Duration 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training 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 Cloudera Data Scientist Training 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 Network Security Operations Workload Application Administrators Security Operations Field Engineers Network Engineers Systems Engineers Technical Solutions Architects Cisco Integrators and Partners Overview After taking this course, you should be able to: Define the Cisco telemetry and analytics approach. Explore common scenarios that Cisco Tetration Analytics can solve. Describe how the Cisco Tetration Analytics platform collects telemetry and other context information. Discuss how relative agents are installed and configured. Explore the operational aspects of the Cisco Tetration Analytics platform. Describe the Cisco Tetration Analytics support for application visibility or application insight based on the Application Dependency Mapping (ADM) feature. List the concepts of the intent-based declarative network management automation model. Describe the Cisco Tetration policy enforcement pipeline, components, functions, and implementation of application policy. Describe how to use Cisco Tetration Analytics for workload protection in order to provide a secure infrastructure for business-critical applications and data. Describe Cisco Tetration Analytics platform use cases in the modern heterogeneous, multicloud data center. List the options for the Cisco Tetration Analytics platform enhancements. Explain how to perform the Cisco Tetration Analytics administration. This course teaches how to deploy, use, and operate Cisco© Tetration Analytics? platform for comprehensive workload-protection and application and network insights across a multicloud infrastructure. You will learn how the Cisco Tetration Analytics platform uses streaming telemetry, behavioral analysis, unsupervised machine learning, analytical intelligence, and big data analytics to deliver pervasive visibility, automated intent-based policy, workload protection, and performance management. Exploring Cisco Tetration Data Center Challenges Define and Position Cisco Tetration Cisco Tetration Features Cisco Tetration Architecture Cisco Tetration Deployment Models Cisco Tetration GUI Overview Implementing and Operating Cisco Tetration Explore Data Collection Install the Software Agent Install the Hardware Agent Import Context Data Describe Cisco Tetration Operational Concepts Examining Cisco Tetration ADM and Application Insight Describe Cisco Tetration Application Insight Perform ADM Interpret ADM Results Application Visibility Examining Cisco Tetration Intent-Based Networking Describe Intent-Based Policy Examine Policy Features Implement Policies Enforcing Tetration Policy Pipeline and Compliance Examine Policy Enforcement Implement Application Policy Examine Policy Compliance Verification and Simulation Examining Tetration Security Use Cases Examine Workload Security Attack Prevention Attack Detection Attack Remediation Examining IT Operations Use Cases Key Features and IT Operations Use Cases Performing Operations in Neighborhood App-based Use Cases Examining Platform Enhancement Use Cases Integrations and Advanced Features Third-party Integration Examples Explore Data Platform Capabilities Exploring Cisco Tetration Analytics Administration Examine User Authentication and Authorization Examine Cluster Management Configure Alerts and Syslog Additional course details: Nexus Humans Cisco Implementing Cisco Tetration Analytics v1.0 (DCITET) 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 Implementing Cisco Tetration Analytics v1.0 (DCITET) 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 In order to be successful in this class, incoming attendees are required to have current, hands-on experience in developing basic web applications, and be versed in HTML5, CSS3 and JavaScript. This is an intermediate level web development class, designed for experienced web developers, new to Angular, that need to further extend their skills in modern web development. Overview At the end of this five-day course, students will have an application up and running that incorporates components, directives, custom pipes, reactive forms, routes, services, unit testing, and the REST API. They will add authentication, implement the Material library, and learn how to maintain state with NgRX. They will then take a deeper dive including making their own custom directives, lazy loading modules, and E2E testing. They will learn how to enhance their application with animations and create their own Angular library. Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn explore: What Angular is and why should you use it How Angular reduces the amount of code that you must write to add rich functionality to both existing and new web pages What TypeScript is, why it is useful, and how to use it with Angular How to facilitate development and deployment using Angular CLI How to work with the various aspects of the Angular architecture to implement clean, responsive web interfaces How Routers can support navigation within a Single Page Application What the best practices are for using Angular so that it works unobtrusively and performs well How to use Angular with HTTP to support JSON, REST, and other services Working with the Ahead of Time compiler including its impact of developers and the development process How to defend against DOM-based XSS How to manage routing decisions based on pre-defined criteria such as a successful authentication How to meet huge data requirements by processing asynchronous data streams with RxJS Simplify server-side rendering How to facilitate unit testing Enhance an Angular user interface with animations and other advanced features Optimize Angular applications with various tools and techniques Maintain state within an Angular application What Angular 9 brings to the table and its relationship to Angular 8 Mastering Angular is a five-day, hands-on course that thoroughly explores the latest Angular features and advances, demonstrating how to solve the traditional challenges of JavaScript web application development. Throughout the course students will build custom components using application routes, form validation, and unit-testing. The course starts with an introduction of Angular CLI and TypeScript, and then delves into component-driven development with Angular components, covering data-binding, directives, services, routing, HTTP, the RxJS library, forms unit testing, and REST. Students will also learn how to add authentication, use the Material library, learn the NgRX design pattern to implement the NgRX store, make custom directives, enhance their application with animations, write an E2E test, and increase their application's efficiency by lazy loading modules and creating their own Angular library Angular Overview Overview of Angular Architecture Getting Started with Angular Getting Started with TypeScript Bootstrapping with Angular CLI Angular Project Structure Working with Angular Components and Events Third Party Libraries Dynamic Views Pipes Angular Forms Forms and the Forms API Single Page Applications and Routes Single Page Applications Services and Dependency Injection Modules Using RESTful Services Overview of REST Angular and REST Angular Best Practices Angular Style Guide What is New in Angular 9 Reactive Programming in Angular Working with RxJS Security and Authentication DomSanitizer JSON Web Tokens Route Guards Enhancing the Angular App Angular Animations Angular Material Angular Elements Deep Dive into Angular Testing and Angular Deep Dive into Components and Directives Deep Dive into Services and Dependency Injection Optimizing for the Enterprise Lazy Loading Optimizing with Universal Creating Your Own Angular Library Maintain State with NgRX NgRX Store Lesson: ES6+ Sass and SCSS for Angular and Material
Duration 2 Days 12 CPD hours Overview This skills-focused course combines expert instructor-led discussions with practical hands-on labs that emphasize useful, current techniques, best practices and standards. Working in this hands-on lab environment, guided by our expert practitioner, you'll learn about and explore: Review of the File System Introduction to Shells: sh, bash, and ksh Shell Programming Advanced Shell Features Text Manipulation Utilities File Processing Utilities Multitasking and Batch Processing Regular Expressions Intermediate Linux: Shell, Bash, Text Manipulation, Multitasking & More is a two-day course designed to provide you with hands on experience using standard Linux commands and utilities used for day-to-day tasks including file manipulation, program execution and control, and effective use of the shell and desktop environments. Throughout the course you?ll explore key concepts to Linux core functionality, while learning the system's most commonly used commands. You?ll also learn the Bourne shell, Bash shell and Korn shell programming techniques you?ll need to read and modify existing shell scripts, and create your own. Data manipulation utilities and shell syntax for synthesizing command pipelines are also emphasized throughout the course. Review of the File System File System Organization File Types File and Directory Naming Rules and Conventions Commands for Navigating the File System Introduction to Inodes Ownership, Permissions, and Dates Manipulating Files and Links Manipulating Directories Determining Disk Usage Other File System Utilities Introduction to Shells: sh, bash, and ksh Shell Functions I/O Redirection and Pipes Command Separation and Grouping Background Execution Filename Expansion Shell Variables Command Substitution Quoting and Escaping Metacharacters Bash Shell Features Korn Shell Features Command Execution Startup Files Customizing the User Environment Shell Programming Shell Script Features and Capabilities