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Register on the SQL NoSQL Big Data and Hadoop today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The SQL NoSQL Big Data and Hadoop is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The SQL NoSQL Big Data and Hadoop Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the SQL NoSQL Big Data and Hadoop, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Section 01: Introduction Introduction 00:07:00 Building a Data-driven Organization - Introduction 00:04:00 Data Engineering 00:06:00 Learning Environment & Course Material 00:04:00 Movielens Dataset 00:03:00 Section 02: Relational Database Systems Introduction to Relational Databases 00:09:00 SQL 00:05:00 Movielens Relational Model 00:15:00 Movielens Relational Model: Normalization vs Denormalization 00:16:00 MySQL 00:05:00 Movielens in MySQL: Database import 00:06:00 OLTP in RDBMS: CRUD Applications 00:17:00 Indexes 00:16:00 Data Warehousing 00:15:00 Analytical Processing 00:17:00 Transaction Logs 00:06:00 Relational Databases - Wrap Up 00:03:00 Section 03: Database Classification Distributed Databases 00:07:00 CAP Theorem 00:10:00 BASE 00:07:00 Other Classifications 00:07:00 Section 04: Key-Value Store Introduction to KV Stores 00:02:00 Redis 00:04:00 Install Redis 00:07:00 Time Complexity of Algorithm 00:05:00 Data Structures in Redis : Key & String 00:20:00 Data Structures in Redis II : Hash & List 00:18:00 Data structures in Redis III : Set & Sorted Set 00:21:00 Data structures in Redis IV : Geo & HyperLogLog 00:11:00 Data structures in Redis V : Pubsub & Transaction 00:08:00 Modelling Movielens in Redis 00:11:00 Redis Example in Application 00:29:00 KV Stores: Wrap Up 00:02:00 Section 05: Document-Oriented Databases Introduction to Document-Oriented Databases 00:05:00 MongoDB 00:04:00 MongoDB Installation 00:02:00 Movielens in MongoDB 00:13:00 Movielens in MongoDB: Normalization vs Denormalization 00:11:00 Movielens in MongoDB: Implementation 00:10:00 CRUD Operations in MongoDB 00:13:00 Indexes 00:16:00 MongoDB Aggregation Query - MapReduce function 00:09:00 MongoDB Aggregation Query - Aggregation Framework 00:16:00 Demo: MySQL vs MongoDB. Modeling with Spark 00:02:00 Document Stores: Wrap Up 00:03:00 Section 06: Search Engines Introduction to Search Engine Stores 00:05:00 Elasticsearch 00:09:00 Basic Terms Concepts and Description 00:13:00 Movielens in Elastisearch 00:12:00 CRUD in Elasticsearch 00:15:00 Search Queries in Elasticsearch 00:23:00 Aggregation Queries in Elasticsearch 00:23:00 The Elastic Stack (ELK) 00:12:00 Use case: UFO Sighting in ElasticSearch 00:29:00 Search Engines: Wrap Up 00:04:00 Section 07: Wide Column Store Introduction to Columnar databases 00:06:00 HBase 00:07:00 HBase Architecture 00:09:00 HBase Installation 00:09:00 Apache Zookeeper 00:06:00 Movielens Data in HBase 00:17:00 Performing CRUD in HBase 00:24:00 SQL on HBase - Apache Phoenix 00:14:00 SQL on HBase - Apache Phoenix - Movielens 00:10:00 Demo : GeoLife GPS Trajectories 00:02:00 Wide Column Store: Wrap Up 00:04:00 Section 08: Time Series Databases Introduction to Time Series 00:09:00 InfluxDB 00:03:00 InfluxDB Installation 00:07:00 InfluxDB Data Model 00:07:00 Data manipulation in InfluxDB 00:17:00 TICK Stack I 00:12:00 TICK Stack II 00:23:00 Time Series Databases: Wrap Up 00:04:00 Section 09: Graph Databases Introduction to Graph Databases 00:05:00 Modelling in Graph 00:14:00 Modelling Movielens as a Graph 00:10:00 Neo4J 00:04:00 Neo4J installation 00:08:00 Cypher 00:12:00 Cypher II 00:19:00 Movielens in Neo4J: Data Import 00:17:00 Movielens in Neo4J: Spring Application 00:12:00 Data Analysis in Graph Databases 00:05:00 Examples of Graph Algorithms in Neo4J 00:18:00 Graph Databases: Wrap Up 00:07:00 Section 10: Hadoop Platform Introduction to Big Data With Apache Hadoop 00:06:00 Big Data Storage in Hadoop (HDFS) 00:16:00 Big Data Processing : YARN 00:11:00 Installation 00:13:00 Data Processing in Hadoop (MapReduce) 00:14:00 Examples in MapReduce 00:25:00 Data Processing in Hadoop (Pig) 00:12:00 Examples in Pig 00:21:00 Data Processing in Hadoop (Spark) 00:23:00 Examples in Spark 00:23:00 Data Analytics with Apache Spark 00:09:00 Data Compression 00:06:00 Data