Duration 2 Days 12 CPD hours This course is intended for This class assumes some prior experience with Git, plus basic coding or programming knowledge. 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. Working in a hands-on learning environment led by our expert team, students will explore: Getting Started with Collaboration Understanding the GitHub Flow Branching with Git Local Git Configuration Working Locally with Git Collaborating on Your Code Merging Pull Requests Viewing Local Project History Streaming Your Workflow with Aliases Workflow Review Project: GitHub Games Resolving Merge Conflicts Working with Multiple Conflicts Searching for Events in Your Code Reverting Commits Helpful Git Commands Viewing Local Changes Creating a New Local Repository Fixing Commit Mistakes Rewriting History with Git Reset Merge Strategies: Rebase This is a fast-paced hands-on course that provides you with a solid overview of Git and GitHub, the web-based version control repository hosting service. While the examples in this class are related to computer code, GitHub can be used for other content. It offers the complete distributed version control and source code management (SCM) functionality of Git as well as adding its own features. It provides access control and several collaboration features such as bug tracking, feature requests, task management, and wikis for every project. Getting Started with The GitHub Ecosystem What is Git? Exploring a GitHub Repository Using GitHub Issues Activity: Creating A GitHub Issue Using Markdown Understanding the GitHub Flow The Essential GitHub Workflow Branching with Git Branching Defined Activity: Creating a Branch with GitHub Introduction Class Diagram Interaction Diagrams Sequence Diagrams Communication Diagrams State Machine Diagrams Activity Diagram Implementation Diagrams Local Git Configuration Checking your Git version Git Configuration Levels Viewing your configurations Configuring your username and email Configuring autocrif Working Locally with Git Creating a Local copy of the repo Our favorite Git command: git status Using Branches locally Switching branches Activity: Creating a New File The Two Stage Commit Collaborating on Your Code Collaboration Pushing your changes to GitHub Activity: Creating a Pull Request Exploring a Pull Request Activity: Code Review Merging Pull Requests Merge Explained Merging Your Pull Request Updating Your Local Repository Cleaning Up the Unneeded Branches Viewing Local Project History Using Git Log Streaming Your Workflow with Aliases Creating Custom Aliases Workflow Review Project: GitHub Games User Accounts vs. Organization Accounts Introduction to GitHub Pages What is a Fork? Creating a Fork Workflow Review: Updating the README.md Resolving Merge Conflicts Local Merge Conflicts Working with Multiple Conflicts Remote Merge Conflicts Exploring Searching for Events in Your Code What is GitHub? What is Git bisect? Finding the bug in your project Reverting Commits How Commits are made Safe operations Reverting Commits Helpful Git Commands Moving and Renaming Files with Git Staging Hunks of Changes Viewing Local Changes Comparing changes with the Repository Creating a New Local Repository Initializing a new local repository Fixing Commit Mistakes Revising your last commit Rewriting History with Git Reset Understanding reset Reset Modes Reset Soft Reset Mixed Reset Hard Does gone really mean gone? Getting it Back You just want that one commit Oops, I didn?t mean to reset Merge Strategies: Rebase About Git rebase Understanding Git Merge Strategies Creating a Linear History Additional course details: Nexus Humans Introduction to GITHub for Developers (TTDV7551) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to GITHub for Developers (TTDV7551) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 3 Days 18 CPD hours This course is intended for This course is appropriate for advanced users, system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Students can apply the course skills to use Python in basic web development projects or automate or simplify common tasks with the use of Python scripts. Overview This skills-focused course is about 50% hands-on lab to lecture ratio, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert instructor, you'll learn how 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 Work with with the standard library and its work-saving modules Create 'real-world', professional Python applications Know when to use collections such as lists, dictionaries, and sets Work with Pythonic features such as comprehensions and iterators Write robust code using exception handling Introduction to Python Programming Basics is a hands-on Python programming course that teaches you the key skills you?ll need to get started with programming in Python to a solid foundational level. The start of the course will lead you through writing and running basic Python scripts, and then guide you through how to use more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This course provides you with an excellent kick start for users new to Python and scripting, enabling you to quickly use basic Python skills on the job in a variety of ways. You?ll be able use Python in basic web development projects, or use it to automate or simplify common tasks with the use of Python scripts. The course also serves as a solid primer course / foundation for continued Python study in support for next level web development with Python, using Python in DevOps, Python for data science / machine learning or Python for systems admin or networking support. Python Quick View What is Python? Python timeline Advantages/disadvantages Installing Python Getting help The Python Environment Starting Python Using the interpreter Running a Python script Editors and IDEs Getting Started with Python Using variables Builtin functions String data Numberic data Converting types Console input/output Command line parameters Flow Control About flow control The if statement Relational and Boolean operators while loops Exiting from loops Array Types About array types Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions and generators Working with Files File overview Opening a text file Reading a text file Writing to a text file Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Returning values Parameters and arguments Variable scope Sorting The sorted() function Custom sort keys Lambda functions Sorting in reverse Using min() and max() Errors and Exception Handling Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Using packages Function and module aliases Getting Started with Object Oriented Programming and Classes About object-oriented programming Defining classes Constructors Understanding self Properties Instance Methods and data Class methods and data Inheritance Additional course details: Nexus Humans Introduction to Python Programming Basics (TTPS4800) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to Python Programming Basics (TTPS4800) 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.
