5218 Model courses

Enroll today and gain the mergers and acquisitions modelling skills needed to guide high-stakes business decisions and transactions.  1.5+ Hours of Video 3.5+ Hours to Complete20+ Interactive Exercises1 Recognised Certificate Course Overview Our comprehensive M&A Modelling certification program teaches the essential skills needed to build robust financial models for merger and acquisition valuations. Through step-by-step video lessons and hands-on exercises, you will learn to structure flexible models that provide vital insights into deal outcomes. This self-paced online course focuses on real-world applications in investment banking, private equity, and corporate development. The curriculum covers all aspects of M&A models including key concepts like goodwill, accretion/dilution, consolidation of financial statements, and optimal deal structuring. With over 1 hour of content and 20+ exercises, the program provides the necessary tools and techniques to become an expert in merger modelling.  “I was previously unsure of all the financial jargon and concepts, now I feel I have taken steps towards getting the big picture of finance. I really liked the Excel web integration!” Rachel Crawford Course Highlights Introduction to M&A Model Components and Framework Step-by-Step Merger Model Recipe and Methods Modelling Goodwill, Purchase Price Allocation, Accretion/Dilution Consolidating Balance Sheets and Financial Statements Optimizing Ownership Structure and Capital Funding Real World Case Studies and Debriefs Certificate Upon Completion

