8170 Power courses

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 3 Days 18 CPD hours This course is intended for Administrators or application owners who are responsible for deploying and managing Kubernetes clusters and workloads Overview By the end of the course, you should be able to meet the following objectives: Describe the VMware Tanzu Mission Control architecture Configure user and group access Create and manage Kubernetes clusters Control access Create image registry, network, quota, security, custom and mutation policies Connect your on-premises vSphere with Tanzu Supervisor to VMware Tanzu Mission Control Create, manage, and back up VMware Tanzu Kubernetes Grid™ clusters Create and manage Amazon Elastic Kubernetes Service clusters Perform cluster inspections Manage packages in your clusters Monitor and secure Kubernetes environments During this two-day course, you focus on using VMware Tanzu© Mission Control? to provision and manage Kubernetes clusters. The course covers how to apply image registry, network, security, quota, custom, and mutation policies to Kubernetes environments. It focuses on how to deploy, upgrade, back up, and monitor Kubernetes clusters on VMware vSphere© with VMware Tanzu©, and it also covers package management using the VMware Tanzu Mission Control catalog. Course Introduction Introduction and course logistics Course Objectives What Is VMware Tanzu Mission Control Describe VMware Tanzu Mission Control Describe vSphere with Tanzu Describe Tanzu Kubernetes Grid Describe VMware Tanzu© for Kubernetes Operations Explain how to request access to VMware Tanzu Mission Control Describe VMware Cloud? services Describe the VMware Cloud services catalog Explain how to access VMware Tanzu Mission Control Identify the components of VMware Tanzu Mission Control Explain the resource hierarchy of VMware Tanzu Mission Control Access, Users, and Groups Explain VMware Cloud services and enterprise federation Describe VMware Cloud services roles Explain multifactor authentication Describe the VMware Tanzu Mission Control UI List the components of the VMware Tanzu Mission Control UI Describe the VMware Tanzu CLI Describe the VMware Tanzu Mission Control API Cluster Lifecycle Management Outline the steps for registering a management cluster to VMware Tanzu Mission Control Discuss what a management cluster is Describe provisioners Explain the purpose of a cloud provider account Describe Amazon Elastic Kubernetes Service Describe Azure Kubernetes Service Workload Clusters Describe Tanzu Kubernetes Grid workload clusters Explain how to create a cluster Explain how to configure a cluster Describe Amazon Elastic Kubernetes Service workload clusters Describe Azure Kubernetes Service workload clusters Explain how to attach a Kubernetes cluster Explain how to verify the connections to the cluster Describe cluster health Policy Management Explain how access policies grant users access to different resources Describe the policy model Describe the available policy types Explain how image registry policies restrict from which image registries container images can be pulled Outline how network policies are applied to clusters Discuss how security policies control deployment of pods in a cluster Discuss how quota policies manage resource consumption in your clusters Discuss how custom policies implement specialized policies that govern your Kubernetes clusters Describe mutation policies Explain how Policy Insights reports VMware Tanzu Mission Control policy issues Control Catalog Describe the VMware Tanzu Mission Control catalog Explain how to install packages Describe cert-manager Explain Service Discovery and ExternalDNS Describe Multus CNI and Whereabouts Describe Fluent-Bit Explain Prometheus and Grafana Describe Harbor Describe Flux Describe Helm Describe Git repositories Tanzu Mission Control Day 2 Operations Describe data protection Describe cluster inspections Explain life cycle management Describe VMware Aria Operations? for Applications Discuss VMware Tanzu© Service Mesh? Advanced edition Describe VMware Aria Cost? powered by CloudHealth©

Duration 2 Days 12 CPD hours This course is intended for Workspace ONE administrators, account managers, solutions architects, solutions engineers, sales engineers, technical support engineers, and consultants Overview By the end of the course, you should be able to meet the following objectives: Summarize the basic troubleshooting methodologies Outline common troubleshooting techniques in the Workspace ONE UEM console Outline common troubleshooting techniques when integrating enterprise solutions in the Workspace ONE UEM console Summarize common troubleshooting strategies for Workspace ONE UEM managed devices Outline common application management troubleshooting techniques in the Workspace ONE UEM console Summarize common troubleshooting techniques for email management in the Workspace ONE UEM console Explain common troubleshooting approaches for the VMware Unified Access Gateway™ platform and individual edge services Outline useful troubleshooting tools, such as the Self-Service Portal and VMware Workspace ONE Assist™ In this two-day