144 Courses in Cardiff delivered Live Online

Use Cases for Business Analysis: In-House Training 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?

Whetstone Communications and comms2point0 are pleased to bring you the Data Bites series of free webinars. Our aim is to boost interest and levels of data literacy among not-for-profit communicators.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Microsoft Office 2016 Complete Course Course Overview: The "Microsoft Office 2016 Complete Course" is designed to provide learners with comprehensive knowledge and essential skills in the core Microsoft Office applications. This course offers in-depth coverage of Microsoft Word, Excel, PowerPoint, Outlook, and Access, enabling participants to confidently use these programs in professional environments. By the end of the course, learners will be equipped to create, manage, and analyse documents, spreadsheets, presentations, emails, and databases with proficiency. This course is an invaluable resource for those looking to enhance their productivity and improve their digital skills, making them more competitive in the job market. Course Description: The "Microsoft Office 2016 Complete Course" delves into the key functionalities of Microsoft Office, with modules dedicated to each major application. Learners will explore the features of Word for document creation and editing, Excel for data analysis and management, PowerPoint for effective presentations, Outlook for email and calendar management, and Access for database handling. Each module is structured to help learners understand the software’s core functions and how to apply them in real-world scenarios. Upon completion, learners will have developed a strong foundation in using Office 2016, boosting their ability to operate efficiently and effectively in modern workplaces. This course is suitable for individuals seeking to increase their office productivity and streamline their daily tasks. Microsoft Office 2016 Complete Course Curriculum: Module 01: Microsoft Word 2016 Module 02: Microsoft Excel 2016 Module 03: Microsoft PowerPoint 2016 Module 04: Microsoft Outlook 2016 Module 05: Microsoft Access 2016 (See full curriculum) Who is this course for? Individuals seeking to improve their office productivity skills. Professionals aiming to advance in roles requiring Microsoft Office proficiency. Beginners with an interest in data management, communication, and office software. Those wishing to enhance their CV and increase career opportunities in administrative and support roles. Career Path: Office Administrator Executive Assistant Data Analyst Personal Assistant Administrative Support Specialist Project Coordinator

Learn with Case Study - Market Research Course Overview: This course, "Learn with Case Study - Market Research," provides an in-depth understanding of the principles and techniques used in market research. It is designed to equip learners with the knowledge necessary to assess market trends, consumer behaviour, and competitive landscapes effectively. Through the use of real-world case studies, participants will gain valuable insights into the application of market research methodologies in various industries. By the end of the course, learners will be able to conduct research, analyse data, and make informed decisions that drive business strategies and growth. This course is ideal for those seeking to enhance their market research skills and apply them to professional practice. Course Description: In this course, learners will explore the core concepts of market research, including data collection, analysis techniques, and the interpretation of findings. The course integrates case studies to demonstrate how these methods are applied in real-life scenarios across different sectors. Key topics covered include survey design, focus groups, consumer behaviour analysis, and competitor research. Learners will develop the ability to evaluate and synthesise market data to inform strategic business decisions. The course encourages critical thinking, data interpretation, and strategic application, ensuring that learners can effectively utilise market research to support business objectives. By the end of the course, participants will have the skills to execute comprehensive market research projects. Learn with Case Study - Market Research Curriculum: Module 01: Introduction to Market Research Module 02: Data Collection Techniques Module 03: Case Study: Market Research in Action Module 04: Data Analysis and Interpretation Module 05: Consumer Behaviour and Market Segmentation Module 06: Reporting and Presenting Research Findings (See full curriculum) Who is this course for? Individuals seeking to improve their market research skills. Professionals aiming to enhance their strategic decision-making abilities. Beginners with an interest in understanding market dynamics. Those working in marketing, sales, or business strategy roles. Career Path: Market Research Analyst Marketing Manager Business Development Specialist Consumer Insights Analyst Data Analyst

