Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.
Duration 2 Days 12 CPD hours This course is intended for Data Modelers Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing a dynamic cube, and enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Dynamic Cubes Define and differentiate Dynamic Cubes Dynamic Cubes characteristics Examine Dynamic Cube requirements Examine Dynamic Cube components Examine high level architecture IBM Cognos Dynamic Query Review Dimensional Data Structures Dynamic Cubes caching Create & Design a Dynamic Cube Explore the IBM Cognos Cube Designer Review the cube development process Examine the Automatic Cube Generation Manual development overview Create dimensions Model the cube Best practice for effective modeling Deploy & Configure a Dynamic Cube Deploy a cube Explore the Estimate Hardware Requirements Identify cube management tasks Examine Query Service administration Explore Dynamic Cube properties Schedule cube actions Use the DCAdmin comment line tool Advanced Dynamic Cube Modelling Examine advanced modeling concepts Explore modeling caveats Calculated measures and members Model Relative Time Explore the Current Period property Define period aggregation rules for measures Advanced Features of Cube Designer Examine multilingual support Examine ragged hierarchies and padding members Define Parent-Child Dimensions Refresh Metadata Import Framework Manager packages Filter measures and dimensions Optimize Performance with Aggregates Identify aggregates and aggregate tables In-memory aggregates Use Aggregate Advisor to identify aggregates User defined in-memory aggregates Optimize In-Memory Aggregates automatically Aggregate Advisor recommendations Monitor Dynamic Cube performance Model aggregates (automatically vs manually) Use Slicers to define aggregation partitions Define Security Overview of Dynamic Cube security Identify security filters The Security process - Three steps Examine security scope Identify scope rules Identify roles Capabilities and access permissions Cube security deep dive Model a Virtual Cube Explore virtual cubes Create the virtual cube Explore virtual cube objects Examine virtual measures and calculated members Currency conversion using virtual cubes Security on virtual cubes Introduction to IBM Cognos Analytics Define IBM Cognos Analytics Redefined Business Intelligence Self-service Navigate to content in IBM Cognos Analytics Interact with the user interface Model data with IBM Cognos Analytics IBM Cognos Analytics components Create reports Perform self-service with analysis and Dashboards IBM Cognos Analytics architecture (high level) IBM Cognos Analytics security Package / data source relationship Create Data modules Upload files Additional course details: Nexus Humans B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 B6063 IBM Cognos Cube Designer - Design Dynamic Cubes (v11.0) 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 Overview In this course you?ll learn how to: Containerize and deploy a new Python script Configure the deployment with ConfigMaps, Secrets and SecurityContexts Understand multi-container pod design Configure probes for pod health Update and roll back an application Implement services and NetworkPolicies Use PersistentVolumeClaims for state persistence And more In this vendor agnostic course, you will use Python to build, monitor and troubleshoot scalable applications in Kubernetes. Introduction Objectives Who You Are The Linux Foundation Linux Foundation Training Preparing Your System Course Registration Labs Kubernetes Architecture What Is Kubernetes? Components of Kubernetes Challenges The Borg Heritage Kubernetes Architecture Terminology Master Node Minion (Worker) Nodes Pods Services Controllers Single IP per Pod Networking Setup CNI Network Configuration File Pod-to-Pod Communication Cloud Native Computing Foundation Resource Recommendations Labs Build Container Options Containerizing an Application Hosting a Local Repository Creating a Deployment Running Commands in a Container Multi-Container Pod readinessProbe livenessProbe Testing Labs Design Traditional Applications: Considerations Decoupled Resources Transience Flexible Framework Managing Resource Usage Multi-Container Pods Sidecar Container Adapter Container Ambassador Points to Ponder Labs Deployment Configuration Volumes Overview Introducing Volumes Volume Spec Volume Types Shared Volume Example Persistent Volumes and Claims Persistent Volume Persistent Volume Claim Dynamic Provisioning Secrets Using Secrets via Environment Variables Mounting Secrets as Volumes Portable Data with ConfigMaps Using ConfigMaps Deployment Configuration Status Scaling and Rolling Updates Deployment Rollbacks Jobs Labs Security Security Overview Accessing the API Authentication Authorization ABAC RBAC RBAC Process Overview Admission Controller Security Contexts Pod Security Policies Network Security Policies Network Security Policy Example Default Policy Example Labs Exposing Applications Service Types Services Diagram Service Update Pattern Accessing an Application with a Service Service without a Selector ClusterIP NodePort LoadBalancer ExternalName Ingress Resource Ingress Controller Labs Troubleshooting Troubleshotting Overview Basic Troubleshooting Steps Ongoing (Constant) Change Basic Troubleshooting Flow: Pods Basic Troubleshooting Flow: Node and Security Basic Troubleshooting Flow: Agents Monitoring Logging Tools Monitoring Applications System and Agent Logs Conformance Testing More Resource Labs Additional course details: Nexus Humans Kubernetes for App Developers 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 Kubernetes for App Developers course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 1 Days 6 CPD hours This course is intended for This course is designed for a non-technical audience and doesn't require any prior coding or technical experience. The handson exercises will be done using pre-built OpenAI tools and interfaces that are user-friendly