1867 Summary courses

Duration 2 Days 12 CPD hours This course is intended for This class has something for everything, from beginners who wish to customise their data entry forms in SharePoint right up to advanced users who need to use advanced formulas to deliver more bespoke actions to their apps. Overview After taking this course, students will be able to: - Understand when to use PowerApp. - Describe the components of PowerApps and their correct use. - Create PowerApps from existing data sources. - Brand PowerApps. - Customize PowerApps beyond just using the automated wizards. - Connect to a range of data sources from Excel to Azure SQL. - Understand the difference between canvas apps and model-driven apps. - Integrate PowerApps with other Office 365 systems ? including Teams and SharePoint Online. - Administer and Maintain PowerApps Students will be taught how to design, test and publish new apps that work with a variety of data sources. We will take users through a selection of well-crafted lessons to help them build new applications for their business. 1 - AN INTRODUCTION TO POWERAPPS What is PowerApps? The benefits of apps How to get PowerApps Canvas Apps and Model-Driven Apps License Options and Costs Discover PowerApps with Templates Lab 1: Introduction to PowerApps 2 - GETTING STARTED WITH POWERAPPS Building a new app from a data source Add, edit and remove controls Intro to Formulas Testing an app App Settings Publish and Share Apps Version History and Restore PowerApps Mobile App Lab 1: Getting Started 3 - BRANDING AND MEDIA Less is more Duplicate Screens Fonts Screen Colours and Matching Colours Screen Backgrounds Buttons and Icons Hide on Timer Size and Alignment by reference Show and Hide on Timer Lab 1: Branding and Media 4 - POWERAPPS CONTROLS Text Controls for Data Entry and Display Controls ? Drop downs, combo box, date picker, radio button and more Forms ? Add and edit data in underlying data sources quickly Charts ? present information in pie, line and bar charts Lab 1: Build Apps from Blank 5 - DATA SOURCES AND LOGIC Data Storage and Services How do I decide which database to use? Connect to on-premises data - Gateway What is Delegation? Specific Data Examples Displaying Data Lab 1: Data Source and Logic 6 - MODEL-DRIVEN APPS What is a model-driven app? Where will my data be stored? How do create a model-driven app Canvas vs model-driven summary Lab 1: Model-Driven App 7 - POWERAPP INTEGRATION Embed PowerApps in Teams Embed PowerApps in SharePoint Online Start a Flow from a PowerApp Lab 1: PowerApp Integration 8 - ADMINISTRATION AND MAINTENANCE OF POWERAPPS Identify which users have been using PowerApps Reuse an app in another location (move from testing or development to production) Review app usage Prevent a user from using PowerApps Manage environments Lab 1: Administration and Maintenance Additional course details: Nexus Humans 55265 Microsoft PowerApps 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 55265 Microsoft PowerApps 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.