Creating and Running a Script Working With Variables Environment Variables Working With Data Types Formatting Base Conversion Setting Special Attributes Input/Output Techniques Conditional Constructs if/then else/elif Looping Constructs for, while, until Math Operators Advanced Shell Features Manipulating Strings Writing and Calling Functions Controlling Process Priorities Interpreting Command Line Arguments Making Scripts Interactive Special Shell Variables Advanced I/O with Streams Improving Performance of Scripts Text Manipulation Utilities Editing a File from a Script Scripting with ed or sed UNIX and Linux Utilities to Manipulate Files Regular Expressions grep and egrep The Stream Editor sed Sorting in Scripts Generating Reports with awk Splitting Large Files Counting Words, Lines, and Characters Transforming File Contents File Processing Utilities Examining and Comparing Files Reporting Differences Between Files Comparing Files of Any Format Displaying Data in Octal and Hex Compressing Data Converting File Formats Extracting Text Strings Multitasking and Batch Processing Multitasking Scheduled Execution Using cron The at and batch Commands Regular Expressions Regular Expression Overview Regular Expression Implementations Regular Expressions RE Character Classes Regex Quantifiers RE Parenthesis Additional course details: Nexus Humans Intermediate Linux (TTLX2104) 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 Intermediate Linux (TTLX2104) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 2 Days 12 CPD hours This course is intended for Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers. Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure with the Google Cloud Platform. Overview Apply a tool set of questions, techniques and design considerations Define application requirements and express them objectively as KPIs, SLO's and SLI's Decompose application requirements to find the right microservice boundaries Leverage Google Cloud developer tools to set up modern, automated deployment pipelines Choose the appropriate Google Cloud Storage services based on application requirements Architect cloud and hybrid networks Implement reliable, scalable, resilient applications balancing key performance metrics with cost Choose the right Google Cloud deployment services for your applications Secure cloud applications, data and infrastructure Monitor service level objectives and costs using Stackdriver tools This course features a combination of lectures, design activities, and hands-on labs to show you how to use proven design patterns on Google Cloud to build highly reliable and efficient solutions and operate deployments that are highly available and cost-effective. This course was created for those who have already completed the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course. Defining the Service Describe users in terms of roles and personas. Write qualitative requirements with user stories. Write quantitative requirements using key performance indicators (KPIs). Evaluate KPIs using SLOs and SLIs. Determine the quality of application requirements using SMART criteria. Microservice Design and Architecture Decompose monolithic applications into microservices. Recognize appropriate microservice boundaries. Architect stateful and stateless services to optimize scalability and reliability. Implement services using 12-factor best practices. Build loosely coupled services by implementing a well-designed REST architecture. Design consistent, standard RESTful service APIs. DevOps Automation Automate service deployment using CI/CD pipelines. Leverage Cloud Source Repositories for source and version control. Automate builds with Cloud Build and build triggers. Manage container images with Google Container Registry. Create infrastructure with code using Deployment Manager and Terraform. Choosing Storage Solutions Choose the appropriate Google Cloud data storage service based on use case, durability, availability, scalability and cost. Store binary data with Cloud Storage. Store relational data using Cloud SQL and Spanner. Store NoSQL data using Firestore and Cloud Bigtable. Cache data for fast access using Memorystore. Build a data warehouse using BigQuery. Google Cloud and Hybrid Network Architecture Design VPC networks to optimize for cost, security, and performance. Configure global and regional load balancers to provide access to services. Leverage Cloud CDN to provide lower latency and decrease network egress. Evaluate network architecture using the Cloud Network Intelligence Center. Connect networks using peering and VPNs. Create hybrid networks between Google Cloud and on-premises data centers using Cloud Interconnect. Deploying Applications to Google Cloud Choose the appropriate Google Cloud deployment service for your applications. Configure scalable, resilient infrastructure using Instance Templates and Groups. Orchestrate microservice deployments using Kubernetes and GKE. Leverage App Engine for a completely automated platform as a service (PaaS). Create serverless applications using Cloud Functions. Designing Reliable Systems Design services to meet requirements for availability, durability, and scalability. Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures. Avoid overload failures with the circuit breaker and truncated exponential backoff design patterns. Design resilient data storage with lazy deletion. Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis. Security Design secure systems using best practices like separation of concerns, principle of least privilege, and regular audits. Leverage Cloud Security Command Center to help identify vulnerabilities. Simplify cloud governance using organizational policies and folders. Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform. Manage the access and authorization of resources by machines and processes using service accounts. Secure networks with private IPs, firewalls, and Private Google Access. Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor. Maintenance and Monitoring Manage new service versions using rolling updates, blue/green deployments, and canary releases. Forecast, monitor, and optimize service cost using the Google Cloud pricing calculator and billing reports and by analyzing billing data. Observe whether your services are meeting their SLOs using Cloud Monitoring and Dashboards. Use Uptime Checks to determine service availability. Respond to service outages using Cloud Monitoring Alerts. Additional course details: Nexus Humans Architecting with Google Cloud: Design and Process training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Architecting with Google Cloud: Design and Process 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 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 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 3 Days 18 CPD hours This course is intended for Developers who have some familiarity with serverless and experience with development in the AWS Cloud Overview In this course, you will learn to: Apply event-driven best practices to a serverless application design using appropriate AWS services Identify the challenges and trade-offs of transitioning to serverless development, and make recommendations that suit your development organization and environment Build serverless applications using patterns that connect AWS managed services together, and account for service characteristics, including service quotas, available integrations, invocation model, error handling, and event source payload Compare and contrast available options for writing infrastructure as code, including AWS CloudFormation, AWS Amplify, AWS Serverless Application Model (AWS SAM), and AWS Cloud Development Kit (AWS CDK) Apply best practices to writing Lambda functions inclusive of error handling, logging, environment re-use, using layers, statelessness, idempotency, and configuring concurrency and memory Apply best practices for building observability and monitoring into your serverless application Apply security best practices to serverless applications Identify key scaling considerations in a serverless application, and match each consideration to the methods, tools, or best practices to manage it Use AWS SAM, AWS CDK, and AWS developer tools to configure a CI/CD workflow, and automate deployment of a serverless application Create and actively maintain a list of serverless resources that will assist in your ongoing serverless development and engagement with the serverless community This course gives developers exposure to and practice with best practices for building serverless applications using AWS Lambda and other services in the AWS serverless platform. You will use AWS frameworks to deploy a serverless application in hands-on labs that progress from simpler to more complex topics. You will use AWS documentation throughout the course to develop authentic methods for learning and problem-solving beyond the classroom. Introduction Introduction to the application you will build Access to course resources (Student Guide, Lab Guide, and Online Course Supplement) Thinking Serverless Best practices for building modern serverless applications Event-driven design AWS services that support event-driven serverless applications API-Driven Development and Synchronous Event Sources Characteristics of standard request/response API-based web applications How Amazon API Gateway fits into serverless applications Try-it-out exercise: Set up an HTTP API endpoint integrated with a Lambda function High-level comparison of API types (REST/HTTP, WebSocket, GraphQL) Introduction to Authentication, Authorization, and Access Control Authentication vs. Authorization Options for authenticating to APIs using API Gateway Amazon Cognito in serverless applications Amazon Cognito user pools vs. federated identities Serverless Deployment Frameworks Overview