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Duration 5 Days 30 CPD hours This course is intended for This course is designed for technology leaders, solution developers, project managers, organizational decision makers, and other individuals seeking to demonstrate a vendor-neutral, cross-industry understanding of ethics in emerging data-driven technologies, such as AI, robotics, IoT, and data science. This course is also designed for professionals who want to pursue the CertNexus Certification Exam CET-110: Certified Ethical Emerging Technologies. Overview In this course, you will incorporate ethics into data-driven technologies such as AI, IoT, and data science. You will: Describe general concepts, theories, and challenges related to ethics and emerging technologies. Identify ethical risks. Practice ethical reasoning. Identify and mitigate safety and security risks. Identify and mitigate privacy risks. Identify and mitigate fairness and bias risks. Identify and mitigate transparency and explainability risks. Identify and mitigate accountability risks. Build an ethical organization. Develop ethical systems in technology-focused organizations. Mutually reinforcing innovations in computing and engineering are catapulting advances in technological production. From blockchain and artificial intelligence (AI) to gene editing and the Internet of Things (IoT), these advances come with tremendous opportunities for improvement in productivity, efficiency, and human well-being. But as scandals increasingly demonstrate, these advances also introduce new and serious risks of conflict and harm.Technology professionals now face growing demands to identify and mitigate ethical risks to human rights and the environment, as well as to navigate ethical tradeoffs between qualities such as privacy and accuracy, fairness and utility, and safety and accountability. This course provides the tools to identify and manage common ethical risks in the development of emerging data-driven technologies. It distills ethical theory, public regulations, and industry best practices into concrete skills and guidelines needed for the responsible development of digital products and services. By following the course's practical, problems-based approach, learners will become adept at applying theories, principles, frameworks, and techniques in their own roles and organizations. Introduction to Ethics of Emerging Technologies Topic A: What?s at Stake Topic B: Ethics and Why It Matters Topic C: Ethical Decision-Making in Practice Topic D: Causes of Ethical Failures Identifying Ethical Risks Topic A: Ethical Reasons Topic B: Stumbling Blocks for Ethical Reasoning Topic C: Identify Ethical Risks in Product Development Topic D: Tools for Identifying Ethical Risks Topic E: Use Regulations, Standards, and Human Rights to Identify Ethical Risks Ethical Reasoning in Practice Topic A: Ethical Theories Topic B: Use Ethical Decision-Making Frameworks Topic C: Select Options for Action Topic D: Avoid Problems in Ethical Decision-Making Identifying and Mitigating Security Risks Topic A: What Is Security? Topic B: Identify Security Risks Topic C: Security Tradeoffs Topic D: Mitigate Security Risks Identifying and Mitigating Privacy Risks Topic A: What Is Privacy? Topic B: Identify Privacy Risks Topic C: Privacy Tradeoffs Topic D: Mitigate Privacy Risks Identifying and Mitigating Fairness and Bias Risks Topic A: What Are Fairness and Bias? Topic B: Identify Bias Risks Topic C: Fairness Tradeoffs Topic D: Mitigate Bias Risks Identifying and Mitigating Transparency and Explainability Risks Topic A: What Are Transparency and Explainability? Topic B: Identify Transparency and Explainability Risks Topic C: Transparency and Explainability Tradeoffs Topic D: Mitigate Transparency and Explainability Risks Identifying and Mitigating Accountability Risks Topic A: What Is Accountability? Topic B: Identify Accountability Risks Topic C: Accountability Tradeoffs Topic D: Mitigate Accountability Risks Building an Ethical Organization Topic A: What Are Ethical Organizations? Topic B: Organizational Purpose Topic C: Ethics Awareness Topic D: Develop Professional Ethics within Organizations Developing Ethical Systems in Technology-Focused Organizations Topic A: Policy and Compliance Topic B: Metrics and Monitoring Topic C: Communication and Stakeholder Engagement Topic D: Ethical Leadership

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

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 4 Days 24 CPD hours This course is intended for This course is for network and system administrators, IT managers, IT support personnel, and other network operations staff who are responsible for deploying new computers across their organizations, managing ongoing software and hardware configuration tasks for computers, and retiring outdated computers. Overview By the completion of this course, you will be able to: Install and configure Ghost Solution Suite 3.0. Use the Ghost Console to create and use jobs and tasks to manage computes. Configure image deployments. Manage ?unknown? and predefined computers. Perform disk wipes and create disk partitions. Create Windows scripted OS installations. Create PC transplant templates. Capture a computer personality, and deploy personality packages. Perform a computer migration from Win 7 to Win 8.1. This course is designed for the professional tasked with installing, configuring, and managing a Deployment Solution system. Overview of Endpoint Lifecycle Management Introduction to Endpoint Lifecycle Management Phases of Endpoint Lifecycle Management ELM Business Objectives