134 Courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools. Overview After completing this course, students will be able to: - Identify independent and dependent variables and measurement levels in their own analytical work scenarios. - Identify variables of interest in relational database tables. - Choose a data aggregation level and data set design appropriate for the intended analysis and tool. - Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others. - Create stored procedures, views, and functions to modularize data retrieval code. This course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. 1 - INTRODUCTION TO TSQL FOR BUSINESS INTELLIGENCE Two Approaches to SQL Programming TSQL Data Retrieval in an Analytics / Business Intelligence Environment The Database Engine SQL Server Management Studio and the CarDeal Sample Database Identifying Variables in Tables SQL is a Declarative Language Introduction to the SELECT Query Lab 1: Introduction to TSQL for Business Intelligence 2 - TURNING TABLE COLUMNS INTO VARIABLES FOR ANALYSIS: SELECT LIST EXPRESSIONS, WHERE, AND ORDER BY Turning Columns into Variables for Analysis Column Expressions, Data Types, and Built-in Functions Column aliases Data type conversions Built-in Scalar Functions Table Aliases The WHERE clause ORDER BY Lab 1: Write queries 3 - COMBINING COLUMNS FROM MULTIPLE TABLES INTO A SINGLE DATASET: THE JOIN OPERATORS Primary Keys, Foreign Keys, and Joins Understanding Joins, Part 1: CROSS JOIN and the Full Cartesian Product Understanding Joins, Part 2: The INNER JOIN Understanding Joins, Part 3: The OUTER JOINS Understanding Joins, Part 4: Joining more than two tables Understanding Joins, Part 5: Combining INNER and OUTER JOINs Combining JOIN Operations with WHERE and ORDER BY Lab 1: Write SELECT queries 4 - CREATING AN APPROPRIATE AGGREGATION LEVEL USING GROUP BY Identifying required aggregation level and granularity Aggregate Functions GROUP BY HAVING Order of operations in SELECT queries Lab 1: Write queries 5 - SUBQUERIES, DERIVED TABLES AND COMMON TABLE EXPRESSIONS Non-correlated and correlated subqueries Derived tables Common table expressions Lab 1: Write queries 6 - ENCAPSULATING DATA RETRIEVAL LOGIC Views Table-valued functions Stored procedures Creating objects for read-access users Creating database accounts for analytical client tools Lab 1: Encapsulating Data Retrieval Logic 7 - GETTING YOUR DATASET TO THE CLIENT Connecting to SQL Server and Submitting Queries from Client Tools Connecting and running SELECT queries from: Excel PowerBI RStudio Exporting datasets to files using Results pane from SSMS The bcp utility The Import/Export Wizard Lab 1: Getting Your Dataset to the Client Additional course details: Nexus Humans 55232 Writing Analytical Queries for Business Intelligence 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 55232 Writing Analytical Queries for Business Intelligence 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.

Our masterclass series goes behind the studio door and explores the processes of globally respected designers.