of imperative vs. declarative programming for infrastructure as code Comparison of CloudFormation, AWS CDK, Amplify, and AWS SAM frameworks Features of AWS SAM and the AWS SAM CLI for local emulation and testing Using Amazon EventBridge and Amazon SNS to Decouple Components Development considerations when using asynchronous event sources Features and use cases of Amazon EventBridge Try-it-out exercise: Build a custom EventBridge bus and rule Comparison of use cases for Amazon Simple Notification Service (Amazon SNS) vs. EventBridge Try-it-out exercise: Configure an Amazon SNS topic with filtering Event-Driven Development Using Queues and Streams Development considerations when using polling event sources to trigger Lambda functions Distinctions between queues and streams as event sources for Lambda Selecting appropriate configurations when using Amazon Simple Queue Service (Amazon SQS) or Amazon Kinesis Data Streams as an event source for Lambda Try-it-out exercise: Configure an Amazon SQS queue with a dead-letter queue as a Lambda event source Writing Good Lambda Functions How the Lambda lifecycle influences your function code Best practices for your Lambda functions Configuring a function Function code, versions and aliases Try-it-out exercise: Configure and test a Lambda function Lambda error handling Handling partial failures with queues and streams Step Functions for Orchestration AWS Step Functions in serverless architectures Try-it-out exercise: Step Functions states The callback pattern Standard vs. Express Workflows Step Functions direct integrations Try-it-out exercise: Troubleshooting a Standard Step Functions workflow Observability and Monitoring The three pillars of observability Amazon CloudWatch Logs and Logs Insights Writing effective log files Try-it-out exercise: Interpreting logs Using AWS X-Ray for observability Try-it-out exercise: Enable X-Ray and interpret X-Ray traces CloudWatch metrics and embedded metrics format Try-it-out exercise: Metrics and alarms Try-it-out exercise: ServiceLens Serverless Application Security Security best practices for serverless applications Applying security at all layers API Gateway and application security Lambda and application security Protecting data in your serverless data stores Auditing and traceability Handling Scale in Serverless Applications Scaling considerations for serverless applications Using API Gateway to manage scale Lambda concurrency scaling How different event sources scale with Lambda Automating the Deployment Pipeline The importance of CI/CD in serverless applications Tools in a serverless pipeline AWS SAM features for serverless deployments Best practices for automation Course wrap-up Additional course details: Nexus Humans AWS Developing Serverless Solutions on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AWS Developing Serverless Solutions on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 5 Days 30 CPD hours This course is intended for System administrator Network administrator Technician DevOps Overview The Linux Professional Institute(LPI) is the go to certification body for vendor independent Linux certifications. This course covers fundamental Linuxskills such as file management and manipulation, text processing, command line use, package management,filesystems, hardware, and many more. Students will feel confident taking the LPI LPIC-1 101 exam with in classroomassessments and practice exams. This course prepares students to take the 101 exam of the LPI level 1 certification. Work on the Command Line LPI Objectives Covered Role of Command Shell Shells Gathering System Info Identifying the Shell Changing the Shell Shell Prompts Bash: Bourne-Again Shell Navigating the Filesystem Help from Commands and Documentation Getting Help Within the Graphical Desktop Getting Help with man & info Bash: Command Line History Bash: Command Editing Bash: Command Completion Shell and Environment Variables Key Environment Variables LAB TASKS Use Streams, Pipes, and Redirects LPI Objectives Covered File Redirection Piping Commands Together Filename Matching File Globbing and Wildcard Patterns Brace Expansion General Quoting Rules Nesting Commands Gotchas: Maximum Command Length LAB TASKS Manage File Permissions and Ownership LPI Objectives Covered Filesystem Hierarchy Standard Displaying Directory Contents Filesystem Structures Determining Disk Usage With df and du File Ownership Default Group Ownership File and Directory Permissions File Creation Permissions with umask Changing File Permissions SUID and SGID on files SGID and Sticky Bit on Directories User Private Group Scheme LAB TASKS Create, Delete, Find, and Display Files LPI Objectives Covered Directory Manipulation File Manipulation Deleting and Creating Files Physical Unix File Structure Filesystem Links File Extensions and Content Which and Type Where is Searching the Filesystem Alternate Search Method Manually Installed Shared Libraries