serialization and storage formats 00:20:00 Hadoop: Wrap Up 00:07:00 Section 11: Big Data SQL Engines Introduction Big Data SQL Engines 00:03:00 Apache Hive 00:10:00 Apache Hive : Demonstration 00:20:00 MPP SQL-on-Hadoop: Introduction 00:03:00 Impala 00:06:00 Impala : Demonstration 00:18:00 PrestoDB 00:13:00 PrestoDB : Demonstration 00:14:00 SQL-on-Hadoop: Wrap Up 00:02:00 Section 12: Distributed Commit Log Data Architectures 00:05:00 Introduction to Distributed Commit Logs 00:07:00 Apache Kafka 00:03:00 Confluent Platform Installation 00:10:00 Data Modeling in Kafka I 00:13:00 Data Modeling in Kafka II 00:15:00 Data Generation for Testing 00:09:00 Use case: Toll fee Collection 00:04:00 Stream processing 00:11:00 Stream Processing II with Stream + Connect APIs 00:19:00 Example: Kafka Streams 00:15:00 KSQL : Streaming Processing in SQL 00:04:00 KSQL: Example 00:14:00 Demonstration: NYC Taxi and Fares 00:01:00 Streaming: Wrap Up 00:02:00 Section 13: Summary Database Polyglot 00:04:00 Extending your knowledge 00:08:00 Data Visualization 00:11:00 Building a Data-driven Organization - Conclusion 00:07:00 Conclusion 00:03:00 Resources Resources - SQL NoSQL Big Data And Hadoop 00:00:00

Forensic Science: Forensic Science Course Online Unlock the Secrets of Forensic Science: Forensic Science Course with Our Comprehensive Online Course! Discover the power of forensic science in our comprehensive Forensic Science course! Each module delves into essential forensic science techniques, ensuring you master forensic science skills needed in the field. With hands-on experience in forensic science applications, you'll learn how to analyze evidence like a true forensic science expert. Join us and elevate your career with our Forensic Science course today! In our Forensic Science course, you will explore the critical role of forensic science in modern investigations. Each lesson is designed to deepen your understanding of forensic science principles, making you proficient in forensic science methodologies. Engage with real-world cases that highlight the importance of forensic science in solving crimes. Our dedicated instructors will guide you through the fascinating landscape of forensic science, ensuring you gain invaluable forensic science insights for your career. Join us to become a leader in forensic science today! Main Course: Forensic Science Course Free Courses included with Forensic Science: Forensic Science Course: Along with Forensic Science Course you will get free Forensic Nurse Course Special Offers of this Forensic Science: Forensic Science Course; This Forensic Science: Forensic Science Course includes a FREE PDF Certificate. Lifetime access to this Forensic Science: Forensic Science Course Instant access to this Forensic Science: Forensic Science Course 24/7 Support Available to this Forensic Science: Forensic Science Course Forensic Science: Forensic Science Course Online Unlock the secrets of crime-solving with our Forensic Science course! Dive deep into forensic science techniques, from DNA analysis to crime scene investigation. Master forensic science methodologies and enhance your skills in forensic science applications. Join us to explore the fascinating world of forensic science, where you'll learn to apply forensic science principles in real-life scenarios. Enroll today! Who is this course for? Forensic Science: Forensic Science Course Online This Forensic Science: Forensic Science Course is open to everyone. Requirements Forensic Science: Forensic Science Course Online To enrol in this Forensic Science: Forensic Science Course, students must fulfil the following requirements: Forensic Science: Good Command over English language is mandatory to enrol in our Forensic Science Course. Forensic Science: Be energetic and self-motivated to complete our Forensic Science Course. Forensic Science: Basic computer Skill is required to complete our Forensic Science Course. Forensic Science: If you want to enrol in our Forensic Science Course, you must be at least 15 years old. Career path Forensic Science: Forensic Science Course Online Residents of the UK will be helped to find new careers in a variety of industries by this Forensic Science: Forensic Science Course.

