382 Sciences courses delivered Live Online

Duration 5 Days 30 CPD hours This course is intended for Managers Project managers Project teams Overview Participants gain an overview of the business processes that can be mapped using SAP for Utilities Customer Relationship and Billing ('CR&B'). The most important customer business processes are introduced briefly using examples. The integration of CR&B with standard SAP components is exemplified. Participants gain an overview of the business processes that can be mapped using SAP for Utilities Customer Relationship and Billing ('CR&B').The most important customer business processes are introduced briefly using examples. The integration of CR&B with standard SAP components is exemplified. Overview CR&B application components Integration of CR&B with standard SAP ERP system Integration of CR&B with standard SAP CRM system Execution of the most important business processes Customer information Customer information with IC Web Client Master data Move-in/out handling Device maintenance Meter reading Billing and invoicing Energy data management Intercompany data exchange Contract accounts receivable and payable Additional course details: Nexus Humans IUT110 Business Processes in SAP for Utilities 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 IUT110 Business Processes in SAP for Utilities 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 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 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. Overview After completing this course delegates will be capable of writing effective R code to manipulate, analyse and visualise data to enable their organisations make better, data-driven decisions. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Course Outline Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R programming language is one of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. The course will explore the following topics through a series of interactive workshop sessions: What is R? Basic R programming conventions Data structures in R Accessing data in R Descriptive statistics in R Statistical analysis in R Data manipulation in R Data visualisation in R Additional course details: Nexus Humans Beginning Data Analytics With R 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 Beginning Data Analytics With R 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 5 Days 30 CPD hours This course is intended for This course is designed for application developers. Overview Describe the benefits of implementing a decision management solution with Operational Decision Manager.Identify the key user roles that are involved in designing and developing a decision management solution, and the tasks that are associated with each role.Describe the development process of building a business rule application and the collaboration between business and development teams.Set up and customize the Business Object Model (BOM) and vocabulary for rule authoring. Implement the Execution Object Model (XOM) that enables rule execution.Orchestrate rule execution through ruleflows. Author rule artifacts to implement business policies.Debug business rule applications to ensure that the implemented business logic is error-free.Set up and customize testing and simulation for business users.Package and deploy decision services to test and production environments.Integrate decision services for managed execution within an enterprise environment.Monitor and audit execution of decision services.Work with Operational Decision Manager features that support decision governance. This course introduces developers to IBM Operational Decision Manager V8.9.2. It teaches participants the concepts and skills required to design, develop, and integrate a business rule solution with Operational Decision Manager. This course begins with an overview of Operational Decision Manager, which is composed of two main environments: Decision Server for technical users and Decision Center for business users. The course outlines the collaboration between development and business teams during project development. Through instructor-led presentations and hands-on lab exercises, participants learn about the core features of Decision Server, which is the primary working environment for developers. Participants design decision services and work with the object models that are required to author and execute rule artifacts. Participants gain experience with deployment and execution, and work extensively with Rule Execution Server. In addition, students become familiar with rule authoring so that you can support business users to set up and customize the rule authoring and validation environments. Participants also learn how to use Operational Decision Manager features to support decision governance. Introducing IBM Operational Decision Manager Exercise: Operational Decision Manager in action Developing decision services Exercise: Setting up decision services Programming with business rules and developing object models Exercise: Working with the BOM Exercise: Refactoring Orchestrating ruleset execution Exercise: Working with ruleflows Authoring rules Exercise: Exploring action rules Exercise: Authoring action rules Exercise: Authoring decision tables Customizing rule vocabulary with categories and domains Exercise: Working with static domains Exercise: Working with dynamic domains Working with queries Exercise: Working with queries Debugging rules Exercise: Executing rules locally Exercise: Debugging a ruleset Enabling tests and simulations Exercise: Enabling rule validation Managing deployment Exercise: Managing deployment Exercise: Using Build Command to build RuleApps Executing rules with Rule Execution Server Exercise: Exploring the Rule Execution Server console Auditing and monitoring ruleset execution Exercise: Auditing ruleset execution through Decision Warehouse Working with the REST API Exercise: Executing rules as a hosted transparent decision service (HTDS) Additional course details: Nexus Humans WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 WB402 IBM Developing Rule Solutions in IBM Operational Decision Manager V8.9.2 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 Technical Leaders Overview What is BlockchainHow does Blockchain workTypes of BlockchainsHow is Blockchain different from what we have todayWhat are use cases for BlockchainWhat does a Blockchain app look likeHow do I design a Blockchain appHow do I develop a Blockchain appHow do I test a Blockchain app This instructor-led 3 day Blockchain Architecture training is for technical leaders who need to make decisions about architecture, environment, and development platforms. What is Blockchain? A record keeping system Trust Decentralization Trustless environment How does Blockchain work? Announcements Blocks Nodes Chaining Verification Consensus Scalability Privacy Crypto Hashing Digital Fingerprinting PoW vs PoS Types of Blockchains Public vs Private Open vs closed Smart Contracts Blockchain as History Tokens / Coins Gas How is Blockchain different from what we have today? Decentralized Peer-to-peer architecture Software vs Firmware Database vs Blockchain Distributed database or other technology? Data Sovereignty Group Consensus What are Use Cases for Blockchain? Use Case Examples Currency Banking Services Voting Medical Records Supply Chain / Value Chain Content Distribution Verification of Software Updates (cars, planes, trains, etc) Law Enforcement Title and Ownership Records Social Media and Online Credibility Fractional asset ownership Cable Television billing High fault tolerance DDoS-proof Public or Private Blockchain? Who are the participants? What does a Blockchain app look like? DApp Resembles typical full stack web application Any internal state changes and all transactions are written to the blockchain Node.js IDE Public Blockchain visibility Private Blockchain solutions Oracles How do I design a Blockchain app? What does this solution need to let users do? Will the proposed solution reduce or remove the problems and pain points currently felt by users? What should this solution prevent users from doing? Do you need a solution ready for heavy use on day 1? Is your solution idea enhanced by the use of Blockchain? Does the use of Blockchain create a better end-user experience? If so, how? Has your business developed custom software solutions before? What level of support are you going to need? How big is the developer community? Does your vision of the future align with the project or platform's vision of the future? Does the platform aim to make new and significant contributions to the development space, or is it an efficiency / cost play? Should the solution be a public or private Blockchain? Should the solution be an open or closed Blockchain? Create a plan for contract updates and changes! Hybrid solutions Monetary exchanges? How do I develop a Blockchain app? AGILE approach pre-release Define guiding principles up front Software vs Firmware Announcements, not transactions! Classes, not contracts Link contracts to share functions Use calling contracts to keep contract address the same Hyperledger vs Ethereum CONSIDER No of Users * Avg No of Transactions (state changes) per User Should a Blockless solution be applied? Performance Security Anonymity Security Monolithic vs Modular Sandwich complexity model How do I test a Blockchain app? Recommend 5x to 10x traditional application testing time Security Networks

