280 Modeling courses delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Duration 5 Days 30 CPD hours This course is intended for This intermediate course is designed for experienced Integration Specialists and Senior-Level Developers with experience in application development, messaging middleware applications, and transport protocols such as HTTP and FTP. Overview Describe the features and uses of the IBM Integration BusDevelop, deploy, and test message flow applicationsGenerate message flow applications from predefined patternsUse IBM Integration Bus problem determination aids to diagnose and solve development and runtime errorsDescribe the function and appropriate use of IBM Integration Bus processing nodesWrite basic Extended Structured Query Language and Java programs to transform dataUse the IBM Graphical Data Mapping editor to transform dataDefine, use, and test simple XML and Data Format Description Language (DFDL) data modelsDescribe supported transport protocols and how to call them in message flows This course teaches you how to use IBM Integration Bus to develop, deploy, and support message flow applications. Students will learn how to construct applications to transport and transform data. Course Outline Course introduction Introduction to IBM Integration Bus Application development fundamentals Exercise: Importing and testing a message flow Creating message flow applications Exercise: Creating a message flow application Connecting to IBM MQ Exercise: Connecting to IBM MQ Controlling the flow of messages Exercise: Adding flow control to a message flow application Modeling the data Exercise: Creating a DFDL model Processing file data Exercise: Processing file data Using problem determination tools and help resources Exercise: Using problem determination tools Exercise: Implementing explicit error handling Mapping messages with the Graphical Data Mapping editor Referencing a database in a message flow application Exercise: Referencing a database in a map Using Compute nodes to transform messages Exercise: Transforming data by using the Compute and JavaCompute nodes Processing JMS, HTTP, and web service messages Preparing for production Exercise: Creating a runtime-aware message flow Course summary Additional course details: Nexus Humans WM666 IBM Integration Bus V10 Application Development I 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 WM666 IBM Integration Bus V10 Application Development I 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 students who need to learn database design essentials, typically in preparation for, or as a supplement to, a course on SQL such as SQL Querying: Fundamentals and courses on specific relational database platforms. Overview In this course, you will perform steps to design a relational database, including gathering requirements, data modeling, and planning implementation. You will: - Follow an efficient process for designing a relational database - Define the database conceptual model - Define the database logical model - Apply database normalization methods to improve the initial design of a database - Complete the database design, including controls to ensure its referential integrity and data integrity This course introduces you to a process for effectively planning and designing a functional, efficient database. Knowing how to plan a relational database is important to the success of the databases you create. Without planning, you cannot possibly know what the database needs to do, or even what information to include in the database. Planning a database is essential, and prevents the extra work of fixing data maintenance problems later on. The concepts are not specific to a particular software application and can be applied to any relational database management system. Getting Started with Relational Database Design Identify Database Components Identify Common Database Design Problems Follow a Database Design Process Gather Requirements Defining the Database Conceptual Model Create the Conceptual Model Identify Entity Relationships Defining the Database Logical Model Identify Columns Identify Primary Keys Identify and Diagram Relationships Normalizing Data Avoid Common Database Design Errors Comply with Higher Normal Forms Finalizing the Database Design Adapt the Physical Model for Different Systems Ensure Referential Integrity Ensure Data Integrity at the Column Level Ensure Data Integrity at the Table Level Design for the Cloud Additional course details: Nexus Humans Database Design - A Modern Approach 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 Database Design - A Modern Approach 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 course will show delegates how to appraise projects in Excel, incorporate and communicate updates as they happen and ultimately understand how to convert an opportunistic property investment into a core asset that can be sold on.

Our unique 5 day workshop prepares you for a first time pass of your CISSP exam. Covering each of the famous 8 CBK's, cram the theory before testing your knowledge during exam simulations. Led by a multi-award winning InfoSec consultant, this workshop delivers everything you need to pass,

This week long CPD accredited training is ideal for those Real Estate professionals, who are looking to bolster the DCF modelling skills. This course covers Real Estate Investment, Development, Finance & Risk.

Duration 3 Days 18 CPD hours This course is intended for This course is primarily for Developers, Developer Consultants, Help Desk/COE Support, Program/Project Manager, System Administrators, System Architects, and Technology Consultants. Overview Explaining scenarios and processes in SAP NetWeaver process integrationIdentify the technical communications modes and processesExplain business scenarios and the business hierarchy used by SAP In this course, students learn how to explain scenarios & processes in SAP NetWeaver process integration. They learn how to identify the technical communications modes & processes, as well as explain business scenarios & the business hierarchy used by SAP. Integration Basics Explaining Scenarios and Processes in SAP NetWeaver Process Integration Explaining Technical Communication Modes and Processes Explaining Business Scenarios Classical System-to-System Communication Communicating Between Two SAP Systems Communicating Between Two Non-SAP Systems Communicating Using Business Application Programming Interfaces (BAPIs) Communicating Using IDocs Processing IDocs Web Services Processing HTTP Requests Describing Simple Object Access Protocol (SOAP) Basics Analyzing Different Web Services Describing Inside-Out and Outside-In Web Services Explaining Service Oriented Architecture (SOA) Integration Technologies: On-Premise Process Integration (Design Time) Processing Integration Middleware Tools (PI Dual Stack) Installing Dual-Stack or Single-Stack Options Securing Objects Creating PI Objects Explaining Design Objects Modeling PI Scenarios Creating an Integration Scenario Configuring an Integration Scenario Displaying the Configuration Objects in the Integration Directory Integration Technologies: On-Premise Process Integration (Runtime) Connecting SAP NetWeaver PI with Proxies Creating File Adapters Executing Configuration Objects Monitoring Tools Integration Technologies: On-Premise Process Orchestration (PO) Explaining Business Process Management (BPM) Explaining Process Orchestration (PO) Explaining Advanced Adapter Engine Extended (AEX) Explaining Business Rules Management (BRM) Integration Technologies: On Demand Explaining SAP HANA Cloud Integration (HCI) Describing Eclipse-Based Access Using the Web UI to Access HCI SAP NetWeaver Gateway Explaining the SAP NetWeaver Gateway Scenario Explaining the SAP NetWeaver Gateway Development View Accessing an Open Data (OData) Service Additional course details: Nexus Humans BIT100 SAP NetWeaver Integration Technology Overview 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 BIT100 SAP NetWeaver Integration Technology Overview 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 students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

