Overview Objective Understanding the Importance of Business Analysis Model Determining various techniques of Process Modelling Understanding the scope of modelling Efficiently mapping the business landscape Analysing the enterprise structure How to avoid project failures. Learning efficient skills of being a successful business analyst. Understand and document various techniques for the organization delivers value. Successful project conversion Building team, changing the organization and overcoming resistance. Creating an effective Business Case.
The Real Estate Analyst course has been taught non-stop to global real estate firms over the last 25 years, and is without doubt the core financial modelling training in your career portfolio. Whether you have an upcoming financial modelling test for a new job or an APC exam, the Real Estate Analyst course is the choice for you.
Duration 2 Days 12 CPD hours This course is intended for The course is designed for individuals who want to gain in-depth knowledge and practice in the discipline of Modelling Business Processes (Business Analysts, Requirements Engineers, Product manager, Product Owner, Chief Product Owner, Service Manager, Service Owner, Project manager, Consultants) Overview Students should be able to demonstrate knowledge and understanding and application of Modelling Business Processes principles and techniques. Key areas are: The role of business process modelling Modelling core business processes at an organizational level Modelling business processes at the process level Documenting and analyzing tasks The use of gap analysis in improving business processes The Business Analyst role analyzes, understands and manages the requirements in a customer-supplier relationship and ensures that the right products are delivered. The course provides in-depth knowledge and practice in Modelling Business Processes Course Introduction Let?s Get to Know Each Other Course Overview Course Learning Objectives Course Structure Course Agenda Introduction to Business Process Modelling Exam Details Business Analysis Certification Scheme The Context for Business Process Modelling Purpose and benefits of business process modelling Three levels of business process hierarchy (Organization, process and task level) Process view versus the functional view of an organization Assessing the impact of a new process design (POPIT model) Implementation of a business change (Pilot, phased, direct changeover, parallel running) The Organizational Context for Business Processes Construction of an organizational level model of a business process External and internal elements of an organizational model Supporting the value proposition Modelling the Business Processes Construction of a business process model Standard notation Process, task and step OPOPOT External, internal and time-based events Internal performance measures and customer expectations of performance Documenting Tasks A task description UML activity diagram notation and structured english Improving Business Processes task automation, removal of gaps and disconnects, process reengineering business rules and assumptions Unsatisfactory performance Combinations of conditions Gap analysis
Duration 2 Days 12 CPD hours This course is intended for Project Managers, Business Analysts, Business and IT stakeholders working with analysts Overview Provide a solid foundation for applying business process modeling principles and best practices with BPMN Demonstrate how to solve practical business problems using BPMN Business Process Diagrams (BPDs) Students will learn to map business processes easily and efficiently using the industry standard - BPMN which stands for Business Process Modeling Notation from the Object Management Group (OMG). Students will learn the best practices in process mapping using the latest industry standards (BPMN) so that both the business and IT stakeholders will be able to understand the models and map processes consistently through-out their organization. Introduction What is Business Process Modeling? What is Business Process Modeling Notation (BPMN)? Benefits of BPMN An Overview of Governance An overview of governance Key governance questions to ask What happens if you don?t have effective governance? Mapping the Business Problem Define a strategic outcomes map Define a Business model and relevant processes Modeling Simple BPMN Structures When do you use BPMN? What are simple BPMN structures? AS-IS vs. TO-BE modeling Modeling Complex BPMN Structures What are complex BPMN structures When to use complex BPMN structures Analyzing Process Models Identifying poor process models Creating process models that everyone can understand Identify criteria for a well-defined process Process Mapping vs. Process Modeling Determine when to create a process map Determine when to create a process model Asking the four ?Ares? Additional Resources Learning about BPMN 2.0 More useful BPMN links BPMN 2.0 free editors
Overview In this course you will learn to build a financial model by working in Excel and how to perform sensitivity analysis in Excel. You will also learn the formulas, functions and types of financial analysis to be an Excel power user. By attending this course, you will be able to effectively prepare and build financial models. Objectives Harness Excel's tools within a best practice framework Add flexibility to their models through the use of switches and flexible lookups Work efficiently with large data volumes Model debt effectively Approach modelling for tax, debt, pensions and disposals with confidence Build flexible charts and sensitivity analysis to aid the presentation of results Learn and apply Excel tools useful in financial forecasting Understand and design the layout of a flexible model Forecast financial statements of a public or private company Apply scenario analysis to the forecasted financial statements and prepare charts for data presentation
Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints
Complete VBA programming training course description This course helps you extend the capabilities of the entire Office suite using Visual Basic for Applications (VBA). Even if you have no programming experience, you'll be automating routine computing processes quickly using the simple, yet powerful VBA programming language. We start at the beginning to get you acquainted with VBA so you can start recording macros right away. You'll then build upon that foundation to utilize the full capabilities of the language in Word, Excel, Outlook, and PowerPoint. What will you learn Record, write and run macros. Work with VBA Editor. Use the huge library of built-in functions. Create simple dialog boxes and complex forms. Customize Word, Excel, PowerPoint, Outlook, and Access. Program the Office 2016 ribbon. Complete VBA programming training course details Who will benefit: Anyone looking to extend the capabilities of the entire Office suite using VBA. Prerequisites: None. Duration 5 days Complete VBA programming training course contents Macros and getting started in VBA VBA syntax, variables, constants, and enumerations, array variables, finding objects, methods, and properties. Working with VBA 1 VBA syntax, variables, constants, and enumerations, array variables, finding objects, methods, and properties. Decisions, loops and functions Built-in functions, creating your own functions, making decisions in your code, using loops to repeat actions. Using message boxes, input boxes, and dialog boxes Getting user input with message boxes and input boxes, creating simple custom dialog boxes, creating complex forms. Creating effective code Building modular code and using classes, debugging your code and handling errors, building well-behaved code, exploring VBA's security features. Programming the Office applications The Word object model and key objects, working with widely used objects in Word, the Excel object model and key objects, working with widely used objects in Excel, the PowerPoint object, model and key objects, working with shapes and running slide shows, the Outlook object model and key objects, working with events in Outlook, the Access object model and key objects, manipulating the data in an Access database via VBA, accessing one application from another application, programming the Office 2016 ribbon.