This masterclass on Visual, Auditory, and Kinaesthetic (VAK) Hypnotic Inductions offers training for hypnotherapists to enhance their skills by tailoring trance inductions to clients' dominant sensory systems.
This course aims to equip you with the skills to create an operational mobile Instagram app feed using React Native and ChatGPT. Additionally, it offers comprehensive resources to develop a well-rounded project that you can showcase as a prototype upon completion. You will use all the latest and trending tools for application development from scratch.
Fraud Prevention: A Guide for Small and Medium Sized Enterprises Course Description Copyright Ross Maynard 2021 Course Description Business fraud is a significant, and growing problem. Hardly a day goes by without news reports of organisations being hacked or having their data hijacked. Phishing scams and ID theft are also serious threats to businesses. According to data produced by Accenture, 43% of cyber attacks are aimed at small or medium sized organisations, but only 14% of those organisations are well protected. Around 60% of successful internet fraud cases are the result of phishing emails, and 30% of cases result from ID theft. These two approaches are increasingly being combined in business internet fraud. The aim of this course is to help managers in small or medium sized organisations understand the fraud risk that they face, and to take action to mitigate the risk. The course covers frauds risks, creating an anti-fraud culture and developing an fraud risk management strategy. The course comes with a fraud risk mini-audit and sample anti-fraud policies, and related policy documents. The best way to prevent fraud is to have clear anti-fraud policies and procedures which all staff understand, and which are rigorously enforced; coupled with an open, communicative environment, where staff feel safe and supported to question actions and raise concerns. To help your organisation put these elements in place, this course has five parts: Part 1: What is Fraud and Who Commits it? Part 2: Creating an Anti-Fraud Culture Part 3: Fraud Risk Management Part 4: Managing Bribery Risk Part 5: Appendices with sample anti-fraud policies, fraud response plans, a whistleblowing policy and anti-bribery policy. I hope you find the course helpful. Key Learning Points On completion of the course, delegates will be able to: Define meaning and nature of business fraud Appreciate the variable nature of people’s honesty and how that can tip into fraud Understand the personality types of people who commit business fraud Identify the elements of an anti-fraud culture Explain the steps required to guard against internet fraud Understand the elements of a fraud risk management strategy Outline the sanctions available for those committing fraud Develop an Anti-Fraud Policy, Fraud Response Plan, Whistleblowing Policy and Anti-Bribery Policy for their organisation Begin to audit the level of fraud risk and bribery risk in their organisation Curriculum Part 1: What is Fraud and Who Commits it? L1: What is Fraud? L2: The Variable Nature of Honesty Part 2: Creating an Anti-Fraud Culture L3: Creating an Anti-Fraud Culture L4: Internet Fraud and Cybercrime Part 3: Fraud Risk Management L5: The Fraud Risk Management Strategy Part 1 L6: The Fraud Risk Management Strategy Part 2 L7: Sanctions for Fraud L8: Tips to Help Prevent Fraud L9: The Fraud Risk Mini-Audit L10: Fraud Prevention Exercises Part 4: Managing Bribery Risk L11: The Bribery Act 2010 L12: The Bribery Risk Mini-Audit Part 5: Appendices Sample Anti-Fraud Policy 1 Sample Anti-Fraud Policy 2 Sample Fraud Response Plan 1 Sample Fraud Response Plan 2 Sample Whistleblowing Policy Sample Anti-Bribery Policy Pre-Course Requirements There are no pre-course requirements Additional Resources PDF copies of the following documents are provided with the course: Sample Anti-Fraud Policy 1 Sample Anti-Fraud Policy 2 Sample Fraud Response Plan 1 Sample Fraud Response Plan 2 Sample Whistleblowing Policy Sample Anti-Bribery Policy Sample Code of Ethics CIMA Fraud Risk Management Guide 2016 The Honesty Questionnaire The Fraud Risk Mini-Audit The Bribery Risk Mini Audit Course Tutor Your tutor is Ross Maynard. Ross is a Fellow of the Chartered Institute of Management Accountants in the UK and has 30 years’ experience as a process improvement consultant specialising in business processes and organisation development. Ross is also a professional author of online training courses. Ross lives in Scotland with his wife, daughter and Cocker Spaniel
The course is crafted to reflect the in-demand skills in the marketplace that will help you in mastering the key concepts and methodologies of RL and deep RL, along with several practical implementations. This course will help you know the theory and practical aspects of reinforcement and deep reinforcement learning.