Register on the Addiction and Mental Health - Dual Diagnosis 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 Addiction and Mental Health - Dual Diagnosis 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 Addiction and Mental Health - Dual Diagnosis 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 After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. 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 Addiction and Mental Health - Dual Diagnosis, 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 Promotional Video Promotional 5 minute video 00:06:00 SAMHI Dual Diagnosis Intro video SAMHI Dual Diagnosis Intro video and downloadable worksheet PowerPoint slides 00:04:00 Module 1 - Drugs and Effects Module 1 - Drugs and Effects: VIDEO PART 1 (content part 1 - 4) 00:16:00 Module 1 - Drugs and Effects: VIDEO PART 2 (content part 5 - 6) 00:20:00 Module 1 - Drugs and Effects: VIDEO PART 3 (content part 7 - 8) 00:20:00 Module 1 - Drugs and Effects: VIDEO PART 4 (content part 9) 00:16:00 Module 1 - Drugs and Effects: VIDEO PART 5 (content part 10) 00:10:00 Module 1 - Drugs and Effects: VIDEO PART 6 (content 10 - 12) 00:18:00 Module 1 - Drugs and Effects: VIDEO PART 7 (content part 13) 00:13:00 Module 1 - Drugs and Effects: VIDEO PART 8 (content part 14) 00:20:00 Module 1 - Drugs and Effects: VIDEO PART 9 (content part 14) 00:20:00 Module 1 - Drugs and Effects: VIDEO PART 10 (content part 15 - 18) 00:19:00 Module 2 - Addictions & Mental Health Module 2 Addictions & Mental Health: VIDEO PART 1 content part 1 - 2 00:16:00 Module 2 Addictions & Mental Health: VIDEO PART 2 content part 3 - 5 00:19:00 Module 2 Addictions & Mental Health: VIDEO PART 3 content part 6 - 7 00:14:00 Module 2 Addictions & Mental Health: VIDEO PART 4 content part 00:17:00 Module 2 Addictions & Mental Health: VIDEO PART 5 content part 00:18:00 Module 2 Addictions & Mental Health: VIDEO PART 6 content part 00:20:00 Module 2 Addictions & Mental Health: VIDEO PART 7 content part 00:14:00 Module 2 Addictions & Mental Health: VIDEO PART 8 content part 00:12:00 Module 2 Addictions & Mental Health: VIDEO PART 9 content part 00:20:00 Module 2 Addictions & Mental Health: VIDEO PART 10 content part 00:13:00 Module 3 - Harm Minimisation & Optimal Health Module 3 Harm Minimisation & Optimal Health VIDEO PART 1 content part 00:23:00 Module 3 Harm Minimisation & Optimal Health VIDEO PART 2 content part 00:17:00 Module 3 Harm Minimisation & Optimal Health VIDEO PART 3 content part 00:09:00 Module 3 Harm Minimisation & Optimal Health VIDEO PART 4 content part 00:18:00 Module 3 Harm Minimisation & Optimal Health VIDEO PART 5 content part 00:17:00 Module 3 Harm Minimisation & Optimal Health VIDEO PART 1 content part 6 00:11:00 Module 3 Harm Minimisation & Optimal Health VIDEO PART 7 content part 7 00:12:00 Module 4 - Brain Works - Neurophysiology Module 4 Brain Works - Neurophysiology 00:17:00 Module 4 Brain Works - Neurophysiology VIDEO PART 1 content part 00:10:00 Module 4 Brain Works - Neurophysiology VIDEO PART 2 content part 00:17:00 Module 4 Brain Works - Neurophysiology VIDEO PART 3 content part 00:19:00 Module 4 Brain Works - Neurophysiology VIDEO PART 4 content part 00:16:00 Module 4 Brain Works - Neurophysiology VIDEO PART 5 content part 00:11:00 Module 5 - Trauma Model & Keys to Treatment Module 5 Trauma Model & Keys to Treatment VIDEO PART 1 content part 1 - 2a - 2f 00:20:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 2 content part 2g 00:15:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 3 content part 2h - 2i 00:15:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 4 content part 3 00:13:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 5 content part 4 00:12:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 6 content part 5 - 7 00:18:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 7 content part 8 00:17:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 7 content partVIDEO PART 8 00:16:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 9 content part 11 00:16:00 Module 5 Trauma Model & Keys to Treatment VIDEO PART 10 content part 12 00:19:00 Module 6 - Brief & Early Intervention and Tripod of Support Module 6 Brief & Early Intervention and Tripod of Support VIDEO 1 content part 1 00:18:00 Module 6 Brief & Early Intervention and Tripod of Support VIDEO 2 content part 2 00:20:00 Resources - Addiction & Mental Health (Dual Diagnosis) Integrative 12hrs Resources - Addiction & Mental Health (Dual Diagnosis) Integrative 12hrs 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for security engineers, security architects, and information security professionals. Overview Identify security benefits and responsibilities of using the AWS Cloud Build secure application infrastructures Protect applications and data from common security threats Perform and automate security checks Configure authentication and permissions for applications and resources Monitor AWS resources and respond to incidents Capture and process logs Create and configure automated and repeatable deployments with tools such as AMIs and AWS CloudFormation This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. The course highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents. Prerequisites We recommend that attendees of this course have: Working knowledge of IT security practices and infrastructure concepts Familiarity with cloud computing concepts Completed AWS Security Essentials and Architecting on AWS courses 1 - Security on AWS Security in the AWS cloud AWS Shared Responsibility Model Incident response overview DevOps with Security Engineering 2 - Identifying Entry Points on AWS Identify the different ways to access the AWS platform Understanding IAM policies IAM Permissions Boundary IAM Access Analyzer Multi-factor authentication AWS CloudTrail 3 - Security Considerations: Web Application Environments Threats in a three-tier architecture Common threats: user access Common threats: data access AWS Trusted Advisor 4 - Application Security Amazon Machine Images Amazon Inspector AWS Systems Manager 5 - Data Security Data protection strategies Encryption on AWS Protecting data at rest with Amazon S3, Amazon RDS, Amazon DynamoDB Protecting archived data with Amazon S3 Glacier Amazon S3 Access Analyzer Amazon S3 Access Points 6 - Securing Network Communications Amazon VPC security considerations Amazon VPC Traffic Mirroring Responding to compromised instances Elastic Load Balancing AWS Certificate Manager 7 - Monitoring and Collecting Logs on AWS Amazon CloudWatch and CloudWatch Logs AWS Config Amazon Macie Amazon VPC Flow Logs Amazon S3 Server Access Logs ELB Access Logs 8 - Processing Logs on AWS Amazon Kinesis Amazon Athena 9 - Security Considerations: Hybrid Environments AWS Site-to-Site and Client VPN connections AWS Direct Connect AWS Transit Gateway 10 - Out-Of-Region Protection Amazon Route 53 AWS WAF Amazon CloudFront AWS Shield AWS Firewall Manager DDoS mitigation on AWS 11 - Security Considerations: Serverless Environments Amazon Cognito Amazon API Gateway AWS Lambda 12 - Threat Detection and Investigation Amazon GuardDuty AWS Security Hub Amazon Detective 13 - Secrets Management on AWS AWS KMS AWS CloudHSM AWS Secrets Manager 14 - Automation and Security by Design AWS CloudFormation AWS Service Catalog 15 - Account Management and Provisioning on AWS AWS Organizations AWS Control Tower AWS SSO AWS Directory Service

