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Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Duration 5 Days 30 CPD hours Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture and main components of NSX Explain the features and benefits of NSX Deploy the NSX Management cluster and VMware NSX Edge™ nodes Prepare VMware ESXi™ hosts to participate in NSX networking Create and configure segments for layer 2 forwarding Create and configure Tier-0 and Tier-1 gateways for logical routing Use distributed and gateway firewall policies to filter east-west and north-south traffic in NSX Configure Advanced Threat Prevention features Configure network services on NSX Edge nodes Use VMware Identity Manager™ and LDAP to manage users and access Explain the use cases, importance, and architecture of Federation This five-day, fast-paced course provides comprehensive training to install, configure, and manage a VMware NSX© environment. This course covers key features and functionality offered in the NSX 4.0.0.1 and NSX 4.0.1 releases, including the overall infrastructure, logical switching, logical routing, networking and security services, firewalls and advanced threat prevention, and more. Course Introduction Introductions and course logistics Course objectives VMware Virtual Cloud Network and VMware NSX Introduce the VMware Virtual Cloud Network vision Describe the NSX product portfolio Discuss NSX features, use cases, and benefits Explain NSX architecture and components Explain the management, control, data, and consumption planes and their functions. Preparing the NSX Infrastructure Deploy VMware NSX© ManagerTM nodes on ESXi hypervisors Navigate through the NSX UI Explain data plane components such as N-VDS/VDS, transport nodes, transport zones, profiles, and more Perform transport node preparation and configure the data plane infrastructure Verify transport node status and connectivity Explain DPU-based acceleration in NSX Install NSX using DPUs NSX Logical Switching Introduce key components and terminology in logical switching Describe the function and types of L2 segments Explain tunneling and the Geneve encapsulation Configure logical segments and attach hosts using NSX UI Describe the function and types of segment profiles Create segment profiles and apply them to segments and ports Explain the function of MAC, ARP, and TEP tables used in packet forwarding Demonstrate L2 unicast packet flow Explain ARP suppression and BUM traffic handling NSX Logical Routing Describe the logical routing function and use cases Introduce the two-tier routing architecture, topologies, and components Explain the Tier-0 and Tier-1 gateway functions Describe the logical router components: Service Router and Distributed Router Discuss the architecture and function of NSX Edge nodes Discuss deployment options of NSX Edge nodes Configure NSX Edge nodes and create NSX Edge clusters Configure Tier-0 and Tier-1 gateways Examine single-tier and multitier packet flows Configure static routing and dynamic routing, including BGP and OSPF Enable ECMP on a Tier-0 gateway Describe NSX Edge HA, failure detection, and failback modes Configure VRF Lite NSX Bridging Describe the function of logical bridging Discuss the logical bridging use cases Compare routing and bridging solutions Explain the components of logical bridging Create bridge clusters and bridge profiles NSX Firewalls Describe NSX segmentation Identify the steps to enforce Zero-Trust with NSX segmentation Describe the Distributed Firewall architecture, components, and function Configure Distributed Firewall sections and rules Configure the Distributed Firewall on VDS Describe the Gateway Firewall architecture, components, and function Configure Gateway Firewall sections and rules NSX Advanced Threat Prevention Explain NSX IDS/IPS and its use cases Configure NSX IDS/IPS Deploy NSX Application Platform Identify the components and architecture of NSX Malware Prevention Configure NSX Malware Prevention for east-west and north-south traffic Describe the use cases and architecture of VMware NSX© Intelligence? Identify the components and architecture of VMware NSX© Network Detection and Response? Use NSX Network Detection and Response to analyze network traffic events. NSX Services Explain and configure Network Address Translation (NAT) Explain and configure DNS and DHCP services Describe VMware NSX© Advanced Load Balancer? architecture, components, topologies, and use cases. Configure NSX Advanced Load Balancer Discuss the IPSec VPN and L2 VPN function and use cases Configure IPSec VPN and L2 VPN using the NSX UI NSX User and Role Management Describe the function and benefits of VMware Identity Manager? in NSX Integrate VMware Identity Manager with NSX Integrate LDAP with NSX Identify the various types of users, authentication policies, and permissions Use role-based access control to restrict user access Explain object-based access control in NSX NSX Federation Introduce the NSX Federation key concepts, terminology, and use cases. Explain the onboarding process of NSX Federation Describe the NSX Federation switching and routing functions. Describe the NSX Federation security concepts.

