This qualification is ideal for anyone who prepares and serves food, as it provides learners with a basic understanding of nutrition and the requirements of special diets to enable the planning and provision of well-balanced meals that will have a positive impact on health.
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.
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
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Duration 3 Days 18 CPD hours This course is intended for The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Prerequisites Understanding core data concepts. Knowledge of working with relational data in the cloud. Knowledge of working with non-relational data in the cloud. Knowledge of data analysis and visualization concepts. DP-900T00 Microsoft Azure Data Fundamentals is recommended 1 - Discover data analysis Overview of data analysis Roles in data Tasks of a data analyst 2 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 3 - Get data in Power BI Get data from files Get data from relational data sources Create dynamic reports with parameters Get data from a NoSQL database Get data from online services Select a storage mode Get data from Azure Analysis Services Fix performance issues Resolve data import errors 4 - Clean, transform, and load data in Power BI Shape the initial data Simplify the data structure Evaluate and change column data types Combine multiple tables into a single table Profile data in Power BI Use Advanced Editor to modify M code 5 - Design a semantic model in Power BI Work with tables Create a date table Work with dimensions Define data granularity Work with relationships and cardinality Resolve modeling challenges 6 - Add measures to Power BI Desktop models Create simple measures Create compound measures Create quick measures Compare calculated columns with measures 7 - Add calculated tables and columns to Power BI Desktop models Create calculated columns Learn about row context Choose a technique to add a column 8 - Use DAX time intelligence functions in Power BI Desktop models Use DAX time intelligence functions Additional time intelligence calculations 9 - Optimize a model for performance in Power BI Review performance of measures, relationships, and visuals Use variables to improve performance and troubleshooting Reduce cardinality Optimize DirectQuery models with table level storage Create and manage aggregations 10 - Design Power BI reports Design the analytical report layout Design visually appealing reports Report objects Select report visuals Select report visuals to suit the report layout Format and configure visualizations Work with key performance indicators 11 - Configure Power BI report filters Apply filters to the report structure Apply filters with slicers Design reports with advanced filtering techniques Consumption-time filtering Select report filter techniques Case study - Configure report filters based on feedback 12 - Enhance Power BI report designs for the user experience Design reports to show details Design reports to highlight values Design reports that behave like apps Work with bookmarks Design reports for navigation Work with visual headers Design reports with built-in assistance Tune report performance Optimize reports for mobile use 13 - Perform analytics in Power BI Explore statistical summary Identify outliers with Power BI visuals Group and bin data for analysis Apply clustering techniques Conduct time series analysis Use the Analyze feature Create what-if parameters Use specialized visuals 14 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 15 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 16 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 17 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method Additional course details: Nexus Humans PL-300T00: Microsoft Power BI Data Analyst 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 PL-300T00: Microsoft Power BI Data Analyst 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 qualification is for tutors, trainers, or assessors, who are new into their role and looking for development of teaching, training and assessment skills. The qualification is made up of a range of units which can be adapted to any learning and development role, so, whether you are working with groups or individuals; delivering training in classrooms, in the workplace or online; planning training sessions or developing resources, units can be combined to suit your role and career objectives. This qualification is an expansion of the Level 3 Award in Education and Training qualification; it also contains the Assessor units for anyone looking to become a qualified assessor. Please see this link for the full qualification breakdown. This qualification is delivered though monthly workshops and mentoring visits from our Learning Advisor, who will support and advise you to develop your knowledge and skills in learning and development. You will also carry out self study and develop training sessions and materials. The course takes between 9-15 months to complete. You will be able to: Plan and deliver engaging and inclusive teaching and training sessions Adapt training and assessment to meet learners’ individual needs Facilitate learning one to one or in groups Have the option to complete the Assessor qualification as part of the course Use reflective practice to improve on your training and assessment skills Access funding for this qualification as part of an Apprenticeship programme *eligibility criteria apply Further Information To access the apprenticeship funding you must: Be new into role within the last 12 months (and be able to provide a contract with your start date in the role) Complete Essential Skills in Communication, Application of Number and Digital Literacy (or provide GCSE Certificates to be exempt). Workshops are provided. Live or work in Wales Be employed / self employed for a minimum of 16 hours per week Workshops include: • Course induction and Reflective Practice • The purpose and context of Learning and Development • Inclusive Practice: Universal Design for Learning • Session Planning • Teaching Methods and approaches • Micro-teach • The Principles and Practices of Assessment (optional) Partnerships This qualification is delivered in partnership with ALS training who provide funding from the Welsh Government Benefits Gain confidence in your teaching and training skills Gain an industry recognised qualification Learn from our experienced Learning Advisor and have bespoke support and guidance Discover practical tools and techniques you can apply in your training and assessment Develop your own professional network When? The next course start date is June 2024 Where? The workshops are held online. The mentoring visits can either be online or in person depending on location and preference Who? This course is for tutors, trainers or assessors who are new into role within the last 12 months Cost For anyone living or working win Wales, this can be fully funded as part of an Apprenticeship Programme. Please enquire at our office on 029 21679037 for eligibility criteria.
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