The course starts with requirements gathering and ends with implementation, which are the two main elements of software development. Through this course, you will learn to use UML diagrams to analyze and design classes and to highlight relationships between the classes. You will also learn to implement and program the design in C++, C#, and Java.

Duration 3 Days 18 CPD hours This course is intended for This course is designed for Pardot Marketers and Salesforce Administrators responsible for designing, building, and implementing marketing workflows and reports in the Pardot Lightning App. It's also for Business Users looking to learn more about the Pardot Lightning App. This course is a great foundation builder for anyone looking to take the Salesforce Pardot Specialist Certification Exam. Overview When you complete this course, you will be able to: Enable the Pardot Lightning App. Explain the relationship created between Pardot and Salesforce once the Pardot Lightning App has been enabled. Generate leads with Pardot Lightning App's various lead generation tools including forms, landing pages, and custom redirects. Manage leads with Pardot Lightning App's lead management tools including page actions, automation rules, segmentation rules, dynamic lists, and completion actions. Engage leads with Pardot Lightning App's lead engagement tools including email, personalization, dynamic content, and Engagement Studio. Qualify leads with Pardot Lightning App's scoring and grading functionality. Interpret data generated via Pardot Lightning App's reporting capabilities. Design and execute successful end-to-end marketing workflows using the Pardot Lightning App. Discover how to drive more qualified leads, nurture prospects through the sales cycle, and sell more effectively using the Pardot Lightning App. In this 3-day class, Pardot experts will show you how to design and implement marketing workflows in the Pardot Lightning App to make data-driven decisions and drive your company?s business forward. Learn how to create and automate dynamic emails, generate and qualify leads, and leverage reports and data to boost sales. Course Introduction Review Course Objectives Set Learner Expectations Review Housekeeping Items Review Additional Course Resources Explore Course Case Study Salesforce Integration Understand the Pardot-Salesforce Relationship Sync Data Between Salesforce and Pardot Enable the Pardot Lightning App in Salesforce Create Custom Fields Review Salesforce Campaigns Administration Create a Pardot Dashboard Authenticate Your Email Sending Domains Sync with Third-Party Applications Using Connectors Restore Assets from the Recycle Bin Create and Assign Users and User Groups Understand Usage Governance Visitors and Prospects Understand Pardot Visitors Understand Pardot Prospects List Management Create List Types Organize Prospects Using Static Lists Test Emails Using Test Lists Personalization and Email Marketing Personalize Your Emails with HML and Advanced Dynamic Content Automate Email Marketing Create Email Templates See What Works Best for Your Audience Using AB Testing Track Email Performance Using Email Reports Forms and Landing Pages Capture Leads with Forms Convert Visitors to Leads Using Landing Pages Track Leads with Forms and Landing Page Reports Track Clicks Using Custom Redirects Create Custom Redirect Reports Lead Management Trigger Page Actions Automate Actions from a Marketing Element Using Completion Actions Create a List of Prospects and Apply a Segmentation Action Using Segmentation Rules Create Repeatable, Criteria-Based Automation Rules Create Dynamic Lists Choose an Automation Tool Lead Qualification Understand Prospect Scoring Grade Prospects Based on Profiles Lead Nurturing Build an Engagement Program Create Engagement Program Reports Additional course details: Nexus Humans Salesforce Drive Sales with the Pardot Lightning App (PDX101) 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 Salesforce Drive Sales with the Pardot Lightning App (PDX101) 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 class is ideal for Salesforce Certified Administrators and Platform Developers responsible for developing and managing Industries CPQ applications, including catalogs and pricing. It's also designed for solution architects and technical architects looking to understand the full capabilities of Industries CPQ in order to formulate industry-specific solutions. This class is also a great foundation builder for anyone looking to earn the Salesforce Certified Industries CPQ Developer credential. Overview When you complete this course, you will be able to: Create 'perfect' orders using order capture and asset-based ordering functionality. Define products and product bundles in the shared catalog. Use pricing components to support simple and complex pricing strategies. Create promotions and discounts to adjust pricing for a limited time. Use rules to ensure the right products are available to the right customers at the right price. Build ordering and quoting solutions using Industries Digital Commerce & CPQ APIs. xplore how to develop Configure, Price, Quote (CPQ) solutions using Industries CPQ. In this class, our