and Goals ELM Solution Mapping to Business Objectives Ghost Solution Suite 3.0 Product Overview Implementation Assessment ELM Requirements Gathering Solution Analysis of ELM Requirements Implementation Design GSS 3.0 Technical Overview Installation Options and Prerequisites Defining the Solution Infrastructure Defining the ELM Solution Configuration Installation and Configuration of the ELM Solution Base Software Installation Navigating the Console Core & Solution Configuration Driver Management Pre-boot Environment Endpoint Identification & Gathering IT Requirements Overview Analyzing and Defining IT Requirements Using ELM to Forecast IT Requirements Endpoint Configuration Standards Endpoint Standards Overview Defining Endpoint Standards Implementation of Endpoint Standards Endpoint Provisioning Endpoint Provisioning Overview Standard Build and Image Methodology Software Compatibility Analysis Software Packaging requirements for use in the ELM Solution Software Quality Assurance Methodology Endpoint Deployment & Staging Endpoint Lifecycle Automation Endpoint Lifecycle Automation Scenario Exercise Backup and restore Automating the backup of a computer image Scripted OS Installation Capturing an image for deployment Automating the creation of a master image Automating the deployment of computer images Software Distribution Software Delivery Methods Software Installation Methods Understanding Software Delivery Reporting and Analysis of Software Distribution Tasks Image and Build Maintenance Image maintenance overview Restoring a computer image Capturing the updated image Updating Jobs Managing Software Upgrades Software Upgrade Process Overview Distribution of Software Updates Supporting the Business Ensuring Business Continuity in an ELM System Endpoint Restoration/Recovery Managing Service Support Activities Endpoint Monitoring & Alerting Endpoint Configuration & Maintenance Automating Problem Resolution Application Self-Healing Desired State Management Hardware Refresh & Migration Hardware Refresh & Migration Process Overview Personality Capture and Restore Gathering Current State Inventory for Requirements and Planning Activities Performing Data capture and storage activities Gathering User state or PC personality information Automating the Migration Process Endpoint Retirement/Disposal Ensuring Compliant Disposal Methods and Procedures End to End Endpoint Lifecycle Use Case Endpoint Management Lifecycle Use Case for GSS Additional course details: Nexus Humans Symantec Ghost Solution Suite 3.0 - Administration 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 Symantec Ghost Solution Suite 3.0 - Administration course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for System administrators System engineers Migration engineers Migration architects Overview By the end of the course, you should be able to meet the following objectives: Describe core VMware HCX use cases and common triggers for mobility Describe the core components and features of VMware HCX Describe a real-life example of a VMware HCX project Identify all major Cloud Providers offering and supporting VMware HCX Describe the features of VMware HCX services Explain the different deployment types for VMware HCX and choose the correct components to deploy for a particular use case Understand the resource, network, and VMware ESXi™ and VMware vCenter requirements for VMware HCX Install and configure VMware HCX Understand, deploy, and manage the HCX Service Mesh Understand Network Extension and Traffic Engineering Create Network Extension and enable Mobility Optimized Networking Understand WAN Optimization Understand the different migration types and be able to choose the best one for different applications and workloads Incorporate VMware HCX into a disaster recovery strategy Design a VMware HCX deployment for different use cases Manage the lifecycle of VMware HCX This four-day course gives you knowledge and practical exercises sufficient to manage VMware HCX© and to migrate virtual machines using VMware HCX. The course focuses on configuration and management of VMware HCX. The course equips system administrators with the knowledge, skills, and abilities to achieve competence in migrating virtual machines. Course Introduction Introductions and course logistics Course objectives Introduction to VMware HCX Describe workload mobility challenges that VMware HCX addresses Recognize use cases for VMware HCX Identify all major Cloud providers offering and supporting VMware HCX HCX Services and Deployment Types Describe the functions of VMware HCX components Recognize the services provided by VMware HCX Recognize when to use different deployment types for VMware HCX Be able to choose which components to install and configure for a different VMware HCX service HCX Deployment Identify the resource, network, and ESXi/VMware vCenter server requirements for VMware HCX Understand the VMware vCenter user roles and access requirements Describe the installation workflow Install, activate, and configure VMware HCX manager Understand the compute and network profile requirements for VMware HCX and its services Create site pair, compute, and network profiles Describe and manage the HCX Service Mesh Create and configure a HCX Service Mesh Network Extension Describe network extension use case and benefits Compare the HCX-Network extension service with other solutions Examine Network Extension capabilities and topology Create a Network Extension Describe network traffic packet flow Describe Mobility Optimized Networking Enable Mobility Optimized Networking Describe the TCP Flow Conditioning