1233 Model courses in Cardiff delivered Live Online

The aim of this course is to provide project managers, project engineers and project support staff with a toolkit they can use on their projects. The tools range from the simple that can be used on all projects to the advanced that can be used where appropriate. This programme will help the participants to: Identify and engage with stakeholders Use tools for requirements gathering and scope management Produce better estimates using a range of techniques Develop more reliable schedules Effectively manage delivery DAY ONE 1 Introduction Overview of the programme Review of participants' needs and objectives 2 Stakeholder management Using PESTLE to aid stakeholder identification Stakeholder mapping The Salience model Stakeholder engagement grid 3 Requirements management Using prototypes and models to elucidate requirements Prioritising techniques Roadmaps Requirements traceability 4 Scope management Work breakdown structures Responsibility assignment matrix 5 Delivery approaches Sequential Agile 6 Estimating Comparative estimating Parametric Bottom-up Three-point estimating Delphi and Planning Poker Creating realistic budgets DAY TWO 7 Scheduling Critical path analysis Smoothing and levelling Timeboxing Team boards Monte Carlo simulations Probability of completion 8 People management Situational Leadership The Tuckman model Negotiation Conflict management Belbin 9 Monitoring and control Earned value management 10 Course review and action planning Identify actions to be implemented individually Conclusion PMI, CAPM, PMP and PMBOK are registered marks of the Project Management Institute, Inc.

Duration 1.5 Days 9 CPD hours This course is intended for Application developers on the beginner and intermediate level seeking to create and deploy secure Android applications. Overview Understand Android software architecture. Understand Android?s security model. Build Android applications with security best practices in mind. Build more secure and more robust application that appeals to clients. This is a two-day (12 hours) professional course, which thoroughly covers the Android security model and concerns of both the developer and end-user point of view. This course is mapped for AND-802 exam. PermissionsManaging the Policy FileUsers? Data Privacy and ProtectionSecuring Storage Additional course details: Nexus Humans Android Security Essentials 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 Android Security Essentials 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 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

Duration 4 Days 24 CPD hours This course is intended for System installersSystem integratorsSystem administratorsNetwork administratorsSolutions designers Overview After completing this course, you should be able to:Describe the Cisco IOS XR 64-Bit software architecture and Linux system fundamentalsDescribe the major differences between classic Cisco IOS XR software and Cisco IOS XR 64-Bit software on the ASR 9000 Series routersMigrate an ASR 9000 Series router from classic IOS XR software to Cisco IOS XR 64-Bit softwarePerform and explain Cisco IOS XR 64-Bit software installationsConfigure and describe Cisco IOS XR 64-Bit software features The Cisco ASR 9000 Series IOS XR 64-Bit Software Migration and Operational Enhancements (IOSXR211) v1.0 course covers the migration from classic 32-bit Cisco IOS© XR software to Cisco IOS XR 64-Bit software on the Cisco© ASR 9000 Series Aggregation Services Routers. This course will also examine the software architecture, boot process, and auto-provisioning of the Cisco IOS XR 64-bit software, as well as showing you how to install Cisco IOS XR and third-party software packages. In addition, it will investigate data models and show you how to implement telemetry, model-driven programmability, and application hosting services. Software Architecture and Linux Fundamentals Cisco IOS XR 64-Bit Software Fundamentals Cisco ASR 9000 Series IOS XR 64-Bit Software vs. Classic 32-Bit Software Exploring Linux Fundamentals Creating User Profiles Cisco IOS XR 64-Bit Software Installation Examining Resource Allocations and Media Mappings Migrating to Cisco IOS XR 64-Bit Software Examining the Boot Process Performing Disaster Recovery Installing Software Packages Cisco IOS XR 64-Bit Software Features Investigating Data Models Implementing Telemetry Exploring Model-Driven Programmability Employing Application Hosting

