CSV/Excel and data table conversions, empowering you to handle data-rich tasks with confidence. Develop competence in managing controls and exploring various plugins and extensions, providing a broader toolkit for handling diverse automation projects. Get hands-on experience with exception handling, debugging, logging, code management, and bot deployment, fundamental skills that ensure your automated processes are reliable and efficient. How to deploy and control Bots with UiPath Orchestrator 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. What is Robotic Process Automation? Scope and techniques of automation Robotic process automation About UiPath The future of automation Record and Play UiPath stack Downloading and installing UiPath Studio Learning UiPath Studio Task recorder Step-by-step examples using the recorder Sequence, Flowchart, and Control Flow Sequencing the workflow Activities Control flow, various types of loops, and decision making Step-by-step example using Sequence and Flowchart Step-by-step example using Sequence and Control flow Data Manipulation Variables and scope Collections Arguments ? Purpose and use Data table usage with examples Clipboard management File operation with step-by-step example CSV/Excel to data table and vice versa (with a step-by-step example) Taking Control of the Controls Finding and attaching windows Finding the control Techniques for waiting for a control Act on controls ? mouse and keyboard activities Working with UiExplorer Handling events Revisit recorder Screen Scraping When to use OCR Types of OCR available How to use OCR Avoiding typical failure points Tame that Application with Plugins and Extensions Terminal plugin SAP automation Java plugin Citrix automation Mail plugin PDF plugin Web integration Excel and Word plugins Credential management Extensions ? Java, Chrome, Firefox, and Silverlight Handling User Events and Assistant Bots What are assistant bots? Monitoring system event triggers Monitoring image and element triggers Launching an assistant bot on a keyboard event Exception Handling, Debugging, and Logging Exception handling Common exceptions and ways to handle them Logging and taking screenshots Debugging techniques Collecting crash dumps Error reporting Managing and Maintaining the Code Project organization Nesting workflows Reusability of workflows Commenting techniques State Machine When to use Flowcharts, State Machines, or Sequences Using config files and examples of a config file Integrating a TFS server Deploying and Maintaining the Bot Publishing using publish utility Overview of Orchestration Server Using Orchestration Server to control bots Using Orchestration Server to deploy bots License management Publishing and managing updates

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators or network administrators, software and DevOps engineers Overview By the end of the course, you should be able to meet the following objectives: Describe VMware NSX Advanced Load Balancer architecture Describe VMware NSX Advanced Load Balancer components and main functions Explain VMware NSX Advanced Load Balancer key features and benefits Describe and leverage VMware NSX Advanced Load Balancer REST API Describe and leverage VMware NSX Advanced Load Balancer SDKs with extended focus on Python SDK Leverage REST API and SDK features and functions to provision application delivery components Describe and leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations Describe and leverage VMware NSX Advanced Load Balancer Github, Docker (avinetworks/avitools), Ansible Galaxy and other open source resources to accelerate the automation planning and implementation Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to provision infrastructure components Leverage VMware NSX Advanced Load Balancer Ansible and Terraform integrations to automate and streamline application delivery services provisioning This three-day, fast-paced course provides comprehensive training on how to automate infrastructure and application components of VMware NSX Advanced Load Balancer (Avi Networks) solution. This course covers key application delivery features of NSX Advanced Load Balancer (Avi Networks) features and functionality offered in VMware NSX Advanced Load Balancer 18.2 release and focuses on how to plan and implement automation of infrastructure and application components leveraging REST API, SDK or automation solutions such as Ansible, Terraform or similar. Access to a software-defined data center