Highlights of the Course Course Type: Online Learning Duration: 1 Hour Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about General Data Protection Regulation or GDPR Understand the core competencies and principles of General Data Protection Regulation or GDPR Explore the various areas of General Data Protection Regulation or GDPR Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert data controller or data protection officer GDPR - How to apply the General Data Protection Regulation Course Master the skills you need to propel your career forward in General Data Protection Regulation or GDPR. This course will equip you with the essential knowledge and skillset that will make you a confident data controller or data protection officer and take your career to the next level. This comprehensive GDPR course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this GDPR course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective General Data Protection Regulation or GDPR practice and equip you with the essential skills, confidence and competence to assist you in the General Data Protection Regulation or GDPR industry. You'll gain a solid understanding of the core competencies required to drive a successful career in General Data Protection Regulation or GDPR. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for data controller or data protection officer or for people who are aspiring to specialise in General Data Protection Regulation or GDPR. Enrol in this GDPR course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive GDPR course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this General Data Protection Regulation or GDPR can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This GDPR course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This GDPR course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This GDPR course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Introduction Trainer Introduction and Course Outline 00:02:00 Why Data Protection? What Exactly is Why Deal with Data Protection Anyway. 00:02:00 How is the Protection of Data Guaranteed. 00:04:00 The Five Basic Principles of Data Protection Introduction 00:01:00 Principle 1: Prohibition of Data Processing and Exceptions to Consent 00:01:00 Principle 2: Purpose of Data Collection 00:03:00 Principle 3: Data Collection Limits 00:02:00 Principle 4: Data Security 00:01:00 Principle 5: Transparency 00:02:00 Summary 00:02:00 The Foundations of Data Processing introduction 00:01:00 Data Processing with Consent 00:03:00 Data Processing without Consent 00:03:00 Rights of Data Subjects Rights of Data Subjects 00:05:00 Responsibility of Data Controller or Processor Introduction 00:01:00 Maintaining a Record of Processing Activities 00:03:00 Technical and Organizational Measures (TOM) 00:01:00 Data Processing 00:02:00 Data Breaches 00:02:00 Summary 00:01:00 The Data Protection Officer The Data Protection Officer 00:02:00 Summary Summary 00:02:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Lean Six Sigma Black Belt Certification Program: Virtual In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Scrum Master Exam Prep: Virtual In-House Training This workshop prepares you for the Scrum.org Professional Scrum Master (PSM)™ I certification. A voucher for the exam and the access information you will need to take the exam will be provided to you via email after you have completed the course. NOTE: If you have participated in any of IIL's other Scrum workshops, you can bypass this program and focus on reading/studying the Scrum Guide and taking practice exams from Scrum.org. A Scrum Master helps project teams properly use the Scrum framework, increasing the likelihood of the project's overall success. Scrum Masters understand Scrum values, practices, and applications and provide a level of knowledge and expertise above and beyond that of typical project managers. Scrum Masters act as 'servant leaders', helping the rest of the Scrum Team work together and learn the Scrum framework. Scrum Masters also protect the team from both internal and external distractions. The Professional Scrum Master™ I (PSM I) certificate is a Scrum.org credential that enables successful candidates to demonstrate a fundamental level of Scrum mastery. PSM I credential holders will grasp Scrum as described in The Scrum Guide™1 and recognize how those concepts can be applied. They will also share a consistent terminology and approach to Scrum with other certified professionals. Scrum.org does not require that you take their own sponsored or any preparatory training. However, training can facilitate your preparation for this credential. And this course is based on IIL's Scrum Master Workshop, which is aligned with The Scrum Guide™ and was built based on PSM I credentialed expertise. It will provide you with the information you need to pass the exam and IIL will make the arrangements for your online exam. You will be provided with an exam code and instructions, so that you can take the exam at your convenience, any time you are ready after the course. Passwords have no expiration date, but they are valid for one attempt only. What you will Learn You'll learn how to: Successfully prepare for the Scrum.org PSM I exam Comprehend the Agile Manifesto and mindset Explain the fundamental principles of Scrum, including events, artifacts, and roles Guide the Scrum team in their responsibilities Define Ready and Done Write requirements in the form of user stories Estimate using planning poker and prioritize using MoSCoW Facilitate the team through the 5 Sprint events Fulfill the role of Scrum Master in a Scrum project Create Information Radiators to enable transparency Define the structure of the retrospective Getting Started Introductions Workshop orientation Exam prep preview Foundation Concepts Agile History, Values, and Mindset Introduction to Scrum Scrum events Scrum artifacts Scrum Roles and Responsibilities Product Owner responsibilities Scrum Master responsibilities The Team responsibilities Cross-functional teams Building effective teams The Product Backlog and User Stories The Product Backlog User Stories Definition of Done Backlog grooming Estimating User Stories Story points, planning poker Prioritizing User Stories The Sprint Team capacity and velocity The Sprint Planning Meeting The Sprint Backlog The Sprint Learning to self-manage, self-organize, self-improve Sprint Review and Retrospective Project Progress and Completion The Daily Scrum The Task Board and The Burndown Chart Information Radiators Closing a Scrum Project Summary and Next Steps Review of course goals, objectives, and content Exam prep next steps

