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Duration 1 Days 6 CPD hours This course is intended for Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

Duration 2 Days 12 CPD hours This course is intended for Attending students should be new to Jira (this is NOT for experienced users), and are required to have a background in basic Enterprise application development Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment guided by our expert Jira practitioner, students will explore: Getting started with JIRA Using JIRA for Business Projects Using JIRA for Agile Projects Issue Management Field Management Screen Management Workflows and Business Process Searching and Filtering Tracking issues is a critical component of any project management strategy. JIRA provides a web based single repository for creating, tracking and reporting on feature requests, bugs reported, or managing workflow. JumpStart to Jira for End Users is a two-day, lab-intensive course for participants new to Jira, that provides them with a hands-on Jira instance to ?learn by doing?. This course provides essential understanding in the practical use of the Jira in an Agile context, with an emphasis on Best Practices and practical job-ready skills. Getting started with JIRA JIRA Overview Core concepts Terminology Infrastructure Users and Groups JIRA roles Using JIRA for Business Projects Overview of Projects Project types Project screens Tasks and task management Project Management Process Management Using JIRA for Agile Projects Overview of Agile with JIRA (very brief) Kanban overview Running a project with Kanban Configuring agile screen resolving an issue Issue Management Overview of Issues Working with issues Issue cloning Time tracking Issues and comments Tasks and subtasks Field Management Overview of Fields Built-in fields Custom fields Searching Configuring JIRA for fields Screen Management Overview of JIRA screens Working with screens Using screen tabs Issue type screens associating an issue type screen a with a project Customizing JIRA screens Workflow and Business Process Overview of Workflow Mapping business processes Managing workflows Authoring a workflow Updating an existing workflow Workflow schemes Applying a workflow to a project Searching and Reporting Overview of Searching Search screens Basic search Advanced search with JQL Working with search results Reports Dashboards Filters Gadgets Charts Summary and Best Practices Looking back at the ?Big Picture? JIRA Administration Overview Where JIRA fits into the Agile perspective JIRA End-User best practices

Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 2 Days 12 CPD hours This course is intended for This course is intended for Sales Representatives (SR), Sales Managers and End-users who have an interest in the Sales components of Dynamics 365. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. As a minimum, students should attend the prerequisite course Introduction to Microsoft Dynamics 365 Overview Understand the features and tools that exist in Microsoft Dynamics 365 for SR?s and Sales Managers. Be familiar with the stages of the Sales Order. Process in Microsoft Dynamics 365. Understand the fundamentals of Lead and Opportunity Management. Be able to track, manage, qualify Leads and convert to Opportunities and related customer records in Microsoft Dynamics 365. Know how to disqualify and cancel Leads, and convert Activity records to Leads and Opportunities. Understand how to collaborate on Opportunities with other SR?s and close Opportunity records as Won and Lost. Be able to track Competitors and Stakeholders. Understand how to view Resolution Activities. Add Products and Write-In Products to Opportunities. Build and maintain a repository of Products, Product Bundles and Product Families in the Product Catalog. Configure Unit Groups, Price Lists and Discount Lists. Work with Product Properties and view a Product Hierarchy. Create Quotes and add Products. Work with the Sales Order Process to convert Quotes to Orders and Invoices. Fulfill Orders and manage Invoice payments. Explore the Sales Reports and create a custom Sales Report using the Reporting Wizard in Microsoft Dynamics 365. Understand the significance of Sales Goal Management and Metrics in Microsoft Dynamics 365. Explore the Sales Charts and Dashboards and create a custom Sales Dashboard in Microsoft Dynamics 365. This course provides students with a detailed hands-on experience of the