environment is provided through hands-on labs to reinforce the skills and concepts presented in the course. Course Introduction Introductions and course logistics Course objectives Introduction to NSX Advanced Load Balancer Introduce NSX Advanced Load Balancer Discuss NSX Advanced Load Balancer use cases, and benefits Explain NSX Advanced Load Balancer architecture and components Explain the management, control, data, and consumption planes and functions Virtual Services Configuration Concepts Explain Virtual Service components Explain Virtual Service types Explain and configure basic virtual services components such as Application Profiles, Network Profiles,Pools and Health Monitors Pools Configuration Concepts Explain and deep dive on Pool configuration options Describe multiple load balancing algorithms Explain multiple Health Monitor types Explain multiple Persistent profiles Explain and configure Pool Groups Leveraging NSX Advanced Load Balancer REST API Explain NSX Advanced Load Balancer automation vision Explain and introduce NSX Advanced Load Balancer REST API Describe NSX Advanced Load Balancer REST API methods and capabilities Describe NSX Advanced Load Balancer REST API session handling properties such authentication, API versioning and tenancy model Deep dive on NSX Advanced Load Balancer REST API Object Model Explain and investigate NSX Advanced Load Balancer REST API leveraging browser and command line utilities Explain and interact with NSX Advanced Load Balancer REST API leveraging browser, Postman and Curl Explain Swagger-based API Documentation Explain and leverage NSX Advanced Load Balancer Inventory API Explain and leverage NSX Advanced Load Balancer methods such as GET, PUT, POST and PATCH and associated queries, filters and parameters Deep dive on NSX Advanced Load Balancer PATCH method Explain and leverage NSX Advanced Load Balancer Analytics API Explain and leverage NSX Advanced Load Balancer MACRO API NSX Advanced Load Balancer Software-Defined Kits (SDKs) and ControlScripts Introduce NSX Advanced Load Balancer SDKs Describe, install and leverage NSX Advanced Load Balancer Python SDK Deep dive on NSX Advanced Load Balancer Python SDK Describe and leverage Golang SDK Leverage NSX Advanced Load Balancer open source resources such as Github, etc to accelerate SDKs adoption Describe NSX Advanced Load Balancer Events and Alerts framework Introduce ControlScripts foundations Leverage ControlScripts to automate configuration changes and alerts remediation Automating NSX Advanced Load Balancer Application Delivery Services with Ansible and Terraform Introduce NSX Advanced Load Balancer Configuration Orchestration and Management vision Introduce and explain Ansible foundations Describe Ansible and NSX Advanced Load Balancer Ansible capabilities Deep dive and implement NSX Advanced Load Balancer Ansible Core configuration modules (avinetworks/avisdk) Deep dive and implement Ansible NSX Advanced Load Balancer Declarative configuration role (avinetworks/aviconfig) Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Ansible playbooks Explain application delivery configuration automation approach and models Apply configuration automation models with Ansible Introduce and explain Terraform foundations Describe Terraform and NSX Advanced Load Balancer Terraform capabilities Deep dive and implement NSX Advanced Load Balancer Terraform Provider Leverage Swagger NSX Advanced Load Balancer REST API models to develop and implement Terraform plans Apply configuration automation models with Terraform Automating NSX Advanced Load Balancer Infrastructure with Ansible and Terraform Introduce NSX Advanced Load Balancer infrastructure Automation vision Describe infrastructure deployment approach and capabilities Describe Ansible and NSX Advanced Load Balancer Ansible Infrastructure deployment approach and capabilities Describe Terraform and NSX Advanced Load Balancer Terraform deployment approach and capabilities Leverage Terraform to deploy Controllers and perform system configuration, including control plane cluster setup Leverage Terraform to provision Cloud, Service Engine Groups and Service Engine components Describe and leverage Ansible roles to deploy Controllers and perform initial system configuration, including control plane cluster setup Leverage Ansible declarative and core roles to provision Cloud, Service Engine Groups and Service Engine components Describe and implement combined Terraform + Ansible model to streamline NSX Advanced Load Balancer solution deployment