and easy to use. Overview Working in an interactive learning environment, led by our engaging expert, you will: Get comfortable with the basics of prompt engineering and discover how it can make a difference in various business tasks, such as enhancing customer support, creating content, and fine-tuning sales pitches. Develop the knack for crafting, refining, and perfecting prompts suited to specific business situations by understanding context, user intent, and what makes a prompt great. Learn how to smoothly incorporate prompt engineering solutions into your existing business workflows, including pinpointing the right processes, integrating with your current software, and keeping data privacy and security in check. Become proficient in advanced techniques and best practices in prompt engineering, like making use of APIs, customizing language models, and collaborating with your teammates across different departments. Keep up with the latest developments in prompt engineering and be ready to adapt to changing business needs and trends, ensuring that you stay relevant and continue to grow in the dynamic business world. Prompt engineering is the process of designing and refining input prompts to get desired output from advanced language models, such as OpenAI Codex or GPT-4. It involves creating effective questions or statements that guide the AI model to generate useful responses for a specific task or purpose, like enhancing customer support, generating content, and fine-tuning sales pitches, making it an essential skill set for a wide range of business applications. Quick Start to Prompt Engineering for Everyday Business Users is a one-day, workshop style hands-on course that where you'll learn how to create effective prompts, integrate prompt engineering solutions into existing workflows, and uncover advanced techniques and best practices. Guided by our engaging, expert instructor, you?ll experiment with innovative tools and develop practical skills that can be immediately applied to a variety of projects. Whether you're aiming to enhance customer interactions, simplify content creation, or refine internal communication, this immersive learning experience will equip you with the knowledge to make a meaningful impact on your organization. Introduction to Prompt Engineering Understand the fundamentals of prompt engineering and its applications in the business world. What is prompt engineering? Importance of prompt engineering in business Key concepts and terminology Examples of prompt engineering in business scenarios Overview of popular prompt engineering tools (e.g., OpenAI Codex, GPT-4) Activity: Hands-on exploration of prompt engineering tools: Participants will engage in a fun scavenger hunt activity, where they will experiment with different prompt engineering tools to answer a set of questions. Developing Effective Prompts Learn how to create and refine prompts for a variety of business applications. Anatomy of a good prompt Understanding context and user intent Techniques for prompt iteration and optimization Generating specific and creative responses Handling sensitive information and biases Activity: Prompt development workshop: Participants will practice developing and refining prompts in a collaborative, game-like environment, where they will compete to create the most effective prompts for given business scenarios. Integrating Prompt Engineering into Business Processes Discover how to incorporate prompt engineering solutions into existing workflows. Identifying business processes that can benefit from prompt engineering Integrating prompt engineering with existing software and tools Evaluating the success and impact of prompt engineering solutions Ensuring data privacy and security Scaling prompt engineering solutions across an organization Activity: Business process integration simulation: Participants will work in teams to create a plan for integrating a prompt engineering solution into a simulated business process, with a focus on creativity and practicality. Advanced Techniques and Best Practices Gain insights into advanced techniques and best practices for prompt engineering in a business context. Leveraging APIs for prompt engineering Customizing and fine-tuning language models Adapting to changing business requirements and trends Collaborating with cross-functional teams Staying up-to-date with prompt engineering advancements Activity: Advanced prompt engineering challenge: Participants will take part in a friendly competition, using advanced techniques to solve complex business-related prompt engineering challenges. Additional course details: Nexus Humans QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 Overview Our engaging instructors and mentors are highly-experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will explore: New Features Overview Multitenant New Features Security Features Cloud Services Networking Globalization Big Data Support Database Installation and Configuration Database Tuning Backup and Recovery Oracle 19c New Features is a hands-on course that explores the newest features such as Big Data Enhancements, Security, Multitenant features, Oracle Cloud Services, Networking, and much more. Oracle is one of the leading databases in industry today. Learn what their latest flagship product has to offer from industry experts. Oracle 19c New Features Overview Introduction to Oracle 19c New Features Oracle 19c Multitenant New Features Refreshable PDB Switchover PDB Integration with Data Guard PDB Snapshot Carousel CDB Fleet Management Oracle 19c Security Features Profile Lockdown Create a User Defined Master Encryption Key Encrypted Passwords in Database Links and Data Pump Create Keystores for Pluggable Databases Datapump and Unified Auditing Schema Only Accounts Oracle 19c Cloud Services Oracle IaaS Oracle Saas Oracle PaaS Oracle 19c Networking Database Connection Manager Database Proxy Support Tenant Isolation Oracle 19c Globalization New globalization for Bind