10496 Courses delivered Online

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 4 Days 24 CPD hours This course is intended for The primary audience for this course is as follows: System Installers System Integrators System Administrators Network Administrators Solutions Designers Overview Upon completing this course, the learner will be able to meet these overall objectives: Describe the Cisco IOS XR 64-Bit software architecture and Linux system fundamentals Describe the major differences between classic Cisco IOS XR software and Cisco IOS XR 64-Bit software on the ASR 9000 Series routers Migrate an ASR 9000 Series router from classic IOS XR software to Cisco IOS XR 64-Bit software Perform and explain Cisco IOS XR 64-Bit software installations Configure and describe Cisco IOS XR 64-Bit software features The Cisco ASR 9000 Series IOS XR 64-Bit Software Migration and Operational Enhancements (IOSXR211) course covers the migration from classic 32-bit Cisco IOS© XR software to Cisco IOS XR 64-Bit software on the Cisco© ASR 9000 Series Aggregation Services Routers. This course will also examine the software architecture, boot process, and auto-provisioning of the Cisco IOS XR 64-bit software, as well as showing you how to install Cisco IOS XR and third-party software packages. In addition, it will investigate data models and show you how to implement telemetry, model-driven programmability, and application hosting services. Software Architecture and Linux Fundamentals Cisco IOS XR 64-Bit Software Fundamentals Cisco ASR 9000 Series IOS XR 64-Bit Software vs. Classic 32-Bit Software Exploring Linux Fundamentals Creating User Profiles Cisco IOS XR 64-Bit Software Installation Examining Resource Allocations and Media Mappings Migrating to Cisco IOS XR 64-Bit Software Examining the Boot Process Performing Disaster Recovery Installing Software Packages Cisco IOS XR 64-Bit Software Features Investigating Data Models Implementing Telemetry Exploring Model-Driven Programmability Employing Application Hosting Additional course details: Nexus Humans Cisco ASR9000 Series 64-bit Software Migration (IOSXR211) 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 ASR9000 Series 64-bit Software Migration (IOSXR211) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is primarily for Developers, Developer Consultants, Help Desk/COE Support, and Program/Project Managers. Overview Learn the fundamental concepts of the ABAP programming languageEfficiently use the ABAP Workbench toolsCreate simple application programs with user dialogs (list, selection screen, screens, Web Dynpro) and database dialogs (reading from the database) In this course, students gain knowledge of the fundamental concepts of ABAP and learn how to comfortably and efficiently work with the ABAP Workbench tools in order to undertake custom developments with confidence. Flow of an ABAP Program Describing the Processing of ABAP Programs ABAP Workbench Introduction Introducing the ABAP Development Environment Organizing ABAP Developments Developing Programs Finalizing Development Basic ABAP Language Elements Defining Elementary Data Objects Using Basic ABAP Statements Working with the ABAP Debugger Modularization Introducing Modularization Modularizing Using Subroutines Modularizing Using Function Modules Implementing Function Modules Modularizing Using BAPIs Modularizing Using Global Classes Implementing Simple Global Classes and Static Methods Modularizing Using Local Classes Complex Data Objects Working with Structures Working with Internal Tables Data Modeling and Data Retrieval Modeling Data Reading Single Database Records Reading Multiple Database Records Handling Other Aspects of Database Access Working with Authorization Checks Classic ABAP Report Implementing ABAP Lists Implementing Selection Screens Implementing Events of ABAP Reports Screen Creating Screens Creating Input/Output Fields Implementing Data Transport SAP List Viewer Using the SAP List Viewer Web Dynpro ABAP Describing Web Dynpro ABAP Implementing Navigation in Web Dynpro Implementing Data Transport in Web Dynpro Program Analysis Tools Using the Code Inspector ABAP Development Tools for SAP NetWeaver Describing ABAP Development Tools for SAP NetWeaver Creating an ABAP Project in Eclipse SAP Standard Software Adjustments Adjusting the SAP Standard Software Additional course details: Nexus Humans BC400 SAP ABAP Workbench Foundations 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 BC400 SAP ABAP Workbench Foundations 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 This course is for analysts, developers, and administrators of IBM Watson Explorer Deep Analytics Edition oneWEX. Overview Identify oneWEX platformsIdentify the process and data flows of oneWEX projectsExplore the oneWEX user interfaceExplain ingestion and conversionUtilize Content MinerDefine enrichmentIdentify advanced features of oneWEX This course is designed to teach students core concepts of IBM Watson Explorer Deep Analytics Edition oneWEX. Students will learn to identify the oneWEX platforms as well as the process flow and data flow of oneWEX projects. Students will explore oneWEX tools, such as Content Miner and the Admin Console, while gaining hands-on experience in data acquisition and enrichment. Finally, students will be exposed to more advanced topics, such as Application Builder, Content Analytics Studio, and API usage. Overview of oneWEX Introduction to oneWEX Explore oneWEX architecture Identify installation options Navigation in oneWEX Explore the Admin Console Explore navigation using Content Miner The Collection detail view The REST API Data flow Explore the data flow of oneWEX Search and Analytics collection templates Identify data acquisition Data ingestion Work with datasets Work with crawlers Use an importer Explore conversion Data ingestion log files Analysis using oneWEX Content Miner Explore analysis using Content Miner The Guided Analysis Experience The Guided Analysis view Explore Annotators Enrichment using Annotators Annotator types Enrichment using Labeler Identify enrichment Identify document classification Classify using training data Classification versus clustering The document classification process Enrichment using Ranker Identify enrichment using Ranker The ranking process Migrate annotators from Content Analytics Studio Migrate Content Analytics Studio annotators Identify the UIMA pipeline configuration for oneWEX Update annotators Using Application Builder with oneWEX Application Builder and user roles Explore Application Builder Set up a oneWEX data source Functionality for oneWEX data sources Additional course details: Nexus Humans O3201 Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.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 O3201 Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.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.