LAB TASKS Work with Archives and Compression LPI Objectives Covered Archives with tar Archives with cpio The gzip Compression Utility The bzip2 Compression Utility The XZ Compression Utility The PKZIP Archiving/Compression format LAB TASKS Process Text Streams Using Filters LPI Objectives Covered Producing File Statistics The Streaming Editor Replacing Text Characters Text Sorting Duplicate Removal Utility Extracting Columns of Text Displaying Files Prepare Text for Display Previewing Files Displaying Binary Files Combining Files and Merging Text LAB TASKS Search Text Files Using Regular Expressions LPI Objectives Covered Searching Inside Files Regular Expression Overview Regular Expressions RE Character Classes Regex Quantifiers RE Parenthesis LAB TASKS Perform Basic File Editing Operations Using VI LPI Objectives Covered Text Editing vi and Vim Learning Vim Basic vi Intermediate vi LAB TASKS Create, Monitor, and Kill Processes LPI Objectives Covered What is a Process? Process Lifecycle Process States Viewing Processes Signals Tools to Send Signals Managing Processes Tuning Process Scheduling Job Control Overview Job Control Commands Nohup and Disown Uptime & w Persistent Shell Sessions with Screen Using screen Advanced Screen LAB TASKS Use RPM, YUM, and Debian Package Management LPI Objectives Covered Managing Software RPM Architecture Working With RPMs Querying and Verifying with RPM Installing Debian Packages Querying and Verifying with dpkg The alien Package Conversion Tool Managing Software Dependencies Using the Yum command yum downloader Configuring Yum The deselect & APT Frontends to dpkg Aptitude Configuring APT LAB TASKS Work with Partitions, Filesystem, and Disk Quotas LPI Objectives Covered Partition Considerations Logical Volume Management Filesystem Planning Partitioning Disks with fdisk & gdisk Resizing a GPT Partition with gdisk Partitioning Disks with parted Non-Interactive Disk Partitioning with sfdisk Filesystem Creation Filesystem Support Unix/Linux Filesystem Features Swap Selecting a Filesystem Filesystem Maintenance Mounting Filesystems Mounting Filesystems Managing an XFS Filesystem NFS SMB Filesystem Table (/etc/fstab) Configuring Disk Quotas Setting Quotas Viewing and Monitoring Quotas LAB TASKS Linux Boot Process LPI Objectives Covered Booting Linux on PCs GRUB 2 GRUB 2 Configuration GRUB Legacy Configuration Boot Parameters Uinit Linux Runlevels Aliases Systemd local-fs.target and sysinit.target Runlevel Implementation System Boot Method Overview Systemd System and Service Manager Modifying systemd services Systemd Targets Using systemd Shutdown and Reboot System Messaging Commands Controlling System Messaging LAB TASKS Determine and Configure Hardware Settings LPI Objectives Covered Managing Linux Device Files Hardware Discovery Tools Configuring New Hardware with hwinfo PC Architecture and Bus DMA & IRQ USB Devices USB Architecture Configuring Kernel Components and Modules Kernel Modules Handling Module Dependencies Configuring the Kernel via /proc/ LAB TASKS Linux Fundamentals Unix and its Design Principles FSF and GNU GPL Æ?? General Public License The Linux Kernel Components of a Distribution Red Hat Linux Products SUSE Linux Products Debian Ubuntu Logging In got root? Switching User Contexts Gathering Login Session Info LAB TASKS Additional course details: Nexus Humans Linux Professional Institute Certification (LPIC) 101 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 Linux Professional Institute Certification (LPIC) 101 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 introductory-level course is for experienced DBAs who will be working with MongoDB. In order to gain the most from this course you should have: Prior practical experience in Database Administration Experience working with Linux and be comfortable working with command line Overview This skills-focused course is approximately 50% hands-on. 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 explore: The MongoDB Basic Architecture and Installation MongoDB administration User Management MongoDB security Indexes Backup & Recovery High Availability / Replication Diagnostics & Troubleshooting MongoDB is fast becoming the database of choice for big data applications, being one of the most popular and widely implemented NoSQL databases. Its scalability, robustness, and flexibility have made it extremely popular among business enterprises who use it to implement a variety of activities including social communications, analytics, content management, archiving and other activities. This has led to an increased demand for MongoDB administrators who have the skills to handle cross functional duties. Geared for experienced DBAs, MongoDB for DBAs is a three-day hands-on course that explores the concepts, architecture and pitfalls of managing a MongoDB installation. This course is targeted to the DBA who is familiar with the concepts and tasks of working with a Relational database