3518 Dash courses

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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Data Done Right - The Value of Good Communication Wouldn't it be great if you could see important textual and graphical information quickly and easily? What if it could be updated automatically or by using a simple refresh? What if you could easily change that information as needed, or see it right now with tools you already have, on multiple devices? In this presentation we will show you all of those things. You'll see reports that are produced in MS Project and MS Excel, graphical reports in Visio, and a dashboard that uses all of these tools. And we'll top it off with a discussion about what information to present and not present. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Data Done Right - The Value of Good Communication Wouldn't it be great if you could see important textual and graphical information quickly and easily? What if it could be updated automatically or by using a simple refresh? What if you could easily change that information as needed, or see it right now with tools you already have, on multiple devices? In this presentation we will show you all of those things. You'll see reports that are produced in MS Project and MS Excel, graphical reports in Visio, and a dashboard that uses all of these tools. And we'll top it off with a discussion about what information to present and not present. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Duration 1 Days 6 CPD hours This course is intended for This course is aimed at users with the Tableau CRM license who need to build effective lenses and dashboards for their business users to explore their data. It may also be of interest to users who are connecting and integrating this data, to understand how it is used in the lens and dashboard building process. Overview Build and manage apps in Tableau CRM Design a dashboard based on requirements, and create a dashboard template Create and add lenses to build a dashboard Optimize a dashboard for mobile use Ready to start building in Tableau CRM? In this course, you?ll find out how to design and create an effective dashboard layout to help viewers quickly find their way around. You?ll learn how to build lenses and add them into your dashboards using the Tableau CRM Dashboard Designer. Once you?ve created a dashboard, you?ll also learn how to optimize the dashboard for mobile. Finally you?ll also learn how to organize your lenses and dashboards using apps and ensure that only the right users have access to them.Looking for Tableau classes? Check out the Tableau catalog here. Managing Apps, Lenses, Dashboards, and Datasets Overview of building and managing apps Building an app Manage apps, lenses, dashboards, and datasets Designing a Dashboard and Creating a Template Dashboard Building Overview Designing a Dashboard Create a dashboard template Building a Dashboard Building a Dashboard Adding Charts, Tables, and KPIs to a Dashboard Adding Filters to a Dashboard Modify a Dashboard for Mobile Translating Desktop Dashboards to a Mobile Device Creating/Updating Mobile Dashboard Layouts

About Course Building Web Applications with Django and PostgreSQL: Master the Complete Stack Learn to build modern and robust web applications with one of the most popular and powerful tech stacks: Django and PostgreSQL. In this comprehensive course, you will learn: The fundamentals of Django, including setting up a development environment, creating models, views, and templates, and handling user authentication and authorization. How to work with Django's built-in admin interface and form files. Advanced topics, such as working with Django's ORM (Object-Relational Mapping) to interact with the PostgreSQL database, handling form submissions, and integrating third-party libraries. Best practices for structuring Django projects, handling user sessions, and securing your web applications against common web vulnerabilities. You will also gain hands-on experience in using PostgreSQL as your database backend, including: Designing database schemas Performing CRUD (Create, Read, Update, Delete) operations Optimizing database performance Throughout the course, you will work on practical projects that will allow you to apply the concepts you've learned and build real-world web applications. By the end of this course, you will be able to: Create dynamic and interactive web applications with Django and PostgreSQL. Build secure, scalable, and maintainable web applications. Become a skilled and proficient web developer. This course is perfect for: Beginners who want to learn how to build web applications from scratch. Experienced web developers who want to learn how to use Django and PostgreSQL. Anyone who wants to learn how to build modern and robust web applications. Enroll today and start your journey to becoming a Django and PostgreSQL expert! Bonus: Get access to the instructor's personal collection of Django and PostgreSQL resources. Why learn Django and PostgreSQL? Django and PostgreSQL are two of the most popular and powerful technologies for building web applications. Django is a popular web framework written in Python that allows developers to build robust and scalable web applications quickly and efficiently. PostgreSQL is a powerful open-source relational database management system known for its reliability and performance. Learning Django and PostgreSQL will give you a significant advantage in the job market and allow you to build more complex and sophisticated web applications. Here are some of the benefits of learning Django and PostgreSQL: Django is a popular web framework with a large and active community. This means that there is a wealth of resources available to help you learn Django and get help when you need it. Django is a powerful and versatile web framework that can be used to build a wide variety of web applications, from simple websites to complex e-commerce platforms. PostgreSQL is a powerful and reliable database management system that is known for its performance and scalability. PostgreSQL is also an open-source database, which means that it is free to use and distribute. So what are you waiting for? Enroll in this course today and start your journey to becoming a Django and PostgreSQL expert! What Will You Learn? Comprehensive coverage of Django web framework and PostgreSQL database Practical projects to apply concepts learned Hands-on experience with PostgreSQL as a database backend Best practices for structuring Django projects and securing web applications In-depth understanding of Django's ORM for database interactions Integration of third-party libraries and Import Real-world examples and use cases Course Content Getting Started Introduction Getting started on Windows, MacOS, and Linux How to Ask Great Questions FAQs Setting Up a Python Development Installing Python Installing PyCharm IDE for Development Creating the first Python Project Write and Run Hello World Program Command Line Basics Installation and Access Pip Command Django Setting Up the Project Introduction to Web Framework and Django Installing Django and Setting Up a Project Understanding Django Architecture and Structured Creating a Simple Django App Building a Django App with PostgreSQL Introduction to PostgreSQL and its Advantages for Web Applications Installing PostgreSQL and Setting Up a Database pgAdmin Secure Login and Create Database Connection Django to PostgreSQL Creating a Basic HTTP View Method Request URL Pattern on App Include Apps to Project URLs Installing the Psycopg2 Module for DB Connection Django Models and ORM (Object Relational Mapping) Defining Models and Creating Database Tables Using Djangos Built-in ORM to Interact with the Database Migration to Create DB Tables Assessment Test Solution for an Assessment Test Working with Admin Module Creating Superuser as Admin Authentication and Authorization User Access Permissions Registering User Models to the Admin Dashboard Creating Data Using CRUD Functionality View Data on the PostgreSQL Database Table Django Views and Templates Understanding the MVC - MVT Creating Views and Handling HTTP Requests and Rendering Templates Creating a Template with HTML Page Building Dynamic Form and Handling Django Form Design Creating Bootstrap Template Applying Bootstrap to Django Form Creating Stunning Product Card items Django Project: Registration form - Real world Creating Model Creating Forms Creating Views Applying ORM - Migrations Creating My Form Template Adding URLs Creating Success_View Template Project URLs Update and Adding Installed Apps Run Project and Submit Data to Database Django Reports Creating Report_View Method Creating Report_Template Update URLs Pattern Run Project and Test Reports Course Resources Course Resources A course by Sekhar Metla IT Industry Expert Material Includes Download Resources and Reference Project Source Code Django to PostgreSQL database connection Project Settings file RequirementsBasic knowledge of Python programmingUnderstanding of relational databases and SQL - optionalFamiliarity with web development concepts (HTML, CSS, and JavaScript) - optional Audience Beginners Python Django developers curious about web application development Web developers who want to learn how to build web applications using Django and PostgreSQL Python developers who want to expand their skillset to web development Students or professionals looking to enhance their web development skills with Django and PostgreSQL. Requirements Basic knowledge of Python programming Understanding of relational databases and SQL - optional Familiarity with web development concepts (HTML, CSS, and JavaScript) - optional