Duration 2 Days 12 CPD hours This course is intended for This Introductory-level course is targeted for aspiring web developers who have software development experience or background. The course can also be adjusted for non-developers upon request. Overview This 'skills-focused' course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our instructors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Introduction to HTML5/ CSS3 and Responsive Design Basics is a hands-on basic web development course geared for developers who need to understand what the latest in web technologies and responsive design practices that are central to targeting the entire spectrum of user platforms and browsers. This comprehensive course provides a balanced mixture of theory and practical labs designed to take students through HTML5 and CSS3. Students who attend this course will leave this course armed with the new skills to design, implement, and deploy robust, flexible, and safe web applications. HTML Define HTML and review its history Look at XHTML and its relationship to HTML Identify HTML limitations and improvements HTML5 HTML5 Overview HTML5 Semantic Structure HTML5 Forms HTML5 Media Delivery CSS Learn the basics of CSS Meaning of cascading in CSS Declaring CSS within your HTML page Creating styles in an external CSS file Control how to display and position HTML elements Overriding standard tag behavior Adding new classes Using custom classes in your page CSS3 Overview What is new in CSS3 The Advantages of CSS3 Browser Support for CSS3 CSS3 Advanced Selectors Selecting Using Attributes Selecting Using DOM Structure Complex Selecting using Pseudo-Classes Selecting Using UI Components and State CSS3 Visual Effects Font Options, Opacity, and Color Distributing Content Across Columns Working with Borders and Boxes Working with Vendor Prefixes Functional Techniques HTML5 JavaScript API Cross-Domain Messaging Working with Web Storage Offline with Application Cache Geolocation: What, Why, and How Responsive Web Design (RWD) Adapting to Varying Screen Sizes Scaling Page and Text Content Scaling and Adapting for Media Options for Adjusting Media Additional course details: Nexus Humans Web Essentials | Introduction to HTML5, CSS3 and Responsive Design (TT4002) 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 Web Essentials | Introduction to HTML5, CSS3 and Responsive Design (TT4002) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

A writing workshop to release stress, explore our shadows and reveal our creative force.

Duration 4 Days 24 CPD hours This course is intended for System installersSystem integratorsSystem administratorsNetwork administratorsSolutions designers Overview After completing this course, you should be able to:Describe the Cisco IOS XR 64-Bit software architecture and Linux system fundamentalsDescribe the major differences between classic Cisco IOS XR software and Cisco IOS XR 64-Bit software on the ASR 9000 Series routersMigrate an ASR 9000 Series router from classic IOS XR software to Cisco IOS XR 64-Bit softwarePerform and explain Cisco IOS XR 64-Bit software installationsConfigure and describe Cisco IOS XR 64-Bit software features The Cisco ASR 9000 Series IOS XR 64-Bit Software Migration and Operational Enhancements (IOSXR211) v1.0 course covers the migration from classic 32-bit Cisco IOS© XR software to Cisco IOS XR 64-Bit software on the Cisco© ASR 9000 Series Aggregation Services Routers. This course will also examine the software architecture, boot process, and auto-provisioning of the Cisco IOS XR 64-bit software, as well as showing you how to install Cisco IOS XR and third-party software packages. In addition, it will investigate data models and show you how to implement telemetry, model-driven programmability, and application hosting services. Software Architecture and Linux Fundamentals Cisco IOS XR 64-Bit Software Fundamentals Cisco ASR 9000 Series IOS XR 64-Bit Software vs. Classic 32-Bit Software Exploring Linux Fundamentals Creating User Profiles Cisco IOS XR 64-Bit Software Installation Examining Resource Allocations and Media Mappings Migrating to Cisco IOS XR 64-Bit Software Examining the Boot Process Performing Disaster Recovery Installing Software Packages Cisco IOS XR 64-Bit Software Features Investigating Data Models Implementing Telemetry Exploring Model-Driven Programmability Employing Application Hosting

Duration 1 Days 6 CPD hours This course is intended for This course is intended for solution architects, developers, business analysts, system administrators, or anyone who works as a solution builder within their company. Overview Build and deploy a solution Create properties and document classes Create roles and in-baskets Create a case type and tasks Create a workflow Use preconditions and sets Automate case packaging Add case stages Apply solution design principles In this course you will create basic case management solutions with IBM Case Manager Builder and Process Designer. Using an iterative solution development process, you will create, deploy, test, and revise your solutions, adding complexity and functionality to your solutions as you gain skills. You will create properties and document classes, configure roles and in-baskets, and define case stages. You will work with case types, tasks, and workflows. This course includes some guidelines on solution design principles. After completing this course, you can build on these skills by taking more advanced or specialized courses in security, user-interface customization, and solution deployment. Build and Deploy a Solution Build a solution Deploy a solution Test a solution Manage roles Redeploy a solution Create Properties and Document Classes Create case properties Create task properties Create a business object Create document classes Create Roles and In-Baskets Create roles Create in-baskets Create Tasks Create a to-do task Create a container task Add the to-do list widget to the Case Details pag Create a Step Map Open a task in Step Designer Create a step map Add a workgroup to a step map Add an attachment to a step map Use Preconditions and Sets Organize tasks with preconditions Organize tasks with inclusive sets Organize tasks with exclusive sets Automate Case Packaging Open a task in Process Designer Add a component step to a task Use a component step to package a case Add Case Stages Add case stages to a solution Use a system step to perform a case stage operation Use a case stage as a task precondition Solution Design Principles Describe solution design principles