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Duration 3 Days 18 CPD hours This course is intended for Channel and Customer Engineers Network Engineer System Engineer Wireless Engineer Consulting Systems Engineer Technical Solutions Architect Network Admisnistrator Wireless Design Engineer Network Manager Channel SEs Sales Engineer Channel AMs Account Manager Overview Upon completing this course, students will be able to meet these objectives: Understand the overall architecture of the Cisco security solutions and how APIs help enable security Understand how to use Cisco Firepower APIs Understand how pxGrid APIs function and their benefits Understand what capabilities the Cisco Stealthwatch APIs offer and construct API requests to them for configuration changes and auditing purposes Understand the features and benefits of using Cisco Stealthwatch Cloud APIs Learn how to use the Cisco Umbrella Investigate API Understand the Functionality provided by Cisco AMP and its APIs Learn how to use Cisco Threat Grid APIs to analyze, search, and dispose of threats This course demonstrates the tools and the benefits of leveraging programmability and automation in Cisco Security Solutions, including Cisco Firepower Management Center, Cisco Firepower Threat Defense, Cisco ISE, Cisco pxGrid, Cisco Stealthwatch Enterprise, Cisco Stealthwatch Cloud, Cisco Umbrella, Cisco AMP, Cisco Threat grid, and Cisco Security Management Appliances. Students will learn how to use the API for each Cisco security solution and specific applications of when the API benefits IT security content. Introducing Cisco Security APIs Role of APIs in Cisco Security Solutions Cisco Firepower, Cisco ISE, Cisco pxGrid, and Cisco Stealthwatch APIs Use cases and security workflow Consuming Cisco Advanced Malware Protection APIs Cisco AMP overview Cisco AMP endpoint API Cisco AMP use cases and workflows Discovery 1: Query Cisco AMP endpoint APIs for verifying compliance Using Cisco ISE Introducing Cisco Identity services engine Cisco ISE use cases Cisco ISE APIs Using Cisco pxGrid APIs Cisco pxGrid overview WebSockets and STOMP messaging protocol Discovery 2: Use the REST API and Cisco pxGrid with Cisco Identity services engine Using Cisco Threat Grid APIs Cisco threat grid overview Cisco threat grid API Cisco threat grid use cases and workflows Discovery 3: Construct a Python script using the Cisco threat grid API Investigating Cisco Umbrella Security Data Programmatically Cisco Umbrella investigate API overview Cisco Umbrella investigate API: Details Discovery 4: Query security data with the Cisco Umbrella investigate API Exploring Cisco Umbrella Reporting and Enforcement APIs Cisco Umbrella reporting and enforcement APIs: Overview Cisco Umbrella reporting and enforcement APIs: Deep dive Discovery 5: Generate reports using the Cisco Umbrella reporting API Automating Security with Cisco Firepower APIs Review basic constructs of Firewall policy management Design policies for automation Cisco FMC APIs in depth Discovery 6: Explore the Cisco Firepower management center API Cisco FTD automation with ansible Discovery 7: Use ansible to automate Cisco Firepower threat defense configuration Cisco FDM API in depth Discovery 8: Automate Firewall policies using the Cisco Firepower device manager API Operationalizing Cisco Stealthwatch and Its API Capabilities Cisco Stealthwatch overview Cisco Stealthwatch APIs: Details Discovery 9: Automate alarm policies and create reports using the Cisco Stealthwatch APIs Using Cisco Stealthwatch Cloud APIs Cisco Stealthwatch Cloud overview Cisco Stealthwatch Cloud APIs: Deep dive Discovery 10: Construct a report using Cisco stealthwatch Cloud APIs Describing Cisco Security Management Appliance APIs Cisco SMA APIs overview Cisco SMA API Discovery 11: Construct reports using Cisco SMA APIs

Duration 3 Days 18 CPD hours This course is intended for This advanced course is for Infrastructure Specialist, Senior Technical Specialist,Technical Specialist, Support Engineers, and System Architects. Overview Understand the MDM Architecture and how the Physical, Virtual and Hybrid MDM handles a service request Understand the core Workbench features available for the InfoSphere MDM Understand how MDM using OSGi for deploying customizations to the product Create a new Physical MDM Entity using the Workbench Wizard Extend an existing Physical MDM Entity using the Workbench Wizard Extend an existing Physical MDM Service using the Workbench Wizard Create a new Composite Service using a transiant object containing other existing business objects Customize and deploy a Virtual configuration Create a new Virtual Callout Handler Create a new Virtual Composite View Generate new Services based on the Virtual configuration (eSOA) Customize a Hybrid MDM implementation Understand the Adaptive Service Interface (ASI) This course is designed for anyone who wants to get an understanding of how to use and customize the InfoSphere Master Data Management using the InfoSphere MDM Workbench InfoSphere MDM Architecture . OSGi and MDM . Data Additions . Physical Data Extensions . MDM Physical Behavior Extensions . Composite Services . Adaptive Services Interface (ASI) . Virtual Data Model . Virtual Handlers . eSOA Toolkit . Hybrid MDM .