Duration 2 Days 12 CPD hours This course is intended for This class is intended for network engineers and network admins that are either using Google Cloud Platform or are planning to do so. The class is also for individuals that want to be exposed to software-defined networking solutions in the cloud. Overview Configure Google VPC networks, subnets, and routers Control administrative access to VPC objects Control network access to endpoints in VPCsInterconnect networks among GCP projects Interconnect networks among GCP VPC networks and on-premises or other-cloud networks Choose among GCP load balancer and proxy options and configure them Use Cloud CDN to reduce latency and save money Optimize network spend using Network TiersConfigure Cloud NAT or Private Google Access to provide instances without public IP addresses access to other services Deploy networks declaratively using Cloud Deployment Manager or Terraform Design networks to meet common customer requirements Configure monitoring and logging to troubleshoot networks problems Learn about the broad variety of networking options on Google Cloud. This course uses lectures, demos, and hands-on labs to help you explore and deploy Google Cloud networking technologies, including Virtual Private Cloud (VPC) networks, subnets, and firewalls; interconnection among networks; load balancing; Cloud DNS; Cloud CDN; and Cloud NAT. You'll also learn about common network design patterns and automated deployment using Cloud Deployment Manager or Terraform. Google Cloud VPC Networking Fundamentals Recall that networks belong to projects. Explain the differences among default, auto, and custom networks. Create networks and subnets. Explain how IPv4 addresses are assigned to Compute Engine instances. Publish domain names using Google Cloud DNS. Create Compute Engine instances with IP aliases. Create Compute Engine instances with multiple virtual network. Controlling Access to VPC Networks Outline how IAM policies affect VPC networks. Control access to network resources using service accounts. Control access to Compute Engine instances with tag-based firewall rules. Sharing Networks across Projects Outline the overall workflow for configuring Shared VPC. Differentiate between the IAM roles that allow network resources to be managed. Configure peering between unrelated VPC Networks. Recall when to use Shared VPC and when to use VPC Network Peering. Load Balancing Recall the various load balancing services. Configure Layer 7 HTTP(S) load balancing. Whitelist and blacklist IP traffic with Cloud Armor. Cache content with Cloud CDN. Explain Layer 4 TCP or SSL proxy load balancing. Explain regional network load balancing. Configure internal load balancing. Recall the choices for enabling IPv6 Internet connectivity for Google Cloud load balancers. Determine which Google Cloud load balancer to use when. Hybrid Connectivity Recall the Google Cloud interconnect and peering services available to connect your infrastructure to Google Cloud. Explain Dedicated Interconnect and Partner Interconnect. Describe the workflow for configuring a Dedicated Interconnect. Build a connection over a VPN with Cloud Router. Determine which Google Cloud interconnect service to use when. Explain Direct Peering and Partner Peering. Determine which Google Cloud peering service to use when. Networking Pricing and Billing Recognize how networking features are charged for. Use Network Service Tiers to optimize spend. Determine which Network Service Tier to use when. Recall that labels can be used to understand networking spend. Network Design and Deployment Explain common network design patterns. Configure Private Google Access to allow access to certain Google Cloud services from VM instances with only internal IP addresses. Configure Cloud NAT to provide your instances without public IP addresses access to the internet. Automate the deployment of networks using Deployment Manager or Terraform. Launch networking solutions using Cloud Marketplace. Network Monitoring and Troubleshooting Configure uptime checks, alerting policies and charts for your network services. Use VPC Flow Logs to log and analyze network traffic behavior.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for individuals who desire to become more skilled at handling difficult customers. Overview Upon successful completion of this course, students will be able to deal with difficult customers in a way that increases productivity and customer service, and decreases unhappy customers. In this course, students will gain a valuable skill set to deal with difficult customers in various situations. 1 - GETTING STARTED Housekeeping Items Pre-Assignment Review Workshop Objectives The Parking Lot Action Plan 2 - THE RIGHT ATTITUDE STARTS WITH YOU Be Grateful Keep Your Body Healthy Focus on Positive Thoughts Invoke Inner Peace Case Study 3 - INTERNAL STRESS MANAGEMENT Irritability Unhappiness with Your Job Feeling Underappreciated Not Well-Rested Case Study 4 - EXTERNAL STRESS MANAGEMENT Office Furniture Not Ergonomically Sound High Noise Volume in the Office Rift with Co-Workers Demanding Supervisor Case Study 5 - TRANSACTIONAL ANALYSIS What is Transactional Analysis? Parent Adult Child Case Study 6 - WHY ARE SOME CUSTOMERS DIFFICULT? They Have Truly Had a Bad Experience and Want to Vent They Have Truly Had a Bad Experience and Want Someone to be Held Accountable They Have Truly Had a Bad Experience and Want Resolution They Are Generally Unhappy Case Study 7 - DEALING WITH THE CUSTOMER OVER THE PHONE Listen to the Customer?s Complaint Build Rapport Do Not Respond with Negative Words or Emotion Offer a Verbal Solution to Customer Case Study 8 - DEALING WITH THE CUSTOMER IN PERSON Listen to the Customer?s Complaint Build Rapport Responding with Positive Words and Body Language Besides Words, What to Look For? Case Study 9 - SENSITIVITY IN DEALING WITH CUSTOMERS Who are Angry Who Are Rude With Different Cultural Values Who Cannot Be Satisfied Case Study 10 - SCENARIOS OF DEALING WITH A DIFFICULT CUSTOMER Angry Customer Rude Customer Culturally Diverse Customer Impossible to Please Customer Case Study 11 - CUSTOMER ONCE YOU HAVE ADDRESSED THEIR COMPLAINT Call the Customer Send the Customer an Email Mail the Customer a Small Token Handwritten or Typed Letter Case Study 12 - WRAPPING UP Words From The Wise Review Of The Parking Lot Lessons Learned Recommended Reading Completion Of Action Plans And Evaluations