course, you learn to investigate, analyze, and determine issues that might occur with all the different components of VMware Workspace ONE© UEM. Troubleshooting is the backbone of service maintenance and management. To effectively troubleshoot product issues, administrators must understand how product services communicate and function. This in turn helps optimize service and software health management. Course Introduction Introductions and course logistics Course objectives Fundamentals of Troubleshooting Workspace ONE UEM Outline software troubleshooting logic and support methods Summarize the main process flows for the Workspace ONE UEM components Explain the importance of Workspace ONE UEM process flows for troubleshooting Identify different Workspace ONE UEM log files Workspace ONE UEM Console Troubleshooting Outline the best practices for troubleshooting Workspace ONE UEM console issues Identify common group management and assignment-related issues Outline common issues for Workspace ONE UEM console roles and system settings Understand how analytic events can be used to identity platform errors Summarize the steps for collecting and analyzing Workspace ONE UEM console logs Integration Troubleshooting Outline the common enterprise integrations in Workspace ONE UEM Outline common troubleshooting techniques for the VMware AirWatch© Cloud Connector? Troubleshoot issues related to Directory Services integration Identify directory user and groups synchronization issues Troubleshoot issues related to certificate authority integration Explain VMware Workspace ONE© Access? integration and VMware Workspace ONE© Intelligent Hub troubleshooting techniques Endpoint Troubleshooting Compare the endpoint connection topologies in Workspace ONE UEM Outline useful tools and resources for endpoint troubleshooting Summarize the best practices for device enrollment troubleshooting Explain device connectivity troubleshooting techniques Understand how to identify and resolve profile-related issues Identify common compliance policy issues and potential root causes Applications Troubleshooting Explain the different scoping questions for troubleshooting applications Review application management configurations Summarize the general tools and resources for application troubleshooting Describe the general logic of troubleshooting public applications Understand internal application issues and potential causes Explain purchased application troubleshooting techniques Unified Access Gateway And Edge Services Troubleshooting Review Unified Access Gateway architecture and edge service workflows Understand Unified Access Gateway general configurations Explain how to utilize Unified Access Gateway related troubleshooting tools and resources Identify and resolve common issues for Content Gateway on Unified Access Gateway Summarize troubleshooting techniques for VMware Workspace ONE© Tunnel? on Unified Access Gateway Email Troubleshooting Review different email architecture and workflows Summarize common errors associated with email profiles Identify tools and resources for email troubleshooting Discuss troubleshooting techniques for VMware AirWatch© Secure Email Gateway? on Unified Access Gateway Outline PowerShell integration issues and techniques to address them Additional Troubleshooting Tools Describe how the Self-Service Portal helps administrators and empowers end-users to resolve issues Understand how Workspace ONE Assist can help endpoint troubleshooting

Duration 2 Days 12 CPD hours This course is intended for Security architects System designers Network administrators Operations engineers Network managers, network or security technicians, and security engineers and managers responsible for web security Cisco integrators and partners Overview After taking this course, you should be able to: Describe Cisco WSA Deploy proxy services Utilize authentication Describe decryption policies to control HTTPS traffic Understand differentiated traffic access policies and identification profiles Enforce acceptable use control settings Defend against malware Describe data security and data loss prevention Perform administration and troubleshooting This course shows you how to implement, use, and maintain Cisco© Web Security Appliance (WSA), powered by Cisco Talos, to provide advanced protection for business email and control against web security threats. Through a combination of expert instruction and hands-on practice, you?ll learn how to deploy proxy services, use authentication, implement policies to control HTTPS traffic and access, implement use control settings and policies, use the solution?s anti-malware features, implement data security and data loss prevention, perform administration of Cisco WSA solution, and more.This course helps you prepare to take the exam, Securing the Web with Cisco Web Security Appliance (300-725 SWSA). Describing Cisco WSA Technology Use Case Cisco WSA Solution Cisco WSA Features Cisco WSA Architecture Proxy Service Integrated Layer 4 Traffic Monitor Data Loss Prevention Cisco Cognitive Intelligence Management Tools Cisco Advanced Web Security Reporting (AWSR) and Third-Party Integration Cisco Content