Variables New Database Local Support Additional Unicode Support Big Data Support New Analytic Support Data Mining Data Warehouse Additional Parallel Processing Support Inline External Tables Database Installation and Configuration Zero Downtime Upgrades Dry Run Command implementation New location for Password File Improved Bulk Operations Database Tuning SQL Tuning Advisor and Exadata New SQL Tuning Set API Concurrent SQL and Sql Performance Analyzer Database In Memory Features In Memory Support for External Tables In Memory Features for Analytics Oracle 19c Backup and Recovery Active Pluggable Cloning Pluggable and non Pluggable Database Migration Additional course details: Nexus Humans Oracle 19c New Features (TTOR20019) 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 Oracle 19c New Features (TTOR20019) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Solutions architects, security DevOps, and security engineers Overview In this course, you will learn to: Establish a landing zone with AWS Control Tower Configure AWS Organizations to create a multi-account environment Implement identity management using AWS Single Sign-On users and groups Federate access using AWS SSO Enforce policies using prepackaged guardrails Centralize logging using AWS CloudTrail and AWS Config Enable cross-account security audits using AWS Identity and Access Management (IAM) Define workflows for provisioning accounts using AWS Service Catalog and AWS Security Hub Security is foundational to AWS. Governance at scale is a new concept for automating cloud governance that can help companies retire manual processes in account management, budget enforcement, and security and compliance. By automating common challenges, companies can scale without inhibiting agility, speed, or innovation. In addition, they can provide decision makers with the visibility, control, and governance necessary to protect sensitive data and systems.In this course, you will learn how to facilitate developer speed and agility, and incorporate preventive and detective controls. By the end of this course, you will be able to apply governance best practices. Course Introduction Instructor introduction Learning objectives Course structure and objectives Course logistics and agenda Module 1: Governance at Scale Governance at scale focal points Business and Technical Challenges Module 2: Governance Automation Multi-account strategies, guidance, and architecture Environments for agility and governance at scale Governance with AWS Control Tower Use cases for governance at scale Module 3: Preventive Controls Enterprise environment challenges for developers AWS Service Catalog Resource creation Workflows for provisioning accounts Preventive cost and security governance Self-service with existing IT service management (ITSM) tools Module 4: Detective Controls Operations aspect of governance at scale Resource monitoring Configuration rules for auditing Operational insights Remediation Clean up accounts Module 5: Resources Explore additional resources for security governance at scale Additional course details: Nexus Humans AWS Security Governance at Scale 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 AWS Security Governance at Scale course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 1 Days 6 CPD hours This course is intended for Individuals planning to deploy applications and create application environments on Google Cloud. Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview Identify the purpose and value of Google Cloud products and services. Interact with Google Cloud services. Describe ways in which customers have used Google Cloud. Choose among and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine, and Compute Engine. Choose among and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore. Make basic use of BigQuery, Google's managed data warehouse for analytics. This course uses lectures, demos, and hands-on labs to give you an overview of Google Cloud products and services so that you can learn the value of Google Cloud and how to incorporate cloud-based solutions into your business strategies. Introducing Google Cloud Platform Explain the advantages of Google Cloud Platform. Define the components of Google's network infrastructure, including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS). Getting Started with Google Cloud Platform Identify the purpose of projects on Google Cloud Platform. Understand the purpose of and use cases for Identity and Access Management. List the methods of interacting with Google Cloud Platform. Lab: Getting Started with Google Cloud Platform. Google Compute Engine and Networking Identify the purpose of and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Lab: Deploying Applications Using Google Compute Engine. Google Cloud Platform Storage Options Understand the purpose of and use cases for: Google Cloud Storage, Google Cloud SQL, and Google Cloud Bigtable. Learn how to choose between the various storage options on Google Cloud Platform. Lab: Integrating Applications with Google Cloud Storage. Google Container Engine Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Introduction to Hybrid and Multi-Cloud computing (Anthos). Lab: Deploying Applications Using Google Container Engine. Google App Engine and Google Cloud Datastore Understand the purpose of and use cases for Google App Engine and Google Cloud Datastore. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand the purpose of and use cases for Google Cloud Endpoints. Lab: Deploying Applications Using App Engine and Cloud Datastore. Deployment and Monitoring Understand the purpose of template-based creation and management of resources. Understand the purpose of integrated monitoring, alerting, and debugging. Lab: Getting Started with Stackdriver and Deployment Manager. Big Data and Machine Learning Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Lab: Getting Started with BigQuery. Summary and Review Summary and Review. What's Next?.