Python Programming: Beginner To Expert Course Overview The "Python Programming: Beginner to Expert" course provides a comprehensive learning journey from the basics of Python to advanced programming techniques. Designed to equip learners with the skills necessary to become proficient Python developers, this course covers a broad range of essential topics, including data types, operators, functions, error handling, and object-oriented programming (OOP). By the end of the course, learners will gain the expertise needed to develop complex applications and tackle real-world problems using Python. The course is ideal for those looking to deepen their understanding of programming and advance their careers in software development, data science, or automation. Course Description This course delves deeply into Python programming, beginning with the fundamentals and progressing to advanced concepts. Learners will explore core programming techniques, including control flow, functions, and error handling, as well as specialized topics such as object-oriented programming (OOP) and libraries like NumPy and Pandas. The course also covers career development topics, such as how to start a career in Python programming. Students will gain a solid understanding of Python’s capabilities and how to apply them across a variety of programming contexts, from scripting to data analysis and more. With its structured modules and clear guidance, learners will finish the course ready to take on more advanced programming projects and pursue roles in the field. Python Programming: Beginner To Expert Curriculum Module 01: Introduction to Python Programming from A-Z Module 02: Getting Familiar with Python Module 03: Basic Data Types Module 04: Python Operators Module 05: Advanced Data Types Module 06: Control Flow Part 1 Module 07: Control Flow Part 2 Module 08: Python Functions Module 09: User Input and Error Handling Module 10: Python Advanced Functions Module 11: Python Scripting and Libraries Module 12: NumPy Module 13: Pandas Module 14: Introduction to OOP Module 15: Advanced OOP Module 16: Starting a Career in Python (See full curriculum) Who is this course for? Individuals seeking to start a career in Python programming. Professionals aiming to enhance their programming skills for career development. Beginners with an interest in software development, data science, or automation. Those looking to expand their programming knowledge in a structured and progressive way. Career Path Python Developer Software Engineer Data Analyst Data Scientist Automation Specialist Web Developer Backend Developer

Developing the Business Case: Virtual In-House Training Business analysts must be able to create business case documents that highlight project benefits, costs, and risks. The business case is based on the real business need to be solved. These become parts of proposals, feasibility studies, and other decision support documents. This course teaches the purpose, structure, and content of a business case. It presents the basic techniques for determining financial ROI, non-tangible benefits, and the probability of meeting expectations. What you will Learn At the end of this program, you will be able to: Perform feasibility studies Justify the business investment to solve the business problem Prepare an effective business case document Plan and implement a business case approval process Foundation Concepts The role of the BA An introduction to the BABOK® Guide The business analyst and the product / project life cycle (PLC) The business case deliverable Introducing the Business Case Process The BA and strategy analysis The BA and the business case process (BCP) The BA during the business case process (BCP) The BA after the business case process (BCP) Importance of defining solution performance metrics Defining the Business Need Overview of defining the business need Business needs: problem / opportunity statement Product vision Objectives and constraints Exploring Business Case Solutions Overview of exploring solutions Solution identification for feasibility Solution definition for analysis Assessing project risks Justifying the Business Case Overview of justifying the business case Qualitative justification Quantitative justification Approving the Business Case Overview of business case approval Developing recommendations Preparing the decision package - documents Preparing the decision package - presentations

Business Analysis Fundamentals: Virtual In-House Training This course is part of IIL's Business Analysis Certificate Program (BACP), a program designed to help prepare individuals to pass the IIBA® Certification exam to become a Certified Business Analysis Professional (CBAP™). This course teaches participants the overall process of business analysis and where it fits in the bigger picture of the project life cycle and the business context. The course is interactive and combines discussion, active workshops, and demonstrations of techniques. The goal is bottom-line results that cut through the real-world problems facing people seeking to improve the way they operate to develop new and improved systems and products or otherwise deliver results through project performance. What you will Learn At the end of this program, you will be able to: Define the solution scope Work with the development team in the systems testing stage Ensure the solution is usable in the business environment Foundation Concepts Defining the business analyst (BA) function The role of the BA as change agent An introduction to the BABOK® Guide BA roles and relationships through the project life cycle (PLC) Business Analysis Planning and Monitoring Overview of business analysis planning and monitoring (BAP&M) Business analysis planning and monitoring - process and tools Business analysis planning and monitoring - roles and responsibilities Business analysis planning and monitoring - governance, information management, and performance improvement Elicitation and Collaboration Overview of elicitation and collaboration Elicitation and collaboration techniques Requirements Life Cycle Management Overview of requirements life cycle management Requirements life cycle management task details Strategy Analysis Overview of strategy analysis Analyze current state Define future state Assess risks Define change strategy Requirements Analysis and Design Definition Overview of requirements analysis and design definition (RA&DD) The anatomy of requirements RA&DD task descriptions RA&DD techniques Solution Evaluation Overview of solution evaluation Solution evaluation tasks Solution evaluation in development stages Underlying Competencies Overview of underlying competencies (UC) Underlying competencies