Salesfeatures and components of Microsoft Dynamics 365. Introduction Sales Order Process Scenarios An Introduction to Sales in Dynamics 365 The Dynamics 365 Platform Dynamics 365 Sales Fundamentals Security Considerations Where to get Help Further Reading and Resources Lead Management The Lead Management Process Working with Lead Records Working with the Lead Form Lead Assignment Leads and Activities Qualifying a Lead Disqualifying a Lead Opportunities Management Introduction to Opportunities The Opportunity Views The Opportunity Form Opportunity Sales Process Closing an Opportunity Resolution Activities Products Introduction to the Product Catalog Adding Products Configuring Unit Groups Price Lists and Price List Items Quotes, Orders and Invoices Introduction to Order Processing Adding Products to an Opportunity Working with Quotes Working with Orders Working with Invoices Sales Analysis Introduction to Sales Analysis in Dynamics 365 The Sales Reports The Reporting Wizard Working with Sales Charts Working with Sales Dashboards Working with Sales Goals and Metrics

Duration 3 Days 18 CPD hours This course is intended for Blockchain Architects Blockchain DevelopersApplication Developers Blockchain System AdministratorsNetwork Security Architects Cyber Security ExpertsIT Professionals w/cyber security experience Overview Those who attend the Security for Blockchain Professionals course and pass the exam certification will have a demonstrated knowledge of:Identifying and differentiating between security threats and attacks on a Blockchain network.Blockchain security methods, best practices, risk mitigation, and more.All known (to date) cyber-attack vectors on the Blockchain.Performing Blockchain network security risk analysis.A complete understanding of Blockchain?s inherent security features and risks.An excellent knowledge of best security practices for Blockchain System/Network Administrators.Demonstrating appropriate Blockchain data safeguarding techniques. This course covers all known aspects of Blockchain security that exist in the Blockchain environment today and provides a detailed overview of all Blockchain security issues, including threats, risk mitigation, node security integrity, confidentiality, best security practices, advanced Blockchain security and more. Fundamental Blockchain Security Cryptography for the Blockchain Hash Functions Public Key Cryptography Elliptic Curve Cryptography A Brief Introduction to Blockchain The Blocks The Chains The Network Promises of the Blockchain Blockchain Security Assumptions Digital Signature Security Hash Function Security Limitations of Basic Blockchain Security Public Key Cryptography Review Real-Life Public Key Protection Cryptography and Quantum Computers Lab 1 (Tentative) Finding Hash Function Collisions Reversible hash function Hash function with poor non-locality Hash function with small search space Breaking Public Key Cryptography Brute Forcing a Short Private Key Brute Forcing a Poorly-Chosen Private Key Consensus in the Blockchain Blockchain Consensus and Byzantine Generals Blockchain Networking Review Byzantine Generals Problem Relation to Blockchain Byzantine Fault Tolerance Introduction to Blockchain Consensus Security Blockchain Consensus Breakthrough Proof of Work What is Proof of Work? How does Proof of Work Solve BGP? Proof of Work Security Assumptions Attacking Proof of Work Proof of Stake What is Proof of Stake? How does Proof of Stake Solve BGP? Proof of Stake Security Assumptions Attacking Proof of Stake General Attacks on Blockchain Consensus Other Blockchain Consensus Algorithms Lab 2 (Tentative) Attacking Proof of Work Performing a 51% Attack Performing a Selfish Mining Attack Attacking Proof of Stake Performing a XX% Attack Performing a Long-Range Attack Malleable Transaction Attacks Advanced Blockchain Security Mechanisms Architectural Security Measures Permissioned Blockchains Checkpointing Advanced Cryptographic Solutions Multiparty Signatures Zero-Knowledge Proofs Stealth Addresses Ring Signatures Confidential Transactions Lab 3 (Tentative) Permissioned Blockchains 51% on a Checkpointed Blockchain Data mining on a blockchain with/without stealth addresses Zero-Knowledge Proof Simulation Trying to fake knowledge of a ZKP Module 4: Blockchain for Business Introduction to Ethereum Security What is Ethereum Consensus in Ethereum Smart Contracts in Ethereum Ethereum Security Pros and Cons of Ethereum Blockchains Introduction to