Life Drawing - Trixie Divine - Drawing Consequences. Life Drawing starts at 18:30 GMT, and all you need is the internet and something to make a mark with.

Complete Python training course description Python is an agile, robust, expressive, fully objectoriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. This course covers Python from the very basics of 'hello world!' through to object oriented programming and advanced topics such as multi threading. Hands on follows all the major sections in order to reinforce the theory. What will you learn Read Python programs. Write Python programs. Debug Python programs. Use Python's objects and memory model as well as its OOP features. Complete Python programming training course details Who will benefit: Anyone wishing to learn Python. Prerequisites: None. Duration 5 days Complete Python programming training course contents Welcome to Python: What is Python? Origins, features. Downloading and installing Python, Python manuals, comparing Python, other implementations. Getting started: Program output, the print statement, "hello world!", Program input, raw_input(), comments, operators, variables and assignment, numbers, strings, lists and tuples, dictionaries, indentation, if statement, while Loop, for loop. range(), list comprehensions. Files, open() and file() built-in functions. Errors and exceptions. Functions, Classes, Modules, useful functions. Python basics: Statements and syntax, variable assignment, identifiers, basic style guidelines, memory management, First Python programs, Related modules/developer tools. Python Objects: Other built-in types, Internal Types, Standard type operators, Standard type built-in functions, Categorizing standard types, Unsupported types. Numbers: Integers, Double precision floating point numbers, Complex numbers, Operators, Built-in and factory functions, Other numeric types. Sequences: strings, lists, and tuples: Sequences, Strings, Strings and operators, String-only operators, Built-in functions, String built-in methods, Special features of strings, Unicode, Summary of string highlights, Lists, Operators, Built-in functions, List type built-in methods, Special features of lists, Tuples, Tuple operators and built-in functions, Tuples special features, Copying Python objects and shallow and deep copies. Mapping and set types: Mapping Type: dictionaries and operators, Mapping type built-in and factory functions, Mapping type built-in methods, Dictionary keys, Set types, Set type operators, Built-in functions, Set type built-in methods. Conditionals and loops: If, else and elif statements, Conditional expressions, while, for, break, continue and pass statements, else statement . . . take two, Iterators and iter(), List comprehensions, Generator expressions. Files and input/output: File objects, File built-in functions [open() and file()], File built-in methods and attributes, Standard files, Command-line arguments, File system, File execution, Persistent storage modules. Errors and exceptions: What are exceptions? Detecting and handling exceptions, Context management, Exceptions as strings, Raising exceptions, Assertions, Standard exceptions, Creating Exceptions, Why exceptions, Exceptions and the sys module. Functions: Calling, creating and passing functions, formal arguments, variable-length arguments, functional programming, Variable scope, recursion, generators. Modules: Modules and files, Namespaces, Importing modules, Module import features, Module built-in functions, Packages, Other features of modules. Object-Oriented Programming (OOP): Classes, Class attributes, Instances, Instance attributes, Binding and method invocation, Static methods and class methods, Composition, Sub-classing and derivation, Inheritance, Built-in functions for classes, and other objects, Customizing classes with special methods, Privacy, Delegation, Advanced features of new-style classes (Python 2.2+), Related modules and documentation. Execution environment: Callable and code Objects, Executable object statements and built-in functions, Executing other programs. 'Restricted' and 'Terminating' execution, operating system interface. Regular expressions: Special symbols and characters, REs and Python, Regular expressions example. Network programming: Sockets: communication endpoints, Network programming in Python, SocketServer module, Twisted framework introduction. Internet client programming: What are internet clients? Transferring files, Network news, E-mail. Multithreaded Programming: Threads and processes Python, threads, and the global interpreter lock, The thread and threading Modules. GUI programming: Tkinter and Python programming, Tkinter Examples, Brief tour of other GUIs. Web programming: Web surfing with Python: creating simple web clients, Advanced Web clients, CGI: helping web servers process client data, Building CGI applications, Using Unicode with CGI, Advanced CGI, Web (HTTP) Servers. Database programming: Python database application programmer's interface (DB-API), ORMs. Miscellaneous Extending Python by writing extensions, Web Services, programming MS Office with Win32 COM, Python and Java programming with Jython.