and Application path resiliency feature of VMware HCX Recognize the key benefits of TCP flow conditioning and Application path resiliency Describe WAN optimization Workload Mobility Describe different migration types Recognize the limitation of each migration method and consideration when planning a migration Understand Bulk and Replication Assisted VMware HCX© vMotion© migration methods Migrate a VM using Bulk migration Describe cold and vMotion migration method Migrate a VM using HCX vMotion migration Examine non VMware vSphere© workload migration Migrate a VM using an OS assisted migration method Business Continuity and Disaster Recovery Examine disaster recovery concepts Describe disaster recovery networks Plan and create disaster recovery networks Describe VM protection operations Protect, recover, and test recovery and reverse replication of a VM Understand VMware HCX and SRM integration and value HCX Lifecycle Management Backup and restore the VMware HCX manager Locate and access VMware HCX logs Troubleshoot VMware HCX Plan for VMware HCX manager and component updates Customer Design Scenarios Design a VMware HCX deployment Choose workload mobility methods for the migration Discuss customer requirements and proposed design Discuss components, services, and migration methods for the scenario

Duration 5 Days 30 CPD hours This course is intended for Experienced Programmers and Systems Administrators. Overview Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. This course is ?skills-centric?, designed to train attendees in core Python and web development skills beyond an intermediate level, coupling the most current, effective techniques with best practices. Working within in an engaging, hands-on learning environment, guided by our expert Python practitioner, students will learn to: ? Create working Python scripts following best practices ? Use python data types appropriately ? Read and write files with both text and binary data ? Search and replace text with regular expressions ? Get familiar with the standard library and its work-saving modules ? Use lesser-known but powerful Python data types ? Create 'real-world', professional Python applications ? Work with dates, times, and calendars ? Know when to use collections such as lists, dictionaries, and sets ? Understand Pythonic features such as comprehensions and iterators ? Write robust code using exception handling An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features. An Overview of Python What is python? 1 -- An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows Editors and IDEs Getting Started Using variables Built-in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings The standard library The sys module Launching external programs Math functions Random numbers The string module Reading CSV data Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the file system Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations 17 ? Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network services Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Parsing command-line options Detecting the current platform Trapping signals Implementing logging Python Timeline Advantages/Disadvantages of Python Getting help with pydoc

Duration 2 Days 12 CPD hours This course is intended for A prior understanding of EU Data Protection legislation is recommended. Candidates are typically management professionals and decision-makers who already have responsibility for data protection compliance within their organisation.Co-Requisite Subjects Candidates should have a good understanding of their own organisation?s data management activities through the life cycle from initial acquisition, through the various areas of processing and usage, to eventual removal or destruction. Overview To equip the learner with a foundational understanding of the principles of the General Data Protection Regulation (GDPR) and to provide constructive suggestions on implementing compliant processes. The social, historical and legal background leading to the General Data Protection Regulation (GDPR) The scope and global context of the GDPR The key concepts within the GDPR The definition of all key words and phrases relating to this Data Protection regulation Principle One: The criteria governing fair, open and transparent processing of personal data Principle Two: Purpose Limitation, the challenge of limiting the processing within the context of specified and lawful purposes Principle Three: Minimisation of processing, and ensuring that only that data is processed which is necessary to achieve the purpose. Principle Two: Purpose Limitation, the challenge of limiting the processing within the context of specified and lawful purposes Principle Three: Minimisation of processing, and ensuring that only that data is processed which is necessary to achieve the purpose. Principle Four: Ensuring that any personal data held by the organisation is kept accurate and current, and that any processing of such data is appropriate Principle Five: Management and storage of personal data in a manner that meets regulatory obligations, while minimising the time that the individual remains identifiable Principle Six: The criteria governing safe, secure and confidential processing of personal data in order to protect its integrity Principle Seven: The key roles, responsibilities and accountabilities of those involved in Data Management within an organisation Establishment within a single Member State Joint Controllers Privacy by Design and by Default Nominated Representatives Third-party Contracts and shared liability Logging