Hyperledger Security What is Hyperledger Consensus in Hyperledger Smart Contracts in Hyperledger Hyperledger Security Pros and Cons of Hyperledger Blockchains Introduction to Corda Security What is Corda Consensus in Corda Smart Contracts in Corda Corda Security Pros and Cons of Corda Blockchains Lab 4 Blockchain Risk Assessment What are the Risks of the Blockchain? Information Security Information Sensitivity Data being placed on blockchain Risks of disclosure Regulatory Requirements Data encryption Data control PII protection Blockchain Architectural Design Public and Private Blockchains Open and Permissioned Blockchains Choosing a Blockchain Architecture Lab 5 Exploring public/private open/permissioned blockchains? Basic Blockchain Security Blockchain Architecture User Security Protecting Private Keys Malware Update Node Security Configuring MSPs Network Security Lab 6 (TBD) Smart Contract Security Introduction to Smart Contracts Smart Contract Security Considerations Turing-Complete Lifetime External Software Smart Contract Code Auditing Difficulties Techniques Tools Lab 7 (Tentative) Try a couple of smart contract code auditing tool against different contracts with built-in vulnerabilities Module 8: Security Implementing Business Blockchains Ethereum Best Practices Hyperledger Best Practices Corda Best Practices Lab 8 Network-Level Vulnerabilities and Attacks Introduction to Blockchain Network Attacks 51% Attacks Denial of Service Attacks Eclipse Attacks Routing Attacks Sybil Attacks Lab 9 Perform different network-level attacks System-Level Vulnerabilities and Attacks Introduction to Blockchain System Vulnerabilities The Bitcoin Hack The Verge Hack The EOS Vulnerability Lab 10 Smart Contract Vulnerabilities and Attacks Introduction to Common Smart Contract Vulnerabilities Reentrancy Access Control Arithmetic Unchecked Return Values Denial of Service Bad Randomness Race Conditions Timestamp Dependence Short Addresses Lab 11 Exploiting vulnerable smart contracts Security of Alternative DLT Architectures What Are Alternative DLT Architectures? Introduction to Directed Acyclic Graphs (DAGs) DAGs vs. Blockchains Advantages of DAGs DAG Vulnerabilities and Security Lab 12 Exploring a DAG network

Duration 3 Days 18 CPD hours This course is intended for Developers Administrators Overview Understand why Blockchain is needed and where Explore the major components of Blockchain Learn about Hyperledger Fabric v1.1 and the structure of the Hyperledger Architecture Lean the features of the Fabric model including chaincode, SDKs, Ledger, Security and Membership Services Perform comprehensive labs on writing chaincode Explore the architecture of Hyperledger Fabric v1.1 Understand and perform in depth labs on Bootstrapping the Network Gain a detailed understanding of the benefits, components and architecture of Hyperledger Composer Learn Hyperledger Explorer and Hyperledger Composer Playground Perform comprehensive labs to integrate/develop an application with Hyperledger Fabric running a smart contract Build applications on Hyperledger Fabric v1.1 This instructor-led Hyperledger training course is designed for developers and administrators who want to take a comprehensive deep dive on Hyperledger Fabric and Hyperledger Composer. This Hyperledger training course has several comprehensive labs, giving you real world experience.In 3 days, you will learn the need for blockchain applications, where blockchain is used, and about Hyperledger Fabric, the open source framework for developing blockchain applications and solutions with a modular architecture. Introduction to Blockchain Introduction to Blockchain What is Blockchain Types of network Public network Permissioned network Private network Need for Blockchain Components of Blockchain Consensus Provenance Immutability Finality Where can Blockchain be used Example on Blockchain How Blockchain Works How Blockchain Works Structure of Blockchain Block Hash Blockchain Distributed Lifecycle of Blockchain Smart Contract Consensus Algorithm Proof of Work Proof of Stake Practical Byzantine Fault Tolerance Actors of Blockchain Blockchain developer Blockchain operator Blockchain regulator Blockchain user Membership service provider Building A Small Blockchain Application Introduction to Hyperledger Fabric v1.1 Introduction to Hyperledger What is Hyperledger Why Hyperledger Where can Hyperledger be used Hyperledger Architecture Membership Blockchain Transaction Chaincode Hyperledger