Querying Microsoft SQL Server course description This course covers the technical skills required to write basic Transact-SQL queries for Microsoft SQL Server and provides the foundation for all SQL Server-related disciplines; namely, database administration, database development and business intelligence. This course helps prepare for exam 70-761. Note: This course is designed for SQL Server 2014or SQL Server 2016. What will you learn Write SELECT statements. Create and implement views and table-valued functions. Transform data by implementing pivot, unpivot, rollup and cube. Create and implement stored procedures. Add programming constructs such as variables, conditions, and loops to T-SQL code. Querying Microsoft SQL Server course details Who will benefit: Database administrators, database developers, and business intelligence professionals. SQL power users, namely, report writers, business analysts and client application developers. Prerequisites: Database fundamentals Duration 5 days Querying Microsoft SQL Server course contents Introduction to Microsoft SQL Server Management studio, creating and organizing T-SQL scripts, using books online. Hands on working with SQL Server tools. T-SQL querying Introducing T-SQL, sets, predicate logic, logical order of operations in SELECT statements, basic SELECT statements, queries that filter data using predicates, queries that sort data using ORDER BY. Hands on introduction to T-SQL querying. Writing SELECT queries Writing simple SELECT statements, eliminating duplicates with DISTINCT, column and table aliases, simple CASE expressions. Hands on writing basic SELECT statements. Querying multiple tables cross joins and self joins, write queries that use Inner joins, write queries that use multiple-table inner joins, write queries that use self-joins, write queries that use outer joins, write queries that use cross joins. Hands on querying multiple tables. Sorting and filtering data Sorting data, filtering data with predicates, filtering data with TOP and OFFSET-FETCH, working with unknown values, WHERE clause, ORDER BY clause, TOP option, OFFSET-FETCH clause. Hands on sorting and filtering data. SQL Server data types Introducing SQL Server data types, Character data, date and time data, queries that return date and time data, write queries that use date and time functions, write queries that return character data, write queries that return character functions. Hands on working with SQL Server data types. DML Adding data to tables, modifying and removing data, generating automatic column values, Inserting records with DML, updating and deleting records using DML. Hands on using DML to modify data. Built-in functions Queries with built-in functions, conversion functions, logical functions, functions with NULL, queries that use conversion functions, queries that use logical functions, queries that test for nullability. Hands on built-in functions Grouping and aggregating data Aggregate functions, the GROUP BY clause, filtering groups with HAVING, queries that use the GROUP BY clause, queries that use aggregate functions, queries that use distinct aggregate functions, queries that filter groups with the HAVING clause. Hands on grouping and aggregating data. Subqueries Self-contained subqueries, correlated subqueries, EXISTS predicate with subqueries, scalar and multi-result subqueries. Hands on subqueries. Table expressions Views, inline table-valued functions, derived tables, common table expressions. queries that use views, write queries that use derived tables, Common Table Expressions (CTEs), write queries that se inline Table valued expressions (TVFs). Hands on table expressions. Set operators The UNION operator, EXCEPT and INTERSECT, APPLY, queries that use UNION set operators and UNION ALL, CROSS APPLY and OUTER APPLY operators. Hands on set operators. Windows ranking, offset, and aggregate functions OVER, window functions, ranking functions, offset functions, window aggregate functions. Hands on; windows ranking, offset, and aggregate functions. Pivoting and grouping sets PIVOT and UNPIVOT, grouping sets, queries that use the PIVOT operator, queries that use the UNPIVOT operator, queries that use the GROUPING SETS CUBE and ROLLUP subclauses. Hands on pivoting and grouping sets Executing stored procedures Querying data with stored procedures, passing parameters to stored procedures, simple stored procedures, dynamic SQL, the EXECUTE statement to invoke stored procedures. Hands on executing stored procedures. Programming with T-SQL T-SQL programming elements, controlling program flow, declaring variables and delimiting batches, control-of-flow elements, variables in a dynamic SQL statement, synonyms. Hands on programming with T-SQL Error handling T-SQL error handling, structured exception handling, redirect errors with TRY/CATCH, THROW to pass an error message back to a client. Hands on implementing error handling. Implementing transactions Transactions and the database engines, controlling transactions, BEGIN, COMMIT, and ROLLBACK, adding error handling to a CATCH block. Hands on implementing transactions.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

Once you join one of our group classes at the studio you will participate in the warm-up, class and cool down.  You will be able to hear the instructor and the class however the instructor will not be able to interact with you.  This is purely a watch and learn class.

https://www.instagram.com/masterpeacelondon/

BRIT Creative Coaching is structured for Performing Arts Students to reach their goals. Discover and build new skills that you need outside the studio.