Duration 1 Days 6 CPD hours This course is intended for This basic course is for those who will be administering Information Server and its product components. Overview List Information Server functional categories and the Information Server products and components that support themList and describe the Information Server architectural tiersAccess Information Server clients, including thin clients using the Information Server Launch Pad, the Information Server Engine clients, and the Information Server Console clients including Information Analyzer and Information Services DirectorCreate and configure Information Server users and groupsManage Information Server active sessionsManage Information Server reportingWork with Information Server command-line tools including tools for session administration, user and group management, and encryptionUse the istool functionality to query, export, and import Information Server Repository assets This course gets those charged with administering Information Server v11.5 and its suite of many products and components started with the basic administrative tasks necessary to support Information Server users and developers. Information Server Technical Overview List the Information Server functional categories List the Information Server products and components that support these functional categories List the Information Server architectural tiers Working with Information Server Clients Use the Information Server Launch Pad to access Information Server thin clients including the Administrative Console, Information Governance Catalog, and Metadata Asset Manager Access Information Server Engine Clients including DataStage, QualityStage, FastTrack, and Information Server Manager Access Information Server Console Clients including Information Analyzer and Information Services Director Authentication and Suite Security Configure Suite users and groups Configure DataStage credentials for Engine users Session Management View a list of active sessions View session properties Disconnect sessions Configure global session properties Managing Reports Create and manage report folders Create a report Run a report View report results Administrative Tools Session Admin tool Directory Command tool Encrypt tool Managing Information Server Repository Assets Use istool to export and import common metadata assets Use istool to query information assets Use istool to export and import security assets Use istool to export and import reporting assets

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

Duration 1 Days 6 CPD hours This course is intended for Leaders, Managers, Individuals who lead meetings This course is designed to help leaders run effective virtual meetings as well as managing their team virtually. We will explore communication styles and understanding their team as well as productivity. This course involves a lot of open discussion as well as teaching leaders how to manage the virtual workplace and run productive meetings. Defining the Virtual Workplace What does it look like? Tools available Communication strategies Understanding communication styles Leading different communication styles Building a Virtual Workplace Strategy Goals & agenda Check-ins Communication strategies Virtual Leadership Strategies Making connections & check ins Managing virtual meetings with team members Defining availability & creating schedules Open Discussion & Action Plan

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a data warehouse analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 1.75 Days 10.5 CPD hours This course is intended for The course is aimed at experienced project managers, business management and specialists in both private and public companies. A good understanding of the basic mechanisms in organisations and markets is required. Overview Knowledge of the 4 dimensions needed for efficient business transformation and digital transformation: Platform, Planning, People and Processes Be able to look at your own organisation in an outside-in perspective Insight into the journey from a precise project scope to the project's components of work packages and to the following organisational implementation Ability to define precise digital service processes Understanding of business and organisational dynamics Tools to break down a defined business algorithm to specific specifications for an IT project Transformation Framework integrates well known management theory with common project management methods. Provides access to a unique and coherent toolbox and IT workbench, which includes the ability to transform digital strategies. The Structure Of 4Dimensions Framework The Digital Ecosystem Organisational setup Structure of the Business Platform Understanding of the course goal The 4D Framework Platform Dimension Plan Dimension People Dimension Working with the framework Views Approaches Wrap up of the day How To Work With 4Dimensions Framework Wrap up of day 1 Toolbox Change sheets Agile Transformation Plan Case work How to use the transformation tool 4dimensions.info How to succeed with the transformation Transformation roles How to get started

These friendly informal sessions started in lockdown 1.0 and are a chance for some informal networking with a supportive group of lawyers, at various stages of their career from student to law firm Managing Director!