Industries CPQ experts will show you how to configure CPQ solutions that ensure your customers get the right products and the right prices at the right time. You?ll learn how to set up and manage products and prices, leverage promotions and rules to drive action, and build a guided experience declaratively using Industries Digital Commerce and CPQ APIs.Note: This class focuses on Industries CPQ, previously known as Vlocity CPQ, and does not cover Salesforce CPQ. Introduction Explore Communications, Media, and Energy and Utilities Clouds and Industries CPQ Understand the Industries CME Data Model Order Capture Create and Configure Orders Using the Cart Work with MACD and ABO Orders Cancel an Order Create Orders with Non-Assetizable Products Configure Data Movement Across Line Items Using Field Mapper Enterprise Product Catalog Create Attributes and Picklists Create Object Types and Learn Inheritance Architecture Create Products Set Product Attribute Metadata and Override Attribute Defaults Create Product Bundles and Define Product Cardinality Work with Product Lifecycle Dates Manage the Shared Catalog?s Platform Cache Pricing Configure One-Time and Recurring Prices Define Price Lists and Child Price Lists Implement Base and Bundled Prices Configure Time Plans and Policies Configure Advanced Pricing Strategies such as Attribute-Based Pricing and Usage Pricing Promotions and Discounts Determine the Difference Between Products, Product Bundles, and Promotions Compare Pricing Adjustments and Overrides Create Promotions for Existing Products Adjust Prices and Time Plans Create Contextual Discounts for Orders, Accounts, and Contracts Identify the Best Type of Pricing Adjustment Given a Scenario Rules Build Context Rules Components Create and Apply Context Rules to Products, Promotions, Price Lists, and Price List Entries Create Product Relationships to Recommend, Exclude, or Require other Products Create Advanced Rules to Modify Product Attributes During Order Capture Create Advanced Rules to Auto-Add Products to the Cart Identify the Best Type of Rule to Use Given a Scenario Guided Selling Customize a Guided LWC Interaction for Purchasing Products Explore Industries Digital Commerce LWC, SDK, and Cacheable APIs Learn About CpqAppHandler Service, Its Methods, and Cart-Based APIs Additional course details: Nexus Humans Salesforce Build CPQ Solutions for Industries (IPQ435) 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 Salesforce Build CPQ Solutions for Industries (IPQ435) 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 Senior Linux system administrators who use high-availability clustering and fault-tolerant shared storage technologies to maximize resiliency of production services. Overview Install and configure a Pacemaker-based high availability cluster. Create and manage highly available services. Troubleshoot common cluster issues. Work with shared storage (iSCSI) and configure multipathing. Implement Logical Volume Manager (LVM) in cluster-aware configurations. Configure GFS2 file systems on storage shared by multiple nodes. Deploy reliable, available critical production services in a high availability cluster In the Red Hat High Availability Clustering (RH436) course, you will learn how to provide highly available network services to a mission-critical enterprise environment through the deployment and management of shared storage and server clusters. Created for senior Linux system administrators, this 4-day course strongly emphasizes lab-based activities. You will set up a cluster of systems running the Pacemaker component of the Red Hat Enterprise Linux High-Availability Add-On, and deploy Linux-based services such as web servers and databases on that cluster. Cluster storage components from the Resilient Storage Add-On are also covered; installations and applications that require multiple cluster nodes can access the same storage simultaneously. This includes Logical Volume Manager (LVM) Shared Volume Groups, Red Hat Global File System 2 (GFS2), and Device-Mapper Multipath. This course is based on Red Hat Enterprise Linux 8.3. Prerequisites Red Hat Certified System Administrator (RHCSA) exam (EX200) and associated courses. Red Hat Cerfitied Engineer (RHCE) exam (EX294) and associated courses. 1 - Creating high availability clusters Create a basic high availability cluster. 2 - Managing cluster nodes and quorum Manage node membership in the cluster and describe how it impacts cluster operation. 3 - Isolating malfunctioning cluster nodes Isolate unresponsive cluster nodes to protect data and recover services and resources after a failure. 4 - Creating and configuring resources Create basic resources and resource groups to provide highly available services. 5 - Troubleshooting high availability clusters Identify, diagnose, and fix cluster issues. 6 - Automating cluster and resource deployment Deploy a new high availability cluster and cluster resources using Ansible automation. 7 - Managing two-node clusters Operate two-node clusters while identifying and avoiding issues specific to a two-node cluster configuration. 8 - Accessing iSCSI storage Configure iSCSI initiators on your servers to access block-based storage devices provided by network storage arrays or Ceph storage clusters. 