Duration 1 Days 6 CPD hours This course is intended for This course provides an introductory overview of the CMMC program for organizational decision makers. Business and IT leaders and IT staff might consider taking this course to learn about the CMMC Model to get a sense of what's required for a successful assessment, and the various ways they can start preparing. Overview In this course, you will identify the key elements and potential impacts of the Cybersecurity Maturity Model Certification (CMMC) program. You will: Identify the crucial elements that are driving the CMMC initiative. Describe the architecture of the CMMC Model and the rationale behind it. Prepare your organization for a successful CMMC Assessment. Identify the roles and responsibilities in the CMMC ecosystem and describe the phases of an Assessment. The Cybersecurity Maturity Model Certification (CMMC), managed by The Cyber AB (formerly known as the CMMC Accreditation Body or the CMMC-AB), is a program through which an organization's cybersecurity program maturity is measured by their initial and ongoing compliance with applicable cybersecurity practices. This course provides a complete review of the key elements of this important program and will entitle you to a CMMC Trailblazer badge.Important: This curriculum product is not considered CMMC-AB Approved Training Material (CATM). This course is not intended as certification preparation and does not qualify students to sit for the CMMC CP certification exam. Identifying What's at Stake Topic A: Identify the Threats and Regulatory Responses Topic B: Identify Sensitive Information Describing CMMC Topic A: Describe the CMMC Model Architecture Topic B: Describe the CMMC Program Getting Ready for a CMMC Assessment Topic A: Scope Your Environment Topic B: Analyze the CMMC Assessment Guides Topic C: Foster a Mature Cybersecurity Culture Topic D: Identify Helpful Documents Topic E: Evaluate Your Readiness Interacting with the CMMC Ecosystem Topic A: Identify the CMMC Ecosystem Topic B: Describe a CMMC Assessment

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Artificial Intelligence brings exciting new opportunities to the field of Conversational User Interfaces (CUI). Learn key concepts and proven design methods to deliver cutting-edge experiences and reach better business outcomes. Silvia Podesta is a Designer in the Client Engineering Team at IBM Nordics. She leverages design thinking, service and UX design to help clients identify opportunities for innovation and pioneer transformational experiences through IBM technology.

About UX Academy: UX Academy provides live online hands-on training to help you take the next step in your career no matter what level you’re at. Offering Beginner, Intermediate UX courses, Product Design, Strategy and Voice Design developed in collaboration with Amazon.