Fabric Features of Hyperledger Fabric Installation of prerequisite Getting Started With Fabric Model The Fabric Model Features of Fabric Model Chaincode SDKs Ledger Privacy through channels Security and Membership services Assets Consensus Components of Fabric Model Peer Orderer Certificate Authority Building your network Chaincode Chaincode Chaincode API How to write a Chaincode Lab Work Architecture of Hyperledger Fabric v1.1 Architecture of Hyperledger Fabric Transaction Ledger Nodes Peer Endorser Ordering Nodes Channels Certificate Authority Transaction Flow Lab Work Bootstrapping Bootstrapping the Network Introduction Lab Work Task 1 - Generate the crypto material for the various participants. Task 2 - Generate the genesis block for the Orderer node and start ordering service (solo node). Task 3 - Generated the configuration transaction block to create a new channel. Task 4 - Sign the configuration block and create the new channel. Task 5 - Make peers of all the organizations join the channel that we created in Task 4 Introdcution to Hyperledger Explorer Introduction To Hyperledger Explorer Block Details Peer List Chaincode List Transaction Details Installation of Hyperledger Explorer Starting the Explorer App Introduction to Hyperledger Composer Introduction Components of Hyperledger Composer Benefits of Hyperledger Composer Key Concepts Hyperledger Composer Solution Installation Hyperledger Composer Playground Hyperledger Composer Playground Introduction Playground Overview Lab Work Additional course details: Nexus Humans Hyperledger Training - Developing on Hyperledger Fabric 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 Hyperledger Training - Developing on Hyperledger Fabric 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 intended for Information workers, IT Professionals and Developers. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. Overview Understand the features and tools that exist in Microsoft Dynamics 365 for Customizers Be aware of integrating complimenting Microsoft products such as SharePoint, Skpe for Business and Exchange Undertake and carry out the initial setup and configuration required in a Microsoft Dynamics 365 deployment Design and configure a comprehensive Security model using the inbuilt tools in Microsoft Dynamics 365 Customize the Dynamics 365 schema by creating custom Entities, Fields and Relationships Design custom Information Forms, Quick View Forms, Quick Create Forms and System Views Create System Charts, Dashboards and Interactive Experience Dashboards Create and manage Business Rules using the Business Rule Designer Plan, design and implement best practice Workflow, Business Process Flows and Custom Actions Be able to apply best practice methodology using Unmanaged and Managed Solutions to deploy Microsoft Dynamics 365 customizations and patches This course provides students with a detailed hands-on experience of setting up, customizing, configuring and maintaining the CRM components of Microsoft Dynamics 365. Attendees of this course will gain an in-depth understanding of the Dynamics 365 security model, learn how to customize the Dynamics 365 framework, create and maintain powerful workflows and business process flows and use solutions to package and deploy customizations across multiple Dynamics 365 environments. The course applies to both Business and Enterprise Editions of Dynamics 365 as well as Online and On-premise deployments. Introduction Getting familiar with the versions of Microsoft Dynamics CRM\365 Get acquainted with the Dynamics 365 framework Review the Dynamics 365 interfaces, devices and apps Understand the tools for Dynamics 365 customizers A brief overview of Solutions Understand the differences between Dynamics 365 organisations and environments Review further reading and resources Set up the lab environment - Acme Enterprises Event Management Solution Initial Setup and Configuration An introduction to Dynamics 365 online setup An introduction to Dynamics 365 on premise setup Review the System Settings area Understand how to configure Auto Save Settings Understand how to configure Format Settings Understand how to configure Email Settings Understand how to configure Skype Integration Understand how to configure SharePoint Integration Security Design and configure Business Units Configure Security Roles Manage Users and Teams Implement Access Teams Configure Hierarchy Security Creating and Managing Entities Introduction