This course starts with the basics then moves seamlessly to an intermediate level. It includes a comprehensive yet balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to use the online Power BI service. It looks at authoring tools that enables you to connect to and transform data from a variety of sources, allowing you to produce dynamic reports using a library of visualisations. Once you have those reports, the course looks at the seamless process of sharing those with your colleagues by publishing to the online Power BI service. The aim of this course is to provide a strong understanding of the Power BI analysis process, by working with real-world examples that will equip you with the necessary skills to start applying your knowledge straight away. 1 Getting started The Power BI process Launching Power BI Desktop The four views of Power BI Dashboard visuals 2 Connecting to files Connect to data sources Connect to an Excel file Connect to a CSV file Connect to a database Import vs. DirectQuery Connect to a web source Create a data table 3 Transforming data The process of cleaning data Column data types Remove rows with filters Add a custom column Append data to a table Fix error issues Basic maths operations 4 Build a data model Table relationships Manage table relationships 5 Merge queries Table join kinds Merging tables 6 Create report visualisations Creating map visuals Formatting maps Creating chart visuals Formatting chart Tables, matrixes, and cards Control formatting with themes Filter reports with slicers Reports for mobile devices Custom online visuals Export report data to Excel 7 The power query editor Fill data up and down Split columns by delimiter Add conditional columns Merging columns 8 The M formula Creating M functions Create an IF function Create a query group 9 Pivot and unpivot tables Pivot tables in the query editor Pivot and append tables Pivot but don't summarise Unpivot tables Append mismatched headers 10 Data modelling revisited Data model relationships Mark a calendar as a date table 11 Introduction to calculated columns New columns vs. measures Creating a new column calculation The SWITCH function 12 Introduction to DAX measures Common measure categories The SUM measure Adding measures to visuals COUNTROWS and DISINCTCOUNT functions DAX rules 13 The CALCULATE measure The syntax of CALCULATE Things of note about CALCULATE 14 The SUMX measure The SUMX measure X iterator functions Anatomy of SUMX 15 Introduction to time intelligence Importance of a calendar table A special lookup table The TOTALYTD measure Change year end in TOTALYTD 16 Hierarchy, groups and formatting Create a hierarchy to drill data Compare data in groups Add conditional formatting 17 Share reports on the web Publish to the BI online service Get quick insights Upload reports from BI service Exporting report data What is Q&A? Sharing your reports 18 Apply your learning Post training recap lesson

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Duration 3 Days 18 CPD hours This course is intended for This class is designed for individuals who are (or will soon be) supporting a Salesforce implementation in a decision-making capacity. This includes, but is not limited to, business analysts, IT managers, project managers, executive leaders, and executive sponsors. This class is not recommended for individuals tasked with solution-building. Overview When you complete this course, you will be able to: Identify key stakeholders needed for a successful Salesforce implementation. Describe the Salesforce data model as it relates to Customer 360, Salesforce Clouds, and the Salesforce Platform. Communicate the appropriate security measures needed to control org and data access. Discuss which standard or custom objects and applications should be implemented based on specific requirements and use cases. Effectively strategize how to migrate data into your Salesforce org while maintaining high data quality. Understand Salesforce automation tools and how they solve for various business challenges. Analyze Salesforce data with Reports and Dashboards. Navigate the key phases and milestones of a Salesforce implementation. Explore Salesforce features and functionality and gain the knowledge to make Salesforce implementation decisions with confidence. In this 3-day, heavily discussion-based class, learn about standard and custom objects and applications, data management, data visualization, flow automation tools, security mechanisms, and more. Successfully navigate the key phases and milestones of a Salesforce implementation, effectively communicate business needs, and provide directives to team members tasked with solution-building to deliver a robust Salesforce solution that achieves business goals. Salesforce Data Model Discover the Customer 360 Platform Examine Salesforce Clouds Navigate the Salesforce Platform Review the Salesforce Platform Data Model Understand Data Visualization Security & Access Create Users Access the Org Control Data Objects & Applications Review Standard Objects Understand Custom Objects Explore Standard Applications Discover Custom Applications Salesforce Customizations Work with Fields Design Page Layouts Understand Record Types Review Dynamic Capabilities Successful Data Management Determine Data Strategy Create Data Ensure Data Quality Process Automation Streamline Business Processes Using Automation Tools Learn Purpose-Driven Automation Automate With Flow Data Analysis Using Reports & Dashboards Organize Reports and Dashboards Build Reports Create Dashboards Create an Analytics Strategy Adoption & Continued Improvement Adopt Your Implementation Evaluate Continued Improvements Additional course details: Nexus Humans Understand and Drive Your Salesforce Implementation ( BSX101 ) 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 Understand and Drive Your Salesforce Implementation ( BSX101 ) 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 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 The course is designed for individuals who want to gain in-depth knowledge and practice in the discipline of Business Analysis (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 Business Analysis principles and techniques. Key areas are: The breath of the role of a Business Analyst The processes and techniques of strategy analysis Investigation of an organization's business systems Techniques used within stakeholder analysis and the need for analyzing perspectives Conceptual modelling and business activity models Business improvements through gap analysis The Business case within the business change lifecycle 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 Business Analysis Course Introduction Let?s Get to Know Each Other Course Overview Course Learning Objectives Course Structure Course Agenda Introduction to Business Analysis Practice Exam Details Business Analysis Certification Scheme Rationale for Business Analysis The role of the BA throughout the stages of the Business change lifecycle The scope of the BA role within the context of the range of analysis activities Three areas of competencies Understanding the Strategic Context Techniques in practice: MOST Resource audit PESTLE Porter's Five Forces SWOT analysis CSF, KPI and Performance target Balanced Business Score Card Understanding the Current Situation Identification of stakeholder categories Identification of relevant investigation techniques The rationale for taking a holistic view Rich pictures, Mind Maps and Fishbone diagrams Stakeholder Analysis and Management Power/interest and level of interest Appropriate stakeholder management strategy Stakeholder perspectives and CATWOE technique Analysing and Modelling Business Activities Conceptual models of a business situation Five types of high level activity Planning activities Enabling activities Doing activities Monitoring and control activities Three types of business events The consensus business activity model Identifying Potential Solutions Different categories of business rules Gap analysis (through conceptual business activity model and as-is business situation) Components of a new business model Building the Business Case Rationale for the development of a business case Contents of a business case Identification of tangible/intangible costs and benefits, risks and impacts Rationale for the financial case and appraisal techniques Business case review in the business change lifecycle Additional course details: Nexus Humans Business Analysis - Practice 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 Business Analysis - Practice 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.