Duration 5 Days 30 CPD hours This course is intended for Security engineer Network engineer Network designer Network administrator Systems engineer Consulting systems engineer Technical solutions architect Network manager Cisco integrators and partners Overview After taking this course, you should be able to: Describe information security concepts and strategies within the network Describe common TCP/IP, network application, and endpoint attacks Describe how various network security technologies work together to guard against attacks Implement access control on Cisco ASA appliance and Cisco Firepower Next-Generation Firewall Describe and implement basic email content security features and functions provided by Cisco Email Security Appliance Describe and implement web content security features and functions provided by Cisco Web Security Appliance Describe Cisco Umbrella security capabilities, deployment models, policy management, and Investigate console Introduce VPNs and describe cryptography solutions and algorithms Describe Cisco secure site-to-site connectivity solutions and explain how to deploy Cisco Internetwork Operating System (Cisco IOS) Virtual Tunnel Interface (VTI)-based point-to-point IPsec VPNs, and point-to-point IPsec VPN on the Cisco ASA and Cisco Firepower Next-Generation Firewall (NGFW) Describe and deploy Cisco secure remote access connectivity solutions and describe how to configure 802.1X and Extensible Authentication Protocol (EAP) authentication Provide basic understanding of endpoint security and describe Advanced Malware Protection (AMP) for Endpoints architecture and basic features Examine various defenses on Cisco devices that protect the control and management plane Configure and verify Cisco IOS software Layer 2 and Layer 3 data plane controls Describe Cisco Stealthwatch Enterprise and Stealthwatch Cloud solutions Describe basics of cloud computing and common cloud attacks and how to secure cloud environment The Implementing and Operating Cisco Security Core Technologies (SCOR) v1.0 course helps you prepare for the Cisco© CCNP© Security and CCIE© Security certifications and for senior-level security roles. In this course, you will master the skills and technologies you need to implement core Cisco security solutions to provide advanced threat protection against cybersecurity attacks. You will learn security for networks, cloud and content, endpoint protection, secure network access, visibility, and enforcements. You will get extensive hands-on experience deploying Cisco Firepower© Next-Generation Firewall and Cisco Adaptive Security Appliance (ASA) Firewall; configuring access control policies, mail policies, and 802.1X Authentication; and more. You will get introductory practice on Cisco Stealthwatch© Enterprise and Cisco Stealthwatch Cloud threat detection features. This course, including the self-paced material, helps prepare you to take the exam, Implementing and Operating Cisco Security Core Technologies (350-701 SCOR), which leads to the new CCNP Security, CCIE Security, and the Cisco Certified Specialist - Security Core certifications. Describing Information Security Concepts* Information Security Overview Assets, Vulnerabilities, and Countermeasures Managing Risk Vulnerability Assessment Understanding Common Vulnerability Scoring System (CVSS) Describing Common TCP/IP Attacks* Legacy TCP/IP Vulnerabilities IP Vulnerabilities Internet Control Message Protocol (ICMP) Vulnerabilities TCP Vulnerabilities User Datagram Protocol (UDP) Vulnerabilities Attack Surface and Attack Vectors Reconnaissance Attacks Access Attacks Man-in-the-Middle Attacks Denial of Service and Distributed Denial of Service Attacks Reflection and Amplification Attacks Spoofing Attacks Dynamic Host Configuration Protocol (DHCP) Attacks Describing Common Network Application Attacks* Password Attacks Domain Name System (DNS)-Based Attacks DNS Tunneling Web-Based Attacks HTTP 302 Cushioning Command Injections SQL Injections Cross-Site Scripting and Request Forgery Email-Based Attacks Describing Common Endpoint Attacks* Buffer Overflow Malware Reconnaissance Attack Gaining Access and Control Gaining Access via Social Engineering Gaining Access via Web-Based Attacks Exploit Kits and Rootkits Privilege Escalation Post-Exploitation Phase Angler Exploit Kit Describing Network Security Technologies Defense-in-Depth Strategy Defending Across the Attack Continuum Network Segmentation and Virtualization