Duration 1 Days 6 CPD hours This course is intended for Multi-role (consumers, business authors, professional authors, developers, administrators, modelers, project managers) This course provides students with an overview of the IBM Cognos Analytics suite of products and their underlying architecture. Students will examine each component as it relates to an Analytics solution & will be shown a range of resources. IBM Cognos Analytics Describe IBM Cognos Analytics Describe IBM Cognos Analytics components Describe IBM Cognos architecture at a high level Describe IBM Cognos security at a high level Consume Content in IBM Cognos Analytics Where do consumers access BI content? Use published reports Drill through to related data Specify run report options Specify properties of an entry Alerts and Watch Items Create Reports in IBM Cognos Analytics Overview of reporting and report authoring Identify package types, uploaded files, and data modules available for reporting Examine IBM Cognos Analytics - Reporting Examine the interface Explore different report types Create a simple, sorted, and formatted report Create a report view Create a subscription Create an Active Report Import and report on personal data Create Dashboards in IBM Cognos Analytics Describe IBM Cognos Dashboarding Identify the IBM Cognos Dashboarding user interface Add report content and tools to create dashboards Widget-to-widget communication Filter data in the dashboard Sort, group and ungroup, and calculate data Create Metadata Models in IBM Cognos Analytics Define IBM Cognos Framework Manager and its purpose Describe the IBM Cognos Framework Manager environment Describe IBM Cognos Cube Designer Get high-level content from Dynamic Cubes course and/or FM course Web-based Modeling Create Data Modules Extend IBM Cognos Analytics Introduction to IBM Cognos Mobile Key features Examine Cognos Mobile architecture Identify supported products Introduction to IBM Cognos BI for Microsoft Office Describe Cognos Analysis for Excel (CAF) Compare IBM Cognos Analytics & IBM Cognos BI New features in IBM Cognos Analytics Changes from IBM Cognos BI to IBM Cognos Analytics Legacy option Examine Event Studio Examine the role of Event Studio in Performance Management List the benefits of Event Studio Examine Metric Studio Identify scorecards, metrics, and metric types Organize metrics with strategies Track initiatives with projects

Duration 3 Days 18 CPD hours This course is intended for This course is designed for project managers, Scrum masters, business analysts, and team leaders looking to effectively manage their development projects using Team Foundation Server 2017. Overview The course also demonstrates how TFS facilitates the use of storyboards to prototype experiences, request stakeholder feedback, foster team collaboration, and generate reports. The final two modules of the course provide an overview of how testers and developers can work effectively using appropriate tools in the Visual Studio family. In this course, attendees will plan a new software development project and go through the steps to initiate the project using Visual Studio 2017. This includes recording requirements, creating a product backlog, and estimating effort for backlog items. Introducing the Microsoft Visual Studio 2017 Family What?s new in Visual Studio 2017 Overview of the Visual Studio 2017 family Overview of product features Project workflow across the Visual Studio 2017 suite of products Initiating a New Project Organizing projects in TFS Understanding process templates Creating a new team project Setting team project properties Switching between team projects Work Item Primer Overview of work items Traceability between work items Searching and creating custom queries Work item charting and pinning charts Work item tagging Configuring project notifications Creating our Product Backlog Examining requirement types Creating backlog items Creating requirement hierarchies using features The importance of acceptance criteria Agile Estimation Introduction to estimation Using story points Planning Poker and other popular estimation techniques Adding your estimates to TFS work items Working from the Product Backlog Introducing the Kanban board Entering and editing details on the Kanban board Customizing columns, including using split columns and limiting WIP Recording our Definition of Done (DoD) Understanding the Cumulative Flow Diagram Working in Sprints Specifying your sprint schedule and your team capacity Selecting items for the sprint backlog using forecasting Decomposing requirements into tasks Using burndown charts to track progress Monitoring work using the task board Working with unparented work items Retrospectives The importance of retrospectives Conducting an efficient sprint retrospective What you should avoid in your retrospective Working with TFS Teams Configuring teams in our team project Managing work from a master backlog Allocating work to our teams Configuring iterations for TFS teams Enhancing Requirements Using Storyboards Overview of storyboarding capabilities Creating a storyboard to illustrate a requirement Linking a storyboard to a work item Getting Stakeholder Feedback Introducing the Microsoft Feedback Client Using the Microsoft Feedback Client to provide rich feedback to the team Adding continuous feedback into your workflow Fostering Team Collaboration An overview of the various clients The use of email in sharing information Choosing the appropriate client tool Creating and Customizing Reports Overview of reporting architecture Reviewing the out of the box reports Adding new reports Creating ad hoc reports using Excel Overview of Agile Testing The role of the tester in a sprint planning meeting A lap around web-based test management Creating a test plan Creating manual test cases from requirements Overview of Agile Development Using My Work to select tasks from the sprint backlog Understanding the value of linking changesets to work items The importance of unit testing Creating a continuous integration build Additional course details: Nexus Humans Managing Agile Projects Using TFS 2017 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 Managing Agile Projects Using TFS 2017 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.

Our masterclass series goes behind the studio door and explores the processes of globally respected people, studios and businesses.