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

Duration 2 Days 12 CPD hours Overview Identify and configure basic functions of Tableau. Connect to data sources, import data into Tableau, and save Tableau files Create views and customize data in visualizations. Manage, sort, and group data. Save and share data sources and workbooks. Filter data in views. Customize visualizations with annotations, highlights, and advanced features. Create and enhance dashboards in Tableau. Create and enhance stories in Tableau As technology progresses and becomes more interwoven with our businesses and lives, more and more data is collected about business and personal activities. This era of "big data" has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage. The creation of data-backed visualizations is a key way data scientists, or any professional, can explore, analyze, and report insights and trends from data. Tableau© software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Tableau's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, allowing users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action. Prerequisites To ensure your success in this course, you should have experience managing data with Microsoft© Excel© or Google Sheets?. Lesson 1: Tableau Fundamentals Topic A: Overview of Tableau Topic B: Navigate and Configure Tableau Lesson 2: Connecting to and Preparing Data Topic A: Connect to Data Topic B: Build a Data Model Topic C: Save Workbook Files Topic D: Prepare Data for Analysis Lesson 3: Exploring Data Topic A: Create Views Topic B: Customize Data in Visualizations Lesson 4: Managing, Sorting, and Grouping Data Topic A: Adjust Fields Topic B: Sort Data Topic C: Group Data Lesson 5: Saving, Publishing, and Sharing Data Topic A: Save Data Sources Topic B: Publish Data Sources and Visualizations Topic C: Share Workbooks for Collaboration Lesson 6: Filtering Data Topic A: Configure Worksheet Filters Topic B: Apply Advanced Filter Options Topic C: Create Interactive Filters Lesson 7: Customizing Visualizations Topic A: Format and Annotate Views Topic B: Emphasize Data in Visualizations Topic C: Create Animated Workbooks Topic D: Best Practices for Visual Design Lesson 8: Creating Dashboards in Tableau Topic A: Create Dashboards Topic B: Enhance Dashboards with Actions Topic C: Create Mobile Dashboards Lesson 9: Creating Stories in Tableau Topic A: Create Stories Topic B: Enhance Stories with Tooltips

Explore intricate financial models with our Advanced Financial Modeling using Excel course. Enhance analytical skills and elevate financial decision-making. Enroll now!