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Duration 2 Days 12 CPD hours This course is intended for The primary audience for this course is as follows: System engineers Network engineers Technical architects Technical support engineers Cisco integrators and partners Overview Upon successful completion of this course, students will be able to meet these overall objectives: Describe Cisco ISE policies and authentication and authorization process Understand different AAA protocols Understand how Cisco ISE fits into Cisco DNA Center architecture Provide configuration examples of Cisco ISE and TrustSec solutions Describe Cisco ISE integration with Cisco DNA Center and policy enforcement using Security Groups Provide configuration examples for wired, wireless, and VPN network access Understand how inline tagging and SGT Exchange Protocol (SXP) works This course shows you how to deploy the Cisco© Identity Services Engine (ISE) to support the Software-Defined Access (SD-Access) solution within your enterprise networks. You will gain an understanding of how Cisco ISE is utilized by the SD-Access solution to provide security policies across the organization. You will learn Cisco ISE fundamentals and get hands-on practice configuring ISE, policies, AAA client configuration, VPN access, integration, wireless guest access, and more. Cisco ISE Overview Exploring the Cisco Identity Services Engine Examining AAA protocols Examining Authentication Examining Authorization Cisco ISE Guest Access Examining Guest Portal Types Examining Guest User Types Examining AAA Policies for Guest Access Cisco ISE and SD-Access Exploring Cisco SD-Access Examining Cisco ISE for SD-Access Cisco ISE SGT Exchange Protocol SD-Access Fabric and Host Provisioning Security Group Exchange Protocol Additional course details: Nexus Humans Cisco Configuring Cisco ISE Essentials for SD- Access v1.0 (ISESDA) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cisco Configuring Cisco ISE Essentials for SD- Access v1.0 (ISESDA) 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 geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 3 Days 18 CPD hours This course is intended for This course is designed for the following roles: System administrators Technical solutions architects Systems integrators Channel partners Value-added resellers Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview This course will help you: Use SaaS or on-prem version of Cisco Intersight to enable IT organizations to analyze, simplify, and automate their environments in more advanced ways than the prior generations of tools Gain hands-on experience using Cisco Intersight Understand the X-Series, B-Series, and C-Series product line similarities and differences Describe Cisco Intersight and how it can be used to manage UCS and Cisco Hyperflex Understand the process for upgrading firmware with Cisco Intersight Administering server profiles, pools, and policies with Cisco Intersight Describe how to get started with Cisco Intersight programmability Cisco Intersight Overview (DCISO) v1.0 is a 3-day instructor led course that builds your experience with the administration of Cisco Unified Computing System (UCS) X-Series servers, including using Cisco Intersight for UCS management. This course covers architecture, configuration, and operation of Cisco Intersight©, and is designed to serve the needs of engineers seeking to understand the capabilities of Cisco Intersight for managing data centers from a single management platform. Course Outline Describing Cisco UCS Management in Cisco Intersight Describing the Cisco UCS Platform Describing Cisco Intersight Workloads Describing Automation Options Using Cisco Intersight

Duration 2 Days 12 CPD hours This course is intended for This course is aimed at anyone currently working with data who is interested in using data visualisation to more effectively communicate their results. Overview At completion, delegates will understand how data visualisations can be best used to communicate actionable insights from data and be competent with the tools required to do it. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. Course Outline The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to horse breeding. The companies doing this most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. To attend this course delegates should be competent in the use of data analysis tools such as reporting tools, spreadsheet software or business intelligence tools. The course will explore the following topics through a series of interactive workshop sessions: Fundamentals of data visualisation Data characteristics & dimensions Mapping visual encodings to data dimensions Colour theory Graphical perception & communication Interaction design Visualisation different characteristics of data: trends, comparisons, correlations, maps, networks, hierarchies, text Designing effective dashboards