Duration 2 Days 12 CPD hours This course is intended for This training is ideally suited for data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities. It will also benefit system administrators and data engineers who wish to harness Elastic Stack's functionalities for efficient system logging, monitoring, and robust data visualization. With a focus on practical application, this course is perfect for those aspiring to solve complex data challenges in real-time environments across diverse industry verticals. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll explore: New features and updates introduced in Elastic Stack 7.0 Fundamentals of Elastic Stack including Elasticsearch, Logstash, and Kibana Useful tips for using Elastic Cloud and deploying Elastic Stack in production environments How to install and configure an Elasticsearch architecture How to solve the full-text search problem with Elasticsearch Powerful analytics capabilities through aggregations using Elasticsearch How to build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis How to create interactive dashboards for effective storytelling with your data using Kibana How to secure, monitor and use Elastic Stack's alerting and reporting capabilities The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. Geared for experienced data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities, Working with Elasticsearch will explore how to use Elastic Stack and Elasticsearch efficiently to build powerful real-time data processing applications. Throughout the two-day hands-on course, you?ll explore the power of this robust toolset that enables advanced distributed search, analytics, logging, and visualization of data, enabled by new features in Elastic Stack 7.0. You?ll delve into the core functionalities of Elastic Stack, understanding the role of each component in constructing potent real-time data processing applications. You?ll gain proficiency in Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for compelling data visualization. You?ll also explore the art of crafting custom plugins using Kibana and Beats, and familiarize yourself with Elastic X-Pack, a vital extension for effective security and monitoring. The course also covers essentials like Elasticsearch architecture, solving full-text search problems, data pipeline building, and creating interactive Kibana dashboards. Learn how to deploy Elastic Stack in production environments and explore the powerful analytics capabilities offered through Elasticsearch aggregations. The course will also touch upon securing, monitoring, and utilizing Elastic Stack's alerting and reporting capabilities. Hands-on labs, captivating demonstrations, and interactive group activities enrich your learning journey throughout the course. Introducing Elastic Stack What is Elasticsearch, and why use it? Exploring the components of the Elastic Stack Use cases of Elastic Stack Downloading and installing Getting Started with Elasticsearch Using the Kibana Console UI Core concepts of Elasticsearch CRUD operations Creating indexes and taking control of mapping REST API overview Searching - What is Relevant The basics of text analysis Searching from structured data Searching from the full text Writing compound queries Modeling relationships Analytics with Elasticsearch The basics of aggregations Preparing data for analysis Metric aggregations Bucket aggregations Pipeline aggregations Substantial Lab and Case Study Analyzing Log Data Log analysis challenges Using Logstash The Logstash architecture Overview of Logstash plugins Ingest node Visualizing Data with Kibana Downloading and installing Kibana Preparing data Kibana UI Timelion Using plugins

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is as follows: Cloud administrators Cloud solution architects Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview After you complete this course the learner will be able to meet these overall objectives: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multi-tenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud CLDCCS, Mulitcloud Management with Cisco© CloudCenter Suite is a 3-day intensive training course that teaches you to securely design, automate, and deploy applications across multiple clouds while optimizing cost and compliance with comprehensive reporting, visibility, and policy-enforcement. Through a combination of lessons with hands-on lab exercises, you will learn to simplify the lifecycle management of multicloud applications, workflows, and their infrastructure. This course will help you: Acquire the advanced skills and techniques for API calls, that can deploy and manage workloads in multiple environments without having deep cloud expertise Learn provisioning and orchestration, cost management, and workload optimization by leveraging cloud management Understanding Cloud Transitions Overview of Traditional IT Introducing Cisco CloudCenter Suite Cisco CloudCenter Suite Definition Setting Up Cisco CloudCenter Workload Manager Artifact Repository Overview and Configuration Understanding User Administration and Multitenancy in Cisco CloudCenter Suite Cisco CloudCenter Suite User Roles Grasping Application Modeling in Cisco CloudCenter Workload Manager Model an Application Identifying Resource Placement Callouts and Lifecycle Actions in Cisco CloudCenter Workload Manager Resource Placement and Validation Callout Understanding Application Deployment Framework in Cisco CloudCenter Workload Manager Workload Manager Application Parameters Exploring Application Services in Cisco CloudCenter Workload Manager Application Services Framework Integrating Cisco CloudCenter Workload Manager with Cisco Application-Centric Infrastructure Configure CloudCenter Workload Manager for Cisco ACI Introducing Application Management in Cisco CloudCenter Workload Manager Cisco CloudCenter Workload Manager Actions Library Exploring Advanced Features in CloudCenter Workload Manager Scheduling an Application in Cisco CloudCenter Workload Manager Comprehending Policies and Tagless Governance in CloudCenter Workload Manager Cisco CloudCenter Workload Manager Policies Introducing Action Orchestrator and Cost Optimizer in Cisco CloudCenter Suite Action Orchestrator in Cisco CloudCenter Suite Additional course details: Nexus Humans Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) 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 Multicloud Management with Cisco CloudCenter Suite (CLDCCS) 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.