9 - Accessing storage devices resiliently Configure resilient access to storage devices that have multiple access paths. 10 - Configuring LVM in clusters Select, configure, and manage the correct LVM configuration for use in your cluster. 11 - Providing storage with the GFS2 cluster file system Use the GFS2 cluster file system to simultaneously pProvide tightly coupled shared storage that can be accessed by multiple nodes. 12 - Eliminating single points of failure Identify and eliminate single points of failure in your cluster to decrease risk and increase average service availability. Note: Course outline is subject to change with technology advances and as the nature of the underlying job evolves. For questions or confirmation on a specific objective or topic, please contact a training specialist. Additional course details: Nexus Humans Red Hat High Availability Clustering (RH436) 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 Red Hat High Availability Clustering (RH436) 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 geared toward Windows system administrators, network administrators, and other system administrators who are interested in supplementing current skills or backstopping other team members, in addition to Linux system administrators who are responsible for these tasks: Configuring, installing, upgrading, and maintaining Linux systems using established standards and procedures, Providing operational support, Managing systems for monitoring system performance and availability, Writing and deploying scripts for task automation and system administration, You will be expected to already understand fundamental Linux computing concepts and be ready to practice the Red Hat Enterprise Linux methods for performing system administration tasks. Significant field experience working with Linux as a system administrator is recommended. If you do not have experience with fundamental Linux computer concepts, we advise you to start with the Red Hat System Administration I (RH124) course instead. Overview You should be able to demonstrate these skills: - Access the command line locally and remotely - Manage files from the command line - Manage local users and groups - Monitor and manage Linux processes - Control services, daemons, and the boot process - Manage tuning profiles for system performance - Control access to files with file system permissions - Analyze and store log files - Configure and secure the OpenSSH service - Install and update software packages and appstreams - Manage Linux file systems and volumes - Manage Linux networking and firewalls This course combines the foundations and applications established and covered in Red Hat System Administration I (RH124) and Red Hat System Administration II (RH134). The rapid pace of review and consolidated course timeline allow you to focus on practical application, making this offering best suited for you if you already have significant experience with Linux© administration. This course is based on Red Hat© Enterprise Linux 8. 1 - Accessing the command line Log in to a Linux system and run simple commands using the shell. 2 - Managing Files from the command line Work with files from the bash shell prompt. 3 - Managing local Linux users and groups Manage Linux users and groups and administer local password policies. 4 - Controlling access to files with Linux file system permissions Set access permissions on files and interpret the security effects of different permission settings. 5 - Managing SELinux security Use SELinux to manage access to files and interpret and troubleshoot SELinux security effects. 6 - Monitoring and managing Linux processes Monitor and control processes running on the system. 7 - Installing and updating software packages Download, install, update, and manage software packages from Red Hat and yum package repositories. 8 - Controlling services and daemons Control and monitor network services and system daemons using systemd. 9 - Managing Red Hat Enterprise Linux networking Configure basic IPv4 networking on Red Hat Enterprise Linux systems. 10 - Analyzing and storing logs Locate and interpret relevant system log files for troubleshooting purposes. 11 - Managing storage and file systems Create and use disk partitions, logical volumes, file systems, and swap spaces. 12 - Scheduling system tasks Schedule recurring system tasks using cron and systemd timer units. 13 - Mounting network file systems Mount network file system (NFS) exports and server message block (SMB) shares from network file servers. 14 - Limiting network communication with firewalld Configure a basic local firewall. Additional course details: Nexus Humans Red Hat RHCSA Rapid Track Course (RH199) 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 Red Hat RHCSA Rapid Track Course (RH199) 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.

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Course Curriculum 90 sections • 90 lectures • 10:19:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:04:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:06:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00