to the Dynamics 365 schema Review the different Entity Types Create new Custom Entities Managing Entity Ownership Managing Entity Properties Custom Entity Security Review Entities and Solutions Customizing Fields Introduction to Field Customization Understand the different Field Types Review Field Formats Create a new Field Review Fields and Solutions Implement a Calculated Field Configure Field Level Security Customizing Relationships and Mappings Introduction to Relationships Review the different Relationship Types Create a Relationship Review Relationships and Solutions Understand Relationship Behavior Implement a Hierarchy Relationship Configure Field Mappings Customizing Forms, Views and Visualizations The process to create a new Form Review the different Form types Using the Form Designer Customizing the Main, Quick View and Quick Create Forms Configure Form Security Review the different View types Customizing System Views Customizing System Charts and Dashboards Workflows, Business Process Flows and Custom Actions Introduction to Processes Workflow Business Process Flows Custom Actions Solution Management An introduction to Solution Management How to add and administer components in a Solution The differences between unmanaged and managed Solutions How to export and import a Solution How to set Managed Properties for a Solution What happens when you delete a Solution How to Clone a Solution Patch How to Clone a Solution

Duration 2 Days 12 CPD hours This course is intended for The course is targeted at professionals who have never worked with Microsoft 365 before, or who have yet to move beyond its basic functions. The target audience typically includes individuals, professionals, and organizations who are looking to improve their productivity, collaboration, and communication using the suite of applications and services provided by Microsoft 365. This could include office workers, project managers, IT professionals, and small to large-scale businesses who want to maximize the benefits of cloud-based solutions for their daily operations.  Overview Upon successfully completing this course, students will have confidence in using the Microsoft 365 applications. Students will increase their work productivity and decrease time on completing tasks. In this course, students will learn how to use different tools of Microsoft 365 for better online collaboration, including OneDrive, SharePoint, Teams, Excel, Outlook, Word, and PowerPoint. First Steps in Office 365 The Difference Between Office 365 and Microsoft 365 Pros and cons of Microsoft 365 First Steps on mobile devices OneDrive Introduction - What is Microsoft OneDrive? How To Access Microsoft OneDrive? Upload Files Share Files Sync Files Recycle Bin Using OneDrive How To Access Onedrive On Phone? Teams - Simplify Collaboration within Companies Discover new ways to collaborate and communicate An introduction to your central place in Office 365 How to launch and install Teams The Interface of Microsoft Teams Use the Teams window to structure your organization Use Channels to structure the Teams window Use Tabs to access tools and information Communicate with others via Chat Keep track of activities Meetings, video conferencing and screen sharing Share files effectively Manage teams and permissions for organizational structuring Use Teams effectively on mobile devices Final remarks SharePoint Sites Introduction First Steps Document Library - First Steps Document Library - Set and Manage Alerts Document Library - Understanding Versioning Sync Libraries Share a Site Picture Library Lists Calendar Tasks Discussion Board Outlook First Steps in Mail Improved Search Function Work with Folders Settings Working with the Mail App Calendar People Tasks Excel Online Introduction Open and Edit an Excel Online Workbook Limitations of Excel Online Create a New Workbook with Excel Online Edit a Workbook Simultaneously with another Person Working with the Excel AppUse Excel effectively on mobile devices PowerPoint Online Introduction Open a PowerPoint Online Presentation Edit a Presentation Online Limitations of PowerPoint Online Create a Presentation with PowerPoint Online Working with the PowerPoint App Use Power Point effectively on mobile devices Word Online Introduction Open and Edit a Word Document Online Limitations of Word Online Create a New Document Edit a Document Simultaneously Working with the Word App

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