Duration 5 Days 30 CPD hours This course is intended for This intermediate course is for future DB2 for z/OS database administrators who need to acquire the basic skills required to administer a DB2 database. Overview Implement a DB2 database designUse database utilities to load and reorganize dataDefine and implement a DB2 database recovery strategyControl access to database using DB2 authorization facilities This course provides students with instruction on how to physically implement a logical database design in DB2. The course includes instruction on DB2 data management, DB2 catalog tables, the bind process, database utilities, & security considerations. Course Outline Setting up a DB2 database Referential integrity Getting data into and out of DB2 Keeping your DB2 data in good shape Application data recovery basics Program preparation and Bind Security Serialization Additional course details: Nexus Humans CV832 IBM DB2 11 for z/OS Database Administration Workshop Part 1 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 CV832 IBM DB2 11 for z/OS Database Administration Workshop Part 1 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 4 Days 24 CPD hours This course is intended for This class is designed for enterprise architects, solution architects, and business analysts working to earn their Salesforce Application Architect credential, or for application architects looking to get more hands-on experience. Overview Design data models that scale gracefully Leverage Salesforce sharing mechanisms at an advanced level Evaluate the nuances of field types and pick the right one for the circumstances Make data model decisions that minimize record locking and other performance degradations Dive into the two cornerstone domains of being an Application Architect: Data Architecture and Management, and Sharing and Visibility. In this 4-day workshop, our Architect experts will present you with a case study scenario that will be broken down and digested through iterative exploration. Learn how to design and build secure, scalable, and high-performing solutions through a combination of lecture, demos, hands-on exercises, and workshop presentations and discussions. Application Architect Overview Assess the Requirements to Become an Application Architect Understand the Real-World Expectations of Application Architects Review the Core Characteristics of Successful Application Architects Scenario Introduction Review the Application Architecture Scenario Identify Scenario Problem Areas Identify Scenario Actors and Licensing Architecture Documentation Understand Key Architecture Documentation Requirements Learn About Best Practices for Artifact Documentation Produce Architecture Documents Data Modeling Identify Relationship Types and Their Impact on Record Access, User Interface, and Reporting Review the Considerations for Changing Field Types Review the Considerations for Modifying Data Models with Schema Builder Review the Considerations for Importing and Exporting Data Identify Use Cases of External Objects Determine an Appropriate Data Model Understand Design Implications with Complex Environments and Large Data Volumes (LDV) Data Management Review the Considerations for Working with LDV Review Data Lifecycle Concepts and Mechanisms Review Master Data Management and System of Record Concepts Review Data Migration, Planning, Preparation, and Execution Identify Potential LDV and Calculate Expected Volumes Go Further with Indexes Standard and Custom Skinny Tables Lock Records Security Model Review the Considerations for Working with Internal and External Sharing Models Restrict and Extend Object and Field Access Determine Sharing Solutions Identify Record Sharing Mechanisms (Declarative, Programmatic, Implicit) Understand Teams Concepts (Account, Opportunity, Case) Understand Person Accounts and Its Implication on Sharing Encrypt Data Sharing in Communities Understand Community Security Mechanisms Secure Integration Endpoints Integrate and Specify Connected Apps and Named Credentials Advanced Security & Visibility Concepts Implement Security & Visibility Controls with Apex and Visualforce Review Territory Management and Its Implication on Data Management, Sharing, and Visibility Review Divisions and Its Implication on Data Management, Sharing, and Visibility Understand Security and Visibility Controls on 'Special' Objects Solution Design Determine When to Leverage Standard Products Functionality vs. Custom Build vs. AppExchange Understand Declarative and Programmatic Configuration Get to Know the Order of Execution Automate Business Processes Consider Reporting and Analytics Needs Consider How to Store and Access Content/Files Apply Solution Design Concepts to Real-World Problems and Scenarios Deployment & Integration Best Practices Review the Application Lifecycle Understand How Sandboxes Should Be Used Review Deployment Options Identify Integration Patterns Wrap-up Review a Practice Scenario Review What Was Covered Additional course details: Nexus Humans Salesforce Build Application Architect Expertise (ARC901) 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 Salesforce Build Application Architect Expertise (ARC901) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This class is designed for administrators preparing to take the Salesforce Marketing Cloud Administrator exam who are able to configure Marketing Cloud products using industry and product best practices. You should be generally familiar with data structure in subscriber data management. You should also be able to thoroughly navigate Setup, troubleshoot account configuration, and manage user requests. Overview When you complete this course, you will be able to: Recall exam objectives. Discuss product features and functionality covered on the exam. Assess your exam readiness by answering practice questions. Familiarize yourself with additional resources necessary to prepare for the exam. Take the next step in your career and become a Salesforce Certified Marketing Cloud Administrator. In this 1-day, expert-led certification prep class, boost your exam readiness with a detailed exam overview, exam resources, and practice exam questions to test your knowledge. This course includes a voucher to sit for the Salesforce Marketing Cloud Administrator exam. Course Outline Exam Overview Digital Marketing Proficiency Review Governance and Compliance in Relation to Digital Marketing Review Security Best Practices for Date, Permissions, and PII Review Marketing Cloud Product Inventory and Offerings Subscriber Data Management Review the Contact Model Review Data Quality Evaluation Review Preference and Profile Center Setup Review Business Units, Users, and Security Configuration Review Integrations Configuration Review Features in Setup Home Review Marketing Cloud Extension Products Channel Management Review Mobile Studio Configuration Review Email Studio Configuration Review Social Studio and Advertising Configuration Review Journey Builder Concepts and Use Cases Maintenance Review Data Extraction and Report Generation Solutions Review Monitoring and System Availability Review Additional Marketing Cloud Product Benefits Practice Exam and Wrap-up Complete a Practice Exam Review Next Steps