Scrum Product Owner Exam Prep: In-House Training: Virtual In-House Training This workshop prepares you for the Scrum.org PSPO™ I certification. A voucher for the exam and the access information you will need to take the exam will be provided to you via email after you have completed the course. NOTE: If you have participated in any of IIL's other Scrum workshops, you can bypass this program and focus on reading/studying the Scrum Guide and taking practice exams from Scrum.org The Product Owner is responsible for maximizing the value of the product and the work of the Development Team. The Product Owner must be knowledgeable, available, and empowered to make decisions quickly in order for an Agile project to be successful. The Product Owner's key accountability is the Product Backlog. Managing, maintaining, and evolving the Product Backlog involves: Establishing a clear vision that engages the Development Team and stakeholders Clearly expressing Product Backlog items Ordering the items in the Product Backlog to best achieve the vision and goals Ensuring that the Product Backlog is visible, transparent, and clear to all Working with the Development Team throughout the project to create a product that fits the customer's need The Professional Scrum Product Owner™ I (PSPO I) certificate is a Scrum.org credential that enables successful candidates to demonstrate a fundamental level of Scrum mastery. PSPO I credential holders demonstrate an intermediate understanding of the Scrum framework, and how to apply it to maximize the value delivered with a product. They will exhibit a dedication to continued professional development, and a high level of commitment to their field of practice. Scrum.org does not require that you take their own sponsored or any preparatory training. However, training can facilitate your preparation for this credential. And this course is based on IIL's Scrum Product Owner Workshop, which is aligned with The Scrum Guide™. It will provide you with the information you need to pass the exam and IIL will make the arrangements for your online exam. You will be provided with an exam code and instructions, so that you can take the exam at your convenience, any time you are ready after the course. Passwords have no expiration date, but they are valid for one attempt only. See additional exam details on the next page. What you will Learn You'll learn how to: Successfully prepare for the Scrum.org PSPO I exam Identify the characteristics of a successful Product Owner Create a powerful vision statement Apply techniques to understand your customers and the market Manage and engage stakeholders Write effective user stories with acceptance criteria Utilize techniques to visualize and prioritize the Product Backlog Participate in the 5 Scrum events as the Product Owner Understand the Product Owner's role in closing a Scrum project Getting Started Introductions Workshop orientation Exam prep preview Fundamentals Recap Agile Manifesto, values, and mindset Product Owner characteristics Good vs. great Product Owner Product Ownership Product ownership Project vision Understand your customers and market Personas Stakeholder management and engagement The Product Backlog User Stories and Acceptance Criteria Preparing User Stories for a Sprint The Product Backlog Visualizing the Product Backlog Product Backlog Prioritization Technical Debt Sprint Planning and Daily Standups Sprint Planning Planning Poker Team Engagement Daily Standups Sprint Review, Retrospectives, and Closing Sprint Reviews Key Agile Patterns Retrospectives Closing the Project Summary and Next Steps Review of course goals, objectives, and content Exam prep next steps

Change Management Practitioner, a comprehensive program building on foundational knowledge. Dive into advanced concepts, models, and tools for effective organisational change. Develop the skills to lead, implement, and sustain successful change. About this course £297.00 19 lessons Accredited training Certificate of completion included Course curriculum IntroductionIntroduction Session 1Lesson - Change & the IndividualTest Your Knowledge Quiz Module 2Lesson - Change & the OrganisationTest Your Knowledge Quiz Module 3Lesson - Stakeholder Engagement & CommunicationTest Your Knowledge Quiz Module 4Lesson - Change PracticeTest Your Knowledge Quiz Supporting Documents APMG Candidate Guidance - Examinable Text by Chapter APMG Change Management Development Paper APMG Change Management Leaflet APMG Change Management Practitioner - Sample Exam PaperFile APMG Change Management Practitioner Candidate Guidance APMG Change Management Summary APMG Change Management Syllabus Study Timetable Accredited AgilePM training is provided by ITonlinelearning, APMG-International Accredited Training Organisation.