Why Learn Vectorworks 2d | 3d and Spotlight training Course? Course info Led by experts, this comprehensive program equips you with skills in 2D drafting, immersive 3D modeling, and dynamic lighting design. Master Vectorworks' powerful features, including the Spotlight module tailored for entertainment and events. Duration: 16 hrs Method: 1-on-1, Personalized attention. Schedule: Tailor your own hours, available from Mon to Sat between 9 am and 7 pm. Or Call 02077202581 or WhatsApp 07970325184. Course Details: Format: 1-on-1 Training Schedule: Flexible, Any Day, Anytime (Monday to Saturday), 9 AM to 7 PM Duration: Customizable to Individual Learning Pace Content: Comprehensive training in Vectorworks, focusing on 2D Drafting, Immersive 3D Modeling, and Dynamic Lighting Design. Specialization: Spotlight Module for Entertainment and Events Instructors: Expert-led sessions ensuring personalized attention and effective learning. Outcome: Mastery of Vectorworks' Powerful Features, Proficiency in 2D and 3D Design, and Expertise in Dynamic Lighting Design for Entertainment Purposes. Note: Schedule and course duration are flexible to accommodate individual preferences and learning needs. Course Details: Format: 1-on-1 Training Schedule: Flexible, Any Day, Anytime (Monday to Saturday), 9 AM to 7 PM Duration: Customizable to Individual Learning Pace Content: Comprehensive training in Vectorworks, focusing on 2D Drafting, Immersive 3D Modeling, and Dynamic Lighting Design. Specialization: Spotlight Module for Entertainment and Events Instructors: Expert-led sessions ensuring personalized attention and effective learning. Outcome: Mastery of Vectorworks' Powerful Features, Proficiency in 2D and 3D Design, and Expertise in Dynamic Lighting Design for Entertainment Purposes. Note: Schedule and course duration are flexible to accommodate individual preferences and learning needs. Vectorworks 2D | 3D and Spotlight Training Course Course Duration: 16 hours Course Description: I. Introduction to Vectorworks (1 hour) Overview of Vectorworks software and its applications Familiarization with the user interface and navigation Customizing preferences and settings for optimal workflow II. 2D Drawing Tools (2 hours) Using basic drawing tools for creating lines, rectangles, circles, and polygons Utilizing text and dimension tools for annotations Applying modify tools for editing and transforming objects Organizing elements with layers and classes III. 3D Modeling Tools (3 hours) Introduction to extrude, revolve, sweep, and loft tools for 3D modeling Creating 3D objects from 2D shapes for spatial representation Modifying and refining 3D models Exploring the 3D modeling environment IV. Advanced 3D Modeling Tools (2 hours) Utilizing solid modeling tools for complex geometry creation Performing Boolean operations to combine or subtract shapes Creating and utilizing symbols for efficient workflow V. Introduction to Spotlight (1 hour) Overview of the Spotlight workspace and its features Adding and configuring lighting devices for stage and event design Creating and modifying lighting positions for accurate placement VI. Spotlight Tools and Techniques (3 hours) Creating and editing lighting instruments for customized setups Using visualization tools for lighting simulations Creating and applying labels and legends for documentation Generating worksheets and reports for lighting analysis VII. Advanced Spotlight Techniques (2 hours) Utilizing video and projection tools for multimedia presentations Incorporating audio and sound systems for immersive experiences Understanding rigging and hoisting for stage setup Managing paperwork and documentation for effective planning VIII. Integration with Other Software (1 hour) Importing and exporting files to collaborate with other software Utilizing Vectorworks in CAD and BIM workflows for interoperability Exploring plugins and add-ons for expanded functionality IX. Project-based Exercises (1 hour) Applying learned techniques to real-world scenarios Creating a lighting plan for a concert or theater production Designing a 3D model of a building or interior space Free 30-day, BIM & CAD Software Trial Request | Vectorworks https://www.vectorworks.net/trial Vectorworks Trial Version Request. Please fill out the following form. We will provide you with an evaluation serial number to activate your trial copy. Learning Outcomes of Vectorworks 2D | 3D and Spotlight Training Course: Master Vectorworks with 2D and 3D design skills. Create precise 2D drawings and detailed 3D models. Learn specialized tools for lighting and event planning in Spotlight. Optimize workflows and improve project coordination. Produce realistic renderings and visualizations. Apply skills to real-world projects in architecture and events.