Use Cases for Business Analysis: Virtual In-House Training 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?

This Tableau Desktop Training course is a jumpstart to getting report writers and analysts with little or no previous knowledge to being productive. It covers everything from connecting to data, through to creating interactive dashboards with a range of visualisations in two days of your time. For Private options, online or in-person, please send us details of your requirements: This Tableau Desktop Training course is a jumpstart to getting report writers and analysts with little or no previous knowledge to being productive. It covers everything from connecting to data, through to creating interactive dashboards with a range of visualisations in two days of your time. Having a quick turnaround from starting to use Tableau, to getting real, actionable insights means that you get a swift return on your investment of time and money. This accelerated approach is key to getting engagement from within your organisation so everyone can immediately see and feel the impact of the data and insights you create. This course is aimed at someone who has not used Tableau in earnest and may be in a functional role, eg. in sales, marketing, finance, operations, business intelligence etc. The course is split into 3 phases and 9 modules: PHASE 1: GET READY MODULE 1: LAUNCH TABLEAU Check Install & Setup Why is Visual Analytics Important MODULE 2: GET FAMILIAR What is possible How does Tableau deal with data Know your way around How do we format charts Dashboard Basics – My First Dashboard MODULE 3: DATA DISCOVERY Connecting to and setting up data in Tableau How Do I Explore my Data – Filters & Sorting How Do I Structure my Data – Groups & Hierarchies, Visual Groups How Tableau Deals with Dates – Using Discrete and Continuous Dates, Custom Dates Phase 2: GET SET MODULE 4: MAKE CALCULATIONS How Do I Create Calculated Fields & Why MODULE 5: MAKE CHARTS Charts that Compare Multiple Measures – Measure Names and Measure Values, Shared Axis Charts, Dual Axis Charts, Scatter Plots Showing Relational & Proportional Data – Pie Charts, Donut Charts, Tree Maps MODULE 6: MAKE TABLES Creating Tables – Creating Tables, Highlight Tables, Heat Maps Phase 3: GO MODULE 7: ADD CONTEXT Reference Lines and Bands MODULE 8: MAKE MAPS Answering Spatial Questions – Mapping, Creating a Choropleth (Filled) Map MODULE 9: MAKE DASHBOARDS Using the Dashboard Interface Dashboard Actions This training course includes over 25 hands-on exercises and quizzes to help participants “learn by doing” and to assist group discussions around real-life use cases. Each attendee receives a login to our extensive training portal which covers the theory, practical applications and use cases, exercises, solutions and quizzes in both written and video format. Students must use their own laptop with an active version of Tableau Desktop 2018.2 (or later) pre-installed. What People Are Saying About This Course “Excellent Trainer – knows his stuff, has done it all in the real world, not just the class room.”Richard L., Intelliflo “Tableau is a complicated and powerful tool. After taking this course, I am confident in what I can do, and how it can help improve my work.”Trevor B., Morrison Utility Services “I would highly recommend this course for Tableau beginners, really easy to follow and keep up with as you are hands on during the course. Trainer really helpful too.”Chelsey H., QVC “He is a natural trainer, patient and very good at explaining in simple terms. He has an excellent knowledge base of the system and an obvious enthusiasm for Tableau, data analysis and the best way to convey results. We had been having difficulties in the business in building financial reports from a data cube and he had solutions for these which have proved to be very useful.”Matthew H., ISS Group