Duration 2 Days 12 CPD hours This course is intended for Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, corrective action coordinators or managers; supervisors, team leaders, and process operators; anyone who wants to improve their ability to solve recurring problems. Overview At the completion of this course, you should be able to: Identify the different types of tools and techniques available Apply change management successfully Review what to look for when applying business case thinking to Root Cause Analysis Develop a process to systematically approach problems Business success is dependent on effective resolution of the problems that present themselves every day. Often the same or similar problems continue causing repeated losses in time or money and your staff become experts at fixing rather than preventing the problems. Learn to find and fix root causes and develop corrective actions that will effectively eliminate or control these problems. Section 1: RCA Foundation Concepts and Objectives Section Learning Objectives Discuss Definitions ? IT Perspective Discuss What is a problem and why do they exist? What is Root Cause? RCA Benefits and Approaches Event and Casual Analysis Event and Causal Analysis: Exercise 1c Worksheet RCA Tools for each approach Section Summary and Conclusions Section 2: Enhance use of RCA tools Why use a Particular Method Tool: Change Analysis Change Analysis Examples Tool: How to Resolve Conflict Tool: 5 Why?s Example Learning Management Problem Tool: Cause and Effect Tool: Fault Tree Analysis Why do we use Fault Tree Analysis? How does it work? Fault Tree Diagram Symbols Example #1 of FTA: Car Hits Object Tool: Failure Modes and Effects Analysis (FMEA) Example: Failure Modes and Effects Analysis Tool: Design / Application Review Section 3: Problem Resolution and Prevention Section Objectives The Secret of Solving Problems: -A Note about Statistical Control -A Note about Fire Fighting Technique: Business Process Mapping Example: IGOE Technique: Lean Six Sigma and DMAIC Lean Six Sigma Benefits Importance of Understanding the Business Process The Business Process Mandate Technique: Process Modeling Graphical Notation Standard (BPMN): -What is Business Process Modeling Notation (BPMN)? -Benefits of BPMN -Basic Components of BPMN Technique: Business Process Maturity Model Five Levels of Maturity Section 4: Capability Improvement for RCA Steps in Disciplined Problem Solving RCA as a RCA Process Key RCA Role Considerations Sustainable RCA Improvement Organizational Units Process Area Goals, Practices Specific and General Practices Specific Practice Examples Software Maturity Survey SWOT Analysis Worksheet Recognize the importance of the Change Management component in your RCA implementation Using the ADKAR Model to Communicate Change Review ADKAR© Model ? -Awareness of the need for change -Desire to participate and support the change -Knowledge on how to change -Ability to implement required skills and behaviors -Reinforcement to sustain the change The ADKAR Model: Reinforcement Section 5: Course Summary and Conclusions Plan the Proposal and Business Case Example: 1 Page Business Case Resource Guide Questions
Duration 4 Days 24 CPD hours This course is intended for This course is intended for Network Administrators, Network Engineers, Network Operations Technicians, and students interested in learning about programming. Overview Upon completing this course, the learner will be able to meet these overall objectives:Understand and describe basic and advanced Python terminologiesIdentify and correct Python script errorsPull and reconfigure networking devices using Python scriptsIntroduction to RESTful API utilizing JSON and XML This course focuses on the interoperability of Python programming with Networking to prepare students for Software Defined Networking. This class is designed for students looking to add programming skills in preparation for various ACI & SDN technologies. Basic Constructs Describe and execute strings Describe and execute printing Describe and execute variables Describe and execute built in methods Describe and execute input from users Describe Boolean expressions Advanced Constructs Describe and execute redundant scripts Describe and execute functions Describe and execute classes Scaling Python Describe and execute Reading Files scripts Describe and execute Writing to File scripts Describe and execute substituting strings and integers Describe and execute while loops Describe and execute for loops and lists Describe and execute slicing Updating and edit a list Error checking Dictionaries and Regular Expressions Describe and execute dictionaries Delete dictionaries Describe and execute dictionaries with lists Describe and execute regular expressions (match, search, findall, sub) XML and JSON Describe XML format Describe JSON Format Example of XML Example of JSON What is an XML Schema? Describe SOAP Example of CURL with a Web Based Application Example of a SOAP exchange with a Web based Application Example of REST with a Web based Application Putting It All Together Apply Python principles with a SOAP Client Apply Python principles with REST and WSDL Apply native Python modules Additional course details: Nexus Humans Introducing Python and Web Services Programmability for Network Engineers - v3.0 IPWSP-NE 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 Introducing Python and Web Services Programmability for Network Engineers - v3.0 IPWSP-NE 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.