Duration 1 Days 6 CPD hours This course is intended for Anyone whose role requires them to use existing Power BI Reports or Dashboards to consume the contents. Roles can include management at all levels, team leaders or anyone who needs to commission the production of reports or dashboards. It is assumed that attendees on the course are familiar with charts. Please note that this course is not suitable for new Excel users, delegates need Ability to create charts Ability to use filters in data Overview This course covers the use of Power BI Desktop and the Power BI service hosted in Office 365 to identify core features, terminology and processes applicable when using reports or dashboards.Delegates will learn how to: Power BI Concepts and Main Features How a report is created Navigating reports and dashboards How to apply filters and slicers To use Insights, Analytics and Natural Language Queries Power BI provides a variety of methods for using reports and dashboards within which data can be viewed and analyzed visually. Getting Started with Power BI Power BI Concepts and Versions Introduction to Main Features: Jargon buster From Data to Reports and Dashboards Visualizations Overview Visualizations Available Visualizations as Filter Reports and Dashboards Similarities and differences Understanding what you are looking at Understanding what you are looking at Using a Report in Power BI Filters, sorting and using slicers See the actual data See Data and See Records Drill visualizations Off the shelf data analysis Quick Conditional Formatting Analytics lines Use Insight for Increases and Decrease Forecast Analytics Changing calculations and Show As Working with Dashboards Dashboards in Power BI Defined How is a dashboard different from a report? Working in the Dashboard window

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, and Business Process Owners/Team Leads/Power Users. In this course, students are enabled to transform Excel workbooks into captivating dashboards for executives and business users. Introduction to Dashboards Creating Interactive Dashboards Using an Embedded Excel Workbook in the Dashboard Data Visualizations with Charts Using Data in a Range Using Data in a Series Preparing Future Data by Ignoring End Blanks Dashboard Distribution Distributing a Dashboard Single Value Components Using Single Value Components Alerts Setting Up Alerts Selectors Using Selectors Setting Default Values for Selectors Selecting Multiple Items Common Components Using Images in a Dashboard Using Tables in a Dashboard Using an Interactive Calendar in a Dashboard Adding a URL to a Dashboard Components Used as Selectors Using the Chart Component as a Selector Using the Map Component as a Selector Format Options Configuring Proportional Size and Position Using Themes to Apply Formats Using Templates to Apply Formats Applying Globalization Dynamic Visability Adding Dynamic Visibility Using Formulas to Create Dynamic Visibility Creating Multi-Layer Dashboards Dashboard Design Optimization Optimizing Dashboard Design Dashboard Connection to Live Data Using Live Data Sources Setting Up an XML Connection Using Web Services to Connect to Data Using the Query Browser to Connect to Data Using the Portal Data Connection to Connect to Data Additional course details: Nexus Humans BOX310 SAP BusinessObjects Dashboards 4.1 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 BOX310 SAP BusinessObjects Dashboards 4.1 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.

Power BI is a powerful data visualisation program that allows businesses to monitor data, analyse trends, and make decisions. This course is designed to provide a solid understanding of the reporting side of Power BI, the dashboards, where administrators, and end users can interact with dynamic visuals that communicates information. This course focuses entirely on the creation and design of visualisations in dashboards, including a range of chart types, engaging maps, and different types of tables. Designing dashboards with KPI's (key performance indicators), heatmaps, flowcharts, sparklines, and compare multiple variables with trendlines. This one-day programme focuses entirely on creating dashboards, by using the many visualisation tools available in Power BI. You will learn to build