Use Cases for Business Analysis The use case is a method for documenting the interactions between the user of a system and the system itself. Use cases have been in the software development lexicon for over twenty years, ever since it was introduced by Ivar Jacobson in the late 1980s. They were originally intended as aids to software design in object-oriented approaches. However, the method is now used throughout the Solution Development Life Cycle from elicitation through to specifying test cases, and is even applied to software development that is not object oriented. This course identifies how business analysts can apply use cases to the processes of defining the problem domain through elicitation, analyzing the problem, defining the solution, and confirming the validity and usability of the solution. What you will Learn You'll learn how to: Apply the use case method to define the problem domain and discover the conditions that need improvement in a business process Employ use cases in the analysis of requirements and information to create a solution to the business problem Translate use cases into requirements Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Overview of use case modeling What is a use case model? The 'how and why' of use cases When to perform use case modeling Where use cases fit into the solution life cycle Use cases in the problem domain Use cases in the solution domain Use case strengths and weaknesses Use case variations Use case driven development Use case lexicon Use cases Actors and roles Associations Goals Boundaries Use cases though the life cycle Use cases in the life cycle Managing requirements with use cases The life cycle is use case driven Elicitation with Use Cases Overview of the basic mechanics and vocabulary of use cases Apply methods of use case elicitation to define the problem domain, or 'as is' process Use case diagrams Why diagram? Partitioning the domain Use case diagramming guidelines How to employ use case diagrams in elicitation Guidelines for use case elicitation sessions Eliciting the problem domain Use case descriptions Use case generic description template Alternative templates Elements Pre and post conditions Main Success Scenario The conversation Alternate paths Exception paths Writing good use case descriptions Eliciting the detailed workflow with use case descriptions Additional information about use cases Analyzing Requirements with Use Cases Use case analysis on existing requirements Confirming and validating requirements with use cases Confirming and validating information with use cases Defining the actors and use cases in a set of requirements Creating the scenarios Essential (requirements) use case Use case level of detail Use Case Analysis Techniques Generalization and Specialization When to use generalization or specialization Generalization and specialization of actors Generalization and specialization of use cases Examples Associating generalizations Subtleties and guidelines Use Case Extensions The <> association The <> association Applying the extensions Incorporating extension points into use case descriptions Why use these extensions? Extensions or separate use cases Guidelines for extensions Applying use case extensions Patterns and anomalies o Redundant actors Linking hierarchies Granularity issues Non-user interface use cases Quality considerations Use case modeling errors to avoid Evaluating use case descriptions Use case quality checklist Relationship between Use Cases and Business Requirements Creating a Requirements Specification from Use Cases Flowing the conversation into requirements Mapping to functional specifications Adding non-functional requirements Relating use cases to other artifacts Wire diagrams and user interface specifications Tying use cases to test cases and scenarios Project plans and project schedules Relationship between Use Cases and Functional Specifications System use cases Reviewing business use cases Balancing use cases Use case realizations Expanding and explaining complexity Activity diagrams State Machine diagrams Sequence diagrams Activity Diagrams Applying what we know Extension points Use case chaining Identifying decision points Use Case Good Practices The documentation trail for use cases Use case re-use Use case checklist Summary What did we learn, and how can we implement this in our work environment?

Duration 1 Days 6 CPD hours For the better part of every day, we are communicating to and with others. Whether it?s the speech you deliver in the boardroom, the level of attention you give your spouse when they are talking to you, or the look you give the cat, it all means something. This workshop will help participants understand the different methods of communication and how to make the most of each of them. 1 - Getting Started Icebreaker Housekeeping Items The Parking Lot Workshop Objectives 2 - The Big Picture What is Communication? How Do We Communicate? Other Factors in Communication 3 - Understanding Communication Barriers An Overview of Common Barriers Language Barriers Cultural Barriers Differences in Time and Place 4 - Paraverbal Communication Skills The Power of Pitch The Truth about Tone The Strength of Speed 5 - Non-Verbal Communication Understanding the Mehrabian Study All About Body Language Interpreting Gestures 6 - Speaking Like a STAR S = Situation T = Task A = Action R = Result Summary 7 - Listening Skills Seven Ways to Listen Better Today Understanding Active Listening Sending Good Signals to Others 8 - Asking Good Questions Open Questions Closed Questions Probing Questions 9 - Appreciative Inquiry The Purpose of AI The Four Stages Examples and Case Studies 10 - Mastering the Art of Conversation Level One: Discussing General Topics Level Two: Sharing Ideas and Perspectives Level Three: Sharing Personal Experiences Our Top Networking Tips 11 - Advanced Communication Skills Understanding Precipitating Factors Establishing Common Ground Using ?I? Messages 12 - Wrapping Up Words from the Wise Review of Parking Lot Lessons Learned Completion of Action Plans and Evaluations Additional course details: Nexus Humans Communication Strategies 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 Communication Strategies course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

This course explains how huge chunks of data can be analyzed and visualized using the power of the data analyst toolbox. You will learn Python programming, advanced pivot tables' concepts, the magic of Power BI, perform analysis with Alteryx, master Qlik Sense, R Programming using R and R Studio, and create stunning visualizations in Tableau Desktop.