Security Management Appliance (SMA) Deploying Proxy Services Explicit Forward Mode vs. Transparent Mode Transparent Mode Traffic Redirection Web Cache Control Protocol Web Cache Communication Protocol (WCCP) Upstream and Downstream Flow Proxy Bypass Proxy Caching Proxy Auto-Config (PAC) Files FTP Proxy Socket Secure (SOCKS) Proxy Proxy Access Log and HTTP Headers Customizing Error Notifications with End User Notification (EUN) Pages Utilizing Authentication Authentication Protocols Authentication Realms Tracking User Credentials Explicit (Forward) and Transparent Proxy Mode Bypassing Authentication with Problematic Agents Reporting and Authentication Re-Authentication FTP Proxy Authentication Troubleshooting Joining Domains and Test Authentication Integration with Cisco Identity Services Engine (ISE) Creating Decryption Policies to Control HTTPS Traffic Transport Layer Security (TLS)/Secure Sockets Layer (SSL) Inspection Overview Certificate Overview Overview of HTTPS Decryption Policies Activating HTTPS Proxy Function Access Control List (ACL) Tags for HTTPS Inspection Access Log Examples Understanding Differentiated Traffic Access Policies and Identification Profiles Overview of Access Policies Access Policy Groups Overview of Identification Profiles Identification Profiles and Authentication Access Policy and Identification Profiles Processing Order Other Policy Types Access Log Examples ACL Decision Tags and Policy Groups Enforcing Time-Based and Traffic Volume Acceptable Use Policies, and End User Notifications Defending Against Malware Web Reputation Filters Anti-Malware Scanning Scanning Outbound Traffic Anti-Malware and Reputation in Policies File Reputation Filtering and File Analysis Cisco Advanced Malware Protection File Reputation and Analysis Features Integration with Cisco Cognitive Intelligence Enforcing Acceptable Use Control Settings Controlling Web Usage URL Filtering URL Category Solutions Dynamic Content Analysis Engine Web Application Visibility and Control Enforcing Media Bandwidth Limits Software as a Service (SaaS) Access Control Filtering Adult Content Data Security and Data Loss Prevention Data Security Cisco Data Security Solution Data Security Policy Definitions Data Security Logs Performing Administration and Troubleshooting Monitor the Cisco Web Security Appliance Cisco WSA Reports Monitoring System Activity Through Logs System Administration Tasks Troubleshooting Command Line Interface

Duration 5 Days 30 CPD hours This course is intended for Developed for experienced IT Professionals working with Citrix Virtual Apps and Desktops 7.1x. Potential students include administrators, engineers, and architects responsible for the end user workspace, provisioning services environment, and overall health and performance of the solution. Overview How to configure Workspace Environment Management to improve the end user environment and virtual resource consumption Understand Zones in Citrix Virtual Apps and Desktops 7.1x and how to account for user and desktop locations and optimal connection and registration How to build and manage App Layers to minimize image sprawl with Citrix Virtual Apps and Desktops 7.1x Understand and configure HDX channels and protocols for improved performance delivering multimedia and data over network connections Get more value out of your Citrix Virtual Apps and Desktops 7.1x investment through the use of Workspace Environment Management, Provisioning Services, Application Layering, and advanced features. Students leave this course with a good understanding of how to manage more complex solutions such as multizone environments spanning multiple locations with configurations around StoreFront, the Delivery Controllers, and HDX. Students will gain the skills to improve logon times, user personalization, and resource performance through Workspace Environment Management. Also, learn to optimize management of your app and desktop images by building and combining App Layers. End the course by learning to install, configure, and manage Provisioning Services in accordance with leading practices.This course includes a voucher to take the related exam (1Y0-311 Citrix XenApp and XenDesktop 7.15 Advanced Administration) and earn your Citrix Certified Professional - Virtualization (CCP-V) certification. Implementing Redundancy and Scalability StoreFront and Citrix Gateway Site Infrastructure Machines Running the Virtual Delivery Agent Managing a Virtual Apps and Desktops Environment with Multiple Locations Zones VDA Registration in a Multi-Zone Environment Zone Preference Optimal Gateway Routing and Zones Managing StoreFront Store Subscriptions in a Multi- Location Environment StoreFront and Citrix ADC Branding Implementing Backups and Disaster Recovery Backups Disaster Recovery Considerations Disaster Recovery Process Implementing Advanced Authentication Methods Multi-factor Authentication - RADIUS & OTP Multi-factor Authentication - Smart Card Authentication Federated Authentication - ADFS, SAML, and FAS Improving App and Data Security Introduction to Application Security Preventing Jailbreak Attacks Minimizing the Impact of Attacks Securing Machines