of data management processes Data Breach Notification obligations Privacy Impact Assessments Overseas transfer of personal data L2.8 The Data Subject Rights, and their implications for the Data Controller and the Data Processor L2.8.1 The ?right to be forgotten? L2.8.2 The right to restriction of processing L2.8.3 The right to object to certain processing L2.8.4 The right to have inaccurate data amended or erased L2.8.5 The right to data portability L2.8.6 The right of access to one?s personal data L2.8.7 Rights in relation to automated decision-making and profiling The role of the Data Protection Officer (DPO) The role of the Data Protection Officer (DPO) Criteria for designating a DPO Tasks of the DPO Position of the DPO within the organisation The role of the Supervisory Authority within the Member State The Lead Supervisory Authority and independence Investigative, corrective and advisory powers Independence of the Supervisory Authority Collaboration with other Supervisory Authorities Codes of Conduct and Certification The role, powers and tasks of the European Data Protection Board (EDPB) The remedies, liabilities and penalties available under the GDPR Right to raise a complaint Right to representation Right to effective judicial remedy Right to compensation and liability Administrative fines of up to ?10m or 2% of GAT Administrative fines of up to ?20m or 4% of GAT Provisions for specific processing situations Freedom of Expression Processing of official documents Processing of National Identification Numbers Processing regarding employment Processing for archiving purposes Processing under obligations of official secrecy Processing of data by religious organisations Preparing for implementation of the GDPR Review of data management policies and procedures Review of data assets and security structures Training and Awareness-raising Data management governance structures Embedding Privacy By Design and Default Codes of Conduct and Certification against standards Breach detection and notification procedures Review of third-party agreements, contracts

Duration 3 Days 18 CPD hours This course is intended for This class is ideal for integration specialists or Salesforce Administrators who want to learn more about connecting and securing data in Tableau CRM. This course is also great for business analysts or developers interested in creating advanced dashboards. Overview When you complete this course, you will be able to: Determine your user, data, and security requirements, and establish a development process. Set up apps and control what users can do in Tableau CRM by assigning them licenses, permission sets, and app permissions. Load external data to Tableau CRM. Create and run dataflows to load Salesforce data, and join it with data from other datasets. Understand and use Data Sync effectively. Understand Recipes and Data Prep. Understand and implement data security in Tableau CRM, and override security for implementation and testing. Understand how filters on dashboards function and be able to use interactions when necessary. Understand a dashboard's JSON file. Explain the process of dashboard queries and modify a query to meet specific analytic requirements. Modify dataset metadata. Take your Tableau CRM skills to the next level. In this 3-day, expert-led class, you?ll learn how to develop and implement a Tableau CRM environment that contains both Salesforce and non-Salesforce data. Our team of experts will walk you through Tableau CRM features and settings, user setup, how to load and transform data, data security, and how to modify queries to customize dashboards so you can work more efficiently, spot trends, and predict outcomes faster. Discovery and Planning Discovery Meeting Establishing Your Users and Development Process Set Up Users and Apps Overview of User Access on the Tableau CRM Platform Creating Tableau CRM Permission Sets Assigning Licenses and Permission Sets to Users Creating and Sharing Tableau CRM Apps Connect Data Overview of Connecting Data Data Mapping Overview of the Dataflow Process Designing a Dataflow Loading External CSV Data Creating Dataflows Optimizing Dataflows Running, Monitoring, and Scheduling a Dataflow Preparing Datasets with Recipes with Data Prep Data Connectors Additional Transformations Data Security Overview of Security in Tableau CRM Determining Security Requirements Overview of Using Predicate Filters Implementing Ownership-Based Row-Level Security Implementing Role-Based Row-Level Security Implementing Team-Based Row-Level Security Overriding Security for Implementation and Testing Sharing Inheritance Extended Metadata in a Dataset Overview of Extended Metadata (XMD) Updating Field Metadata Adding Quick Action Menus for Records in Tableau CRM Dashboard Templates and Mobile Dashboards Overview of Tableau CRM Dashboard Templates Overview of JSON for Dashboards Building a Dashboard Using a Template Optimizing Dashboards for a Mobile Device Bindings in Dashboards Understanding Filters in Lenses and Dashboards Multi-Dataset Dashboards Filters with Interactions Custom Queries Query Modification Overview of Modifying Queries Maximizing the Use of the Compare Table Salesforce Analytics Query Language (SAQL) SAQL Queries in a Tableau CRM Dashboard Additional course details: Nexus Humans Salesforce Implement and Manage Tableau CRM (ANC301) 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 Implement and Manage Tableau CRM (ANC301) 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 intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 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.