Overview Stateful Firewall Overview Security Intelligence Overview Threat Information Standardization Network-Based Malware Protection Overview Intrusion Prevention System (IPS) Overview Next Generation Firewall Overview Email Content Security Overview Web Content Security Overview Threat Analytic Systems Overview DNS Security Overview Authentication, Authorization, and Accounting Overview Identity and Access Management Overview Virtual Private Network Technology Overview Network Security Device Form Factors Overview Deploying Cisco ASA Firewall Cisco ASA Deployment Types Cisco ASA Interface Security Levels Cisco ASA Objects and Object Groups Network Address Translation Cisco ASA Interface Access Control Lists (ACLs) Cisco ASA Global ACLs Cisco ASA Advanced Access Policies Cisco ASA High Availability Overview Deploying Cisco Firepower Next-Generation Firewall Cisco Firepower NGFW Deployments Cisco Firepower NGFW Packet Processing and Policies Cisco Firepower NGFW Objects Cisco Firepower NGFW Network Address Translation (NAT) Cisco Firepower NGFW Prefilter Policies Cisco Firepower NGFW Access Control Policies Cisco Firepower NGFW Security Intelligence Cisco Firepower NGFW Discovery Policies Cisco Firepower NGFW IPS Policies Cisco Firepower NGFW Malware and File Policies Deploying Email Content Security Cisco Email Content Security Overview Simple Mail Transfer Protocol (SMTP) Overview Email Pipeline Overview Public and Private Listeners Host Access Table Overview Recipient Access Table Overview Mail Policies Overview Protection Against Spam and Graymail Anti-virus and Anti-malware Protection Outbreak Filters Content Filters Data Loss Prevention Email Encryption Deploying Web Content Security Cisco Web Security Appliance (WSA) Overview Deployment Options Network Users Authentication Secure HTTP (HTTPS) Traffic Decryption Access Policies and Identification Profiles Acceptable Use Controls Settings Anti-Malware Protection Deploying Cisco Umbrella* Cisco Umbrella Architecture Deploying Cisco Umbrella Cisco Umbrella Roaming Client Managing Cisco Umbrella Cisco Umbrella Investigate Overview and Concepts Explaining VPN Technologies and Cryptography VPN Definition VPN Types Secure Communication and Cryptographic Services Keys in Cryptography Public Key Infrastructure Introducing Cisco Secure Site-to-Site VPN Solutions Site-to-Site VPN Topologies IPsec VPN Overview IPsec Static Crypto Maps IPsec Static Virtual Tunnel Interface Dynamic Multipoint VPN Cisco IOS FlexVPN Deploying Cisco IOS VTI-Based Point-to-Point IPsec VPNs Cisco IOS VTIs Static VTI Point-to-Point IPsec Internet Key Exchange (IKE) v2 VPN Configuration Deploying Point-to-Point IPsec VPNs on the Cisco ASA and Cisco Firepower NGFW Point-to-Point VPNs on the Cisco ASA and Cisco Firepower NGFW Cisco ASA Point-to-Point VPN Configuration Cisco Firepower NGFW Point-to-Point VPN Configuration Introducing Cisco Secure Remote Access VPN Solutions Remote Access VPN Components Remote Access VPN Technologies Secure Sockets Layer (SSL) Overview Deploying Remote Access SSL VPNs on the Cisco ASA and Cisco Firepower NGFW Remote Access Configuration Concepts Connection Profiles Group Policies Cisco ASA Remote Access VPN Configuration Cisco Firepower NGFW Remote Access VPN Configuration Explaining Cisco Secure Network Access Solutions Cisco Secure Network Access Cisco Secure Network Access Components AAA Role in Cisco Secure Network Access Solution Cisco Identity Services Engine Cisco TrustSec Describing 802.1X Authentication 802.1X and Extensible Authentication Protocol (EAP) EAP Methods Role of Remote Authentication Dial-in User Service (RADIUS) in 802.1X Communications RADIUS Change of Authorization Configuring 802.1X Authentication Cisco Catalyst© Switch 802.1X Configuration Cisco Wireless LAN Controller (WLC) 802.1X Configuration Cisco Identity Services Engine (ISE) 802.1X Configuration Supplicant 802.1x Configuration Cisco Central Web Authentication Describing Endpoint Security Technologies* Host-Based Personal Firewall Host-Based Anti-Virus Host-Based Intrusion Prevention System Application Whitelists and Blacklists Host-Based Malware Protection Sandboxing Overview File Integrity Checking Deploying Cisco Advanced Malware Protection (AMP) for Endpoints* Cisco AMP for Endpoints Architecture Cisco AMP for Endpoints Engines Retrospective Security with Cisco AMP Cisco AMP Device and File Trajectory Managing Cisco AMP for Endpoints Introducing Network Infrastructure Protection* Identifying Network Device Planes Control Plane Security Controls Management Plane Security Controls Network Telemetry Layer 2 Data Plane Security Controls Layer 3 Data Plane Security Controls Deploying Control Plane Security Controls* Infrastructure ACLs Control Plane Policing Control Plane Protection Routing Protocol Security Deploying Layer 2 Data Plane Security Controls* Overview of Layer 2 Data Plane Security Controls Virtual LAN (VLAN)-Based Attacks Mitigation Sp