and is not responsible for a NoSQL MongoDB database. You will learn the critical aspects of MongoDB and use it to solve data management challenges. You will learn to manage MongoDB effectively by gaining expertise in MongoDB administration tools, syntax, MongoDB installations, configurations, security, troubleshooting, backup, scaling and many other features. The focus of this course is on practical skills and applying the DBA existing database knowledge to a MongoDB installation. Introduction to MongoDB Basic Architecture and Installation Differentiate database categories Learn MongoDB design goals List MongoDB tools Describe JSON and BSON Understanding the basic concepts of a Database Database categories: What is NoSQL? Why NoSQL? Benefit over RDBMS Types of NoSQL Database, and NoSQL vs. SQL Comparison, ACID & Base Property CAP Theorem, implementing NoSQL and what is MongoDB? Graph Database Overview of MongoDB, Design Goals for MongoDB Server and Database, MongoDB tools Understanding the following: Collection, Documents and Key/Values, etc., Introduction to JSON and BSON documents Environment setup (live Handson) and using various MongoDB tools available in the MongoDB Package MongoDB Administration Take database backup and restore MongoDB© Export and import data from/ to a MongoDB© instance Check server status and DB status Monitor various resource utilization of a mongod instance Understand various optimization strategies Administration concepts in MongoDB Monitoring issues related to Database Monitoring at Server, Database, Collection level, and various Monitoring tools related to MongoDB Database Profiling, Locks, Memory Usage, No of connections, page fault etc., Backup and Recovery Methods for MongoDB Export and Import of Data to and from MongoDB Run time configuration of MongoDB Production notes/ best practices Data Managements in MongoDB (Capped Collections/ Expired data from TTL), TTL Collection Features GridFS Memory-Mapped Files Journaling Mechanics Storage Engines Power of 2-Sized Allocations No Padding Allocation Strategy Diagnosing Performance Issues Optimization Strategies for MongoDB Configure Tag Sets for Replica Set. Optimize Query Performance Monitoring Strategies for MongoDB . MongoDB Utilities MongoDB Commands MongoDB Management Service (MMS) Data Backup Strategies in MongoDB Copying Underlying Data Files Backup with MongoDump Fsync and Lock MongoDB Ops Manager Backup Software Security Strategies in MongoDB Authentication Implementation in MongoDB . Authentication in a Replica set Authentication on Sharded Clusters Authorization End-to-End Auditing for Compliance User Management Create a User Administrator. Add a User to a Database. Create/Assign User a Role. Verify/Modify a User Access/Privileges. Change a User?s Password MongoDB Security Knowing security concepts in MongoDB Understand how Authentication and Authorisation works Security Introduction Security Concepts Indexes Index Introduction, Index Concepts, Index Types Index Properties Index Creation and Indexing Reference Introduction to Aggregation Aggregation Approach to Aggregation sort Order Pipeline Operators and Indexes Text Indexes Aggregate Pipeline Stages Text Search MapReduce Index Creation Aggregation Operations Index Creation on Replica Set Remove, Modify, and Rebuild Indexes Listing Indexes Measure Index Use Control Index Use Index Use Reporting Geospatial Indexes MongoDB?s Geospatial Query Operators GeoWith Operator Backup & Recovery Import and Export MongoDB Data Restore and recovery of MongoDB(Including point in time Recovery) Restore a Replica Set from MongoDB Backups Recover Data after an Unexpected Shutdown Backup and Restore with Filesystem Snapshots Back Up and Restore with MongoDB Tools Backup and Restore Sharded Clusters High Availability (Replication ) Understand the concept of Replication in MongoDB© ? Create a production like Replica Set Introduction to Replication (High Availability), Concepts around Replication What is Replica Set and Master Slave Replication? Type of Replication in MongoDB How to setup a replicated cluster & managing replica sets etc., Master-Slave Replication Replica Set in MongoDB Automatic Failover Replica Set Members Write Concern Write Concern Levels Write Concern for a Replica Set Modify Default Write Concern Read Preference Read Preference Modes Blocking for Replication Tag Set Configure Tag Sets for Replica set. Replica Set Deployment Strategies . Replica Set Deployment Patterns Oplog File Replication State and Local Database, Replication Administration Diagnostics & Troubleshooting Troubleshoot slow queries Diagnose connectivity problems Understand diagnostic tools Learn common production issues Learn fixes and solutions. Additional course details: Nexus Humans Introduction to MongoDB for DBAs (TTDB4680) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to MongoDB for DBAs (TTDB4680) 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.