Running the Virtual Delivery Agent TLS to VDA Encryption GPOs and Citrix Policies Image Management Introduction to Troubleshooting Troubleshooting Methodology Process (Standard Slide) Resource Tools and Utilities Introduction to PowerShell Troubleshooting Access Issues Troubleshooting StoreFront Troubleshooting Citrix Gateway Troubleshooting Delivery Controller Issues Validating FMA Services Troubleshooting VDA Registration Issues Troubleshooting VDA Registration Troubleshooting HDX Connection Issues Troubleshooting HDX Connections Introduction to App Layering App Layering Introduction Architecture and How it Works Creating an OS Layer The OS Layer Creating a Platform Layer The Platform Layer Creating App Layers The App Layers Creating Elastic App and User Layers Elastic App Layering User Layers Deploying a Layered Image using Citrix Virtual Apps and Desktops Using Templates in App Layering Using Layered Images in a Citrix Virtual Apps and Desktops Site Exploring Layer Priority Layer Priority Maintaining an App Layering Environment Updating Layers Maintaining and Updating the App Layering Environment Common App Layering Considerations and Additional Resources Introduction to Workspace Environment Management (WEM) Workspace Environment Management (WEM) Introduction WEM Administration Using WEM to Centralize Managing User Resources with WEM Managing Profiles with WEM Managing Endpoints with the WEM Transformer Feature Using WEM for Performance Optimization Optimizing Machine Performance with WEM Optimizing User Experience with WEM Using WEM to Secure Environments WEM Environments Migrating and Upgrading WEM Migrating to WEM Upgrading a WEM Deployment WEM Multi-Location Considerations

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

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 3 Days 18 CPD hours This course is intended for This course is intended for Information workers, IT Professionals and Developers. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. Overview Understand the features and tools that exist in Microsoft Dynamics 365 for Customizers Be aware of integrating complimenting Microsoft products such as SharePoint, Skpe for Business and Exchange Undertake and carry out the initial setup and configuration required in a Microsoft Dynamics 365 deployment Design and configure a comprehensive Security model using the inbuilt tools in Microsoft Dynamics 365 Customize the Dynamics 365 schema by creating custom Entities, Fields and Relationships Design custom Information Forms, Quick View Forms, Quick Create Forms and System Views Create System Charts, Dashboards and Interactive Experience Dashboards Create and manage Business Rules using the Business Rule Designer Plan, design and implement best practice Workflow, Business Process Flows and Custom Actions Be able to apply best practice methodology using Unmanaged and Managed Solutions to deploy Microsoft Dynamics 365 customizations and patches This course provides students with a detailed hands-on experience of setting up, customizing, configuring and maintaining the CRM components of Microsoft Dynamics 365. Attendees of this course will gain an in-depth understanding of the Dynamics 365 security model, learn how to customize the Dynamics 365 framework, create and maintain powerful workflows and business process flows and use solutions to package and deploy customizations across multiple Dynamics 365 environments. The course applies to both Business and Enterprise Editions of Dynamics 365 as well as Online and On-premise deployments. Introduction Getting familiar with the versions of Microsoft Dynamics CRM\365 Get acquainted with the Dynamics 365 framework Review the Dynamics 365 interfaces, devices and apps Understand the tools for Dynamics 365 customizers A brief overview of Solutions Understand the differences between Dynamics 365 organisations and environments Review further reading and resources Set up the lab environment - Acme Enterprises Event Management Solution Initial Setup and Configuration An introduction to Dynamics 365 online setup An introduction to Dynamics 365 on premise setup Review the System Settings area Understand how to configure Auto Save Settings Understand how to configure Format Settings Understand how to configure Email Settings Understand how to configure Skype Integration Understand how to configure SharePoint Integration Security Design and configure Business Units Configure Security Roles Manage Users and Teams Implement Access Teams Configure Hierarchy Security Creating and Managing Entities Introduction to the Dynamics 365 schema Review the different Entity Types Create new Custom Entities Managing Entity Ownership Managing Entity Properties Custom Entity Security Review Entities and Solutions Customizing Fields Introduction to Field Customization Understand the different Field Types Review Field Formats Create a new Field Review Fields and Solutions Implement a Calculated Field Configure Field Level Security Customizing Relationships and Mappings Introduction to Relationships Review the different Relationship Types Create a Relationship Review Relationships and Solutions Understand Relationship