Managing Multiple Projects: In-House Training Succeeding in today's competitive marketplace often requires cycle time reduction - reducing the duration of projects and getting results faster. This workshop will address managing multiple projects within the context of program or product management. Are your projects taking longer and longer to complete? Are results less than optimal because of time pressures on resources? Would you like to increase project 'throughout'? Succeeding in today's competitive marketplace often requires cycle time reduction - reducing the duration of projects and getting results faster. This workshop will address managing multiple projects within the context of program or product management. Planning and managing individual projects is challenging. When introducing the real-life limitation of resources and other outside influences into the multi-project environment, those challenges are magnified, and new challenges are introduced. This interactive workshop will position you for immediate action. The goal of this course is to equip you with the necessary knowledge, skills, and techniques so that you can effectively and productively manage multiple projects. What you Will Learn You'll learn how to: Manage stakeholder relationships and expectations Prioritize and sequence multiple projects Manage time and stress within a multiple project environment Effectively manage logical dependencies among projects Optimize the use of resources across multiple projects using concepts from Critical Chain methods Manage risk and communications in a multiple project environment Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Portfolio, program, and project management principles The multiple project environment The MMP Process Model Developing the Multiple Project List Multiple project portfolio management Project selection Project categories and types The multiple project list Multiple Project Logical Dependencies Project dependencies Types of multiple project portfolios Categories of logical dependencies across multiple projects Project priorities in the multiple project schedule Multiple Project Resource Management Multiple project resources and resource management concepts Multiple project resource loading Resource pool and resource database Multiple project resource issues and outsourcing Critical chain resource management, including drum resources and multi-tasking Managing Risk Across Multiple Projects Multiple project risk management process Identifying, assessing, and responding to multiple project risks Critical chain and multiple project risks Risk interrelationship management methods Creating and Executing the Multiple Project Plan The multiple project plan Multiple project scheduling Multiple project budgeting Executing and maintaining the multiple project plan Controlling in the multiple project environment Tools in multiple project management Multiple Project Communications Effective communication in the multiple project environment Common communication barriers Multiple project communications plan Resolving multiple project conflicts Summary and Next Steps What did we learn, and how can we implement this in our work environments?

Managing Multiple Projects Succeeding in today's competitive marketplace often requires cycle time reduction - reducing the duration of projects and getting results faster. This workshop will address managing multiple projects within the context of program or product management. Are your projects taking longer and longer to complete? Are results less than optimal because of time pressures on resources? Would you like to increase project 'throughout'? Succeeding in today's competitive marketplace often requires cycle time reduction - reducing the duration of projects and getting results faster. This workshop will address managing multiple projects within the context of program or product management. Planning and managing individual projects is challenging. When introducing the real-life limitation of resources and other outside influences into the multi-project environment, those challenges are magnified, and new challenges are introduced. This interactive workshop will position you for immediate action. The goal of this course is to equip you with the necessary knowledge, skills, and techniques so that you can effectively and productively manage multiple projects. What you Will Learn You'll learn how to: Manage stakeholder relationships and expectations Prioritize and sequence multiple projects Manage time and stress within a multiple project environment Effectively manage logical dependencies among projects Optimize the use of resources across multiple projects using concepts from Critical Chain methods Manage risk and communications in a multiple project environment Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Portfolio, program, and project management principles The multiple project environment The MMP Process Model Developing the Multiple Project List Multiple project portfolio management Project selection Project categories and types The multiple project list Multiple Project Logical Dependencies Project dependencies Types of multiple project portfolios Categories of logical dependencies across multiple projects Project priorities in the multiple project schedule Multiple Project Resource Management Multiple project resources and resource management concepts Multiple project resource loading Resource pool and resource database Multiple project resource issues and outsourcing Critical chain resource management, including drum resources and multi-tasking Managing Risk Across Multiple Projects Multiple project risk management process Identifying, assessing, and responding to multiple project risks Critical chain and multiple project risks Risk interrelationship management methods Creating and Executing the Multiple Project Plan The multiple project plan Multiple project scheduling Multiple project budgeting Executing and maintaining the multiple project plan Controlling in the multiple project environment Tools in multiple project management Multiple Project Communications Effective communication in the multiple project environment Common communication barriers Multiple project communications plan Resolving multiple project conflicts Summary and Next Steps What did we learn, and how can we implement this in our work environments?