Negotiation Skills: Negotiation Skills Course Online Transform Your Future with Our Level 5 Negotiation Skills Course! Are you ready to elevate your career with advanced negotiation skills? Our Level 5 Negotiation Skills course is specifically designed to enhance your negotiation skills, empowering you to navigate any situation with confidence. In this comprehensive course, you will master key negotiation skills, learning effective techniques that can be applied in real-world scenarios. Each module focuses on developing your negotiation skills through engaging content and practical exercises. Unlock the secrets of successful negotiation skills with insights from industry experts. Our Level 5 Negotiation Skills course will provide you with the tools to refine your negotiation skills and achieve outstanding results. Join us today and take the first step toward mastering your negotiation skills. With our Level 5 Negotiation Skills course, you’ll gain the confidence and expertise needed to excel in any negotiation. Don’t wait—enroll now and elevate your negotiation skills to new heights! Special Offers of this Negotiation Skills: Negotiation Skills Course: This Negotiation Skills: Negotiation Skills Course includes a FREE PDF Certificate. Lifetime access to this Negotiation Skills: Negotiation Skills Course Instant access to this Negotiation Skills: Negotiation Skills Course 24/7 Support Available to this Negotiation Skills: Negotiation Skills Course [ Note: Free PDF certificate as soon as completing the Negotiation Skills: Negotiation Skills Course] Negotiation Skills: Negotiation Skills Course Online This Negotiation Skills Course consist of 12 detailed modules In our Level 5 Negotiation Skills course, you will develop essential negotiation skills that will transform your approach. Each module enhances your negotiation skills, focusing on practical applications of negotiation skills. You’ll engage in exercises designed to improve your negotiation skills and boost your confidence in negotiation skills. Mastering negotiation skills opens doors to success in all aspects of negotiation skills. Who is this course for? Negotiation Skills: Negotiation Skills Course Online This Negotiation Skills: Negotiation Skills Course is ideal for candidates committed to their ongoing professional development. Requirements Negotiation Skills: Negotiation Skills Course Online To enrol in this Negotiation Skills: Negotiation Skills Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Negotiation Skills: Negotiation Skills Course. Be energetic and self-motivated to complete our Negotiation Skills: Negotiation Skills Course. Basic computer Skill is required to complete our Negotiation Skills: Negotiation Skills Course. If you want to enrol in our Negotiation Skills: Negotiation Skills Course, you must be at least 15 years old. Career path Negotiation Skills: Negotiation Skills Course Online This Negotiation Skills: Negotiation Skills Course could hold the key to the leadership career of your dreams. Typical job titles in management and leadership include: Team Leader Manager Controller
This masterclass is designed to provide professionals, caregivers, and individuals with a comprehensive understanding of the 3-Phase Protocol for PTSD—a structured approach aimed at addressing trauma-related symptoms, stabilizing emotional responses, and fostering long-term recovery. The protocol combines evidence-based practices with experiential learning, enabling participants to apply these principles in clinical and self-help settings.
Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm
Duration 5 Days 30 CPD hours This course is intended for This course is recommended for IT Professionals and Consultants. Overview Identify risks and areas for improvement in a Citrix Virtual Apps and Desktops environment by assessing relevant information in an existing deployment. Determine core Citrix Virtual Apps and Desktops design decisions and align them to business requirements to achieve a practical solution. Design a Citrix Virtual Apps and Desktops disaster recovery plan and understand different disaster recovery considerations. This advanced 5-day training course teaches the design principles for creating a Citrix Virtual Apps and Desktops virtualization solution. In this training, you will also learn how to assess existing environments, explore different scenarios, and make design decisions based on business requirements. This course covers the Citrix Consulting approach to design and covers the key design decisions through lectures, lab exercises, and interactive discussions. You will also learn about additional considerations and advanced configurations for multi-location solutions and disaster recovery planning. This training will help you prepare for the Citrix Certified Expert in Virtualization (CCE-V) exam. Module 1: Methodology & Assessment The Citrix Consulting Methodology Citrix Consulting Methodology Use Business Drivers Prioritize Business Drivers User Segmentation User Segmentation Process App Assessment Introduction App Assessment Analysis Why Perform a Capabilities Assessment? Common Capabilities Assessment Risks Module 2: User Layer Endpoint Considerations Peripherals Considerations Citrix Workspace App Version Considerations Citrix Workspace App Multiple Version Considerations Network Connectivity and the User Experience Bandwidth and Latency Considerations Graphics Mode Design Considerations HDX Transport Protocols Considerations Media Content Redirection Considerations Session Interruption Management Session Reliability Feature Considerations Session Interruption Management Auto-Client Reconnect Feature Considerations Session Interruption Management ICA Keep-Alive Feature Considerations Module 3: Access Layer Access Matrix Access Layer Access Layer Communications Double-Hop Access Layer Considerations Citrix Cloud Access Layer Considerations Use Cases for Multiple Stores Define Access Paths per User Group Define Number of URLs Configuration and Prerequisites for Access Paths Citrix Gateway Scalability Citrix Gateway High Availability StoreFront Server Scalability StoreFront Server High Availability Module 4: Resource Layer - Images Flexcast Models VDA Machine Scalability VDA Machine Sizing with NUMA VDA Machine Sizing VDA Machine Scalability Cloud Considerations Scalability Testing and Monitoring Secure VDA Machines Network Traffic Secure VDA Machines Prevent Breakouts Secure VDA Machines Implement Hardening Secure VDA Machines Anti-Virus Review of Image Methods Citrix Provisioning Overall Benefits and Considerations Citrix Provisioning Target Device Boot Methods Citrix Provisioning Read Cache and Sizing Citrix Provisioning Write Cache Type Citrix Provisioning vDisk Store Location Citrix Provisioning Network Design Citrix Provisioning Scalability Considerations Citrix Machine Creation Services Overall Benefits and Considerations Citrix Machine Creation Services Cloning Types Citrix Machine Creation Services Storage Locations & Sizing Citrix Machine Services Read and Write Cache App Layering Considerations Image Management Methods Module 5: Resource Layer - Applications and Personalization Application Delivery Option Determine the Optimal Deployment Method for an App General Application Concerns Profile Strategy Profile Types Review Citrix Profile Management Design Considerations Citrix Profile Management Scaling Citrix Profile Management Permissions Policies Review Optimize Logon Performance with Policies Printing Considerations Module 6: Control Layer Pod Architecture Introduction Pod Architecture Considerations Citrix Virtual Apps and Desktops Service Design Considerations Implement User Acceptance Testing Load Balancing the Machine Running the VDA Citrix Director Design Considerations Management Console Considerations Change Control Delivery Controller Scalability and High Availability Control Layer Security Configuration Logging Considerations Session Recording Module 7: Hardware/Compute Layer Hypervisor Host Hardware Considerations Separating Workloads Considerations Workload Considerations VMs Per Host and Hosts Per Pool Citrix Hypervisor Scalability VM Considerations in Azure and Amazon Web Services Storage Tier Considerations Storage I/O Considerations Storage Architecture Storage RAID & Disk Type Storage Sizing LUNs Storage Bandwidth Storage in Public Cloud Datacenter Networking Considerations Securing Hypervisor Administrative Access Secure the Physical Datacenter Secure the Virtual Datacenter Module 8: Module 8: High Availability and Multiple Location Environments Redundancy vs. Fault Tolerance vs. High Availability Multi-Location Architecture Considerations Multi-Site Architecture Considerations Global Server Load Balancing Optimal Gateway Routing Zone Preference and Failover StoreFront Resource Aggregation StoreFront Subscription Sync Hybrid Environment Options Citrix Provisioning Across Site Site Database Scalability and High Availability Citrix Provisioning Across Sites Considerations Citrix Machine Creation Across Sites App Layering Across Sites Managing Roaming Profiles and Citrix Workspace App Configurations Across Devices Profile Management Multi-Site Replication Considerations Folder Redirections and Other User Data in a Multi-Location Environment Application Data Considerations Cloud-Based Storage Replication Options Multi-Location Printing Considerations Zone Considerations Active Directory Considerations Module 9: Disaster Recovery Tiers of Disaster Recovery Disaster Recovery Considerations Business Continuity Planning and Testing Citrix Standard of Business Continuity