Behavior Implement a Hierarchy Relationship Configure Field Mappings Customizing Forms, Views and Visualizations The process to create a new Form Review the different Form types Using the Form Designer Customizing the Main, Quick View and Quick Create Forms Configure Form Security Review the different View types Customizing System Views Customizing System Charts and Dashboards Workflows, Business Process Flows and Custom Actions Introduction to Processes Workflow Business Process Flows Custom Actions Solution Management An introduction to Solution Management How to add and administer components in a Solution The differences between unmanaged and managed Solutions How to export and import a Solution How to set Managed Properties for a Solution What happens when you delete a Solution How to Clone a Solution Patch How to Clone a Solution

Duration 2 Days 12 CPD hours This course is intended for Data Protection Officers Data Protection Managers Auditors Legal Compliance Officers Security Manager Information Managers Anyone involved with data protection processes and programs Overview It will show the world that students know privacy laws and regulations and how to apply them, and that students know how to secure your place in the information economy. When students earn a CIPP credential, it means they've gained a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. The Certified Information Privacy Professional/United States (CIPP/US) program, developed by the International Association of Privacy Professionals (IAPP) - the world?s largest comprehensive global information privacy community and resource, was the first professional certification ever to be offered in information privacy. The CIPP/US credential demonstrates a strong foundation in U.S. privacy laws and regulations and understanding of the legal requirements for the responsible transfer of sensitive personal data to/from the U.S., the EU and other jurisdictions.This course will provide you with a foundational understanding of broad global concepts of privacy and data protection law and practice, including: jurisdictional laws, regulations and enforcement models; essential privacy concepts and principals; legal requirements for handling and transferring data and more. Introduction to privacy Modern history of privacy Introduction to personal information Overview of data protection roles Summary of modern privacy frameworks Structure of U.S. law Structure and sources of U.S. law and relevant terms Governmental bodies having privacy and information security authority General Data Protection Regulation overview (GDPR) High-level overview of the GDPR Significance of the GDPR to U.S. organizations Roles and responsibilities outlined in the law California Consumer Privacy Act of 2018 (CCPA) High-level overview of the newly passed California Consumer Privacy Act of 2018 Scope Consumer rights Business obligations Enforcement Enforcement of U.S. privacy and security laws Distinguishing between criminal and civil liability Comparing federal and state authority Theories of legal liability Enforcement powers and responsibilities of government bodies, such as the FTC and state attorneys general Information management from a U.S. perspective Developing a privacy program Role of privacy professionals and accountability Employee training User preferences Managing vendors Data classification Federal versus state authority Differences between federal and state authority Preemption Healthcare Privacy laws in healthcare Major components of HIPAA Development of HITECH Privacy protections mandated by other significant healthcare laws Financial privacy Goals of financial privacy laws Key concepts of FCRA, FACTA and GLBA Red Flags Rule, Dodd-Frank and consumer protection laws Education Privacy rights and protections under FERPA Recent amendments provided by PPRA and NCLBA Telecommunications and marketing Rules and regulations of telecommunications entities Laws that govern marketing Addressing privacy in the digital advertising Law enforcement and privacy Privacy laws on intercepting communication Telecommunications industry and law enforcement Laws ensuring rights to financial privacy National security and privacy Rules and regulations on intercepting communication Evolution of the law Collaboration of government agencies and private companies to improve cybersecurity Civil litigation and privacy Privacy issues related to litigation Electronic discovery, redaction and protective orders U.S. discovery rules versus foreign laws Legal overview of workplace privacy Federal and state laws regulating and protecting employee privacy Federal laws prohibiting discrimination Privacy before, during and after employment Lifecycle of employee privacy Background screening Employee monitoring Investigating misconduct and termination Antidiscrimination laws ?Bring your own device? policies State data security laws State laws impacting data security Social Security number use regulation Laws governing data destruction Data breach notification laws Scope of state data breach notification law Nine elements of state data breach notification laws Major differences in state laws