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators and network administrators Overview By the end of the course, you should be able to meet the following objectives: Describe the NSX Advanced Load Balancer architecture, components, and main functions Explain the key features and benefits of NSX Advanced Load Balancer Explain and configure local load-balancing constructs such as virtual services, pools, health monitors, and related components Recognize web application breaches and threats Recognize multiple attack vectors such as web scraping, Layer 7 Denial of Service, brute force, and code injections Explain the components of NSX Advanced Load Balancer WAF that build a security pipeline to protect a web application from being attacked Describe how to configure the NSX Advanced Load Balancer WAF components Describe an NSX Advanced Load Balancer WAF operational task such as setting up an application with WAF, tuning the WAF Policy, and working with logs and analytics Explain the NSX Advanced Load Balancer WAF best practices for on-boarding a web application; configuring WAF settings for effective application security Explain how to size the NSX Advanced Load Balancer WAF data plane Explain the WAF Application learning feature, configuration of Application learning, Virtual Patching concepts, common caveats, and troubleshooting while deploying in any environment Recognize NSX Advanced Load Balancer Cloud Services that include threat Intelligence services Describe the Threat Intelligence service provided by NSX Advanced Load Balancer WAF and how the NSX Advanced Load Balancer WAF Threat Intelligence service receives live security threat feed for multiple attack vectors from Cloud Services (formerly Avi Pulse) Describe the NSX Advanced Load Balancer DataScript capabilities for detecting and defending against advance and zero-day attacks. Discuss the relevant NSX Advanced Load Balancer WAF logs and perform basic troubleshooting of applications that are protected by NSX Advanced Load Balancer WAF Explain the NSX Advanced Load Balancer WAF capability to protect Personally Identifiable Information (PII) This three-day course provides comprehensive training to install, configure, and manage a VMware NSX Advanced Load Balancer Web Application Firewall (WAF) solution. This course covers key NSX Advanced Load Balancer WAF features and functionality offered in the NSX Advanced Load Balancer 22.1.3 release for web security and application attack protection. Features include security pipeline, application learning, policy tuning, false positive mitigation, virtual patching, threat intelligence, troubleshooting, logs, analytics, and solution monitoring. Hands-on labs provide access to an NSX Advanced Load Balancer environment to reinforce the skills and concepts presented in the course. Course Introduction Introduction and course logistics Course objectives Introduction to NSX Advanced Load Balancer Illustrate NSX Advanced Load Balancer Explain NSX Advanced Load Balancer architecture and components Describe control plane clustering and high availability Describe data plane high availability mode Understand the common terminologies used with NSX Advanced Load Balancer Explain the NSX Advanced Load Balancer service elements Explain virtual service components and how to configure a virtual service Explain application profiles and network profiles Explain the pool configuration options and how to configure a pool Explain the available load-balancing algorithms Explain and configure SSL profiles and certificates Explain cloud connectors and cloud connector integration modes Explain multiple health monitor types Understand client logs Introduction to Application Security Understand web application security breaches and the implication of breaches Explain common terminologies related to Web Application Security Understand the different teams involved to secure applications Attacking Web Applications Understand the various web application security testing methodologies Understand the OWASP Top 10 vulnerabilities Understand the tools to generate a web application attack Describe a few types of web application attacks Types of Transport Understand different web traffic transport modes Describe web traffic and API traffic NSX Advanced Load Balancer WAF Components Understand the core design principles of NSX Advanced Load Balancer WAF Describe the NSX Advanced Load Balancer WAF components that build the WAF security pipeline Understand the NSX Advanced Load Balancer WAF configuration objects NSX Advanced Load Balancer WAF Operations Examine how to set up an application with WAF Describe considerations for the WAF policy Work with WAF logs and analytics Describe WAF policy tuning Describe the options available to remediate false positive mitigation NSX Advanced Load Balancer WAF Best Practices Describe technical and application considerations for onboarding an application front ended by WAF Describe best practices to remediate false positive mitigation. Describe how to manage a response from a back-end application server and client upload to the application server Describe the consideration for setting the rigidity of a WAF signature rule set Describe the options available to identify client traffic NSX Advanced Load Balancer WAF Sizing Understand how to do WAF data plane sizing in Greenfield and Brownfield deployments NSX Advanced Load Balancer WAF Custom Rules Understand WAF custom rules Describe the need and recommendation for custom rules Describe ModSecurity rules Understand the ModSecurity rule structure and explain how to construct the rule Analyze a sample custom rule for the use-case scenario for in-depth understanding of a custom rule NSX Advanced Load Balancer WAF Application Learning Understand the significance of Application Learning Explain the Positive Security Model architecture Describe the WAF multifaceted Application Learning technique to build an application model for creating positive security rules Describe how to view the data that is learned by the Application learning module Describe the WAF Virtual Patching technique to construct a WAF policy from Dynamic Application Security Testing (DAST) scanner results Understand the conditions for sharing WAF Learning Data and PSM Group in WAF Policy. Malware Protection Through ICAP in NSX Advanced Load Balancer Understand Malicious File Upload Protection and ICAP workflow Describe ICAP configuration and log analytics NSX Advanced Load Balancer IP Reputation Understand IP Reputation concepts and their integration with NSX Advanced Load Balancer Describe IP Reputation configuration, log analytics, and troubleshooting DataScript for Application Security Describe DataScript events and reference Describe application security using DataScript Explain how to troubleshoot DataScript issues Rate Limiting and DOS Describe and configure the NSX Advanced Load Balancer rate limiter technique Describe protection from denial of service (DoS) attacks and distributed DoS (DDoS) attacks in NSX Advanced Load Balancer Explain the Service Engine general advice and guidance for DDOS Bot Management Understand Bots Describe the Bot Management mechanism in NSX Advanced Load Balancer Describe how to configure NSX Advanced Load Balancer Bot Management Managing Personally Identifiable Information in NSX Advanced Load Balancer Understand Personally Identifiable Information (PII) Understand the scope of managing PII in NSX Advanced Load Balancer Describe how to configure the hidden PII in NSX Advanced Load Balancer logs using profiles and WAF rules. Threat Intelligence Introduce the Threat Intelligence service Describe the Threat Intelligence live security threat feed for multiple attack vectors Describe how to configure Threat Intelligence in NSX Advanced Load Balancer Application Programming Interface Security Define Application Programming Interface (API) Security Understand API authentication and authorization using virtual service authentication mechanisms used for a virtual service such as LDAP, SAML, JSON Web Token, and OAUTH Understand API Rate Limiting in NSX Advanced Load Balancer Understand the NSX Advanced Load Balancer WAF Protection for API Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware NSX Advanced Load Balancer: Web Application Firewall Security [V22.x] 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 VMware NSX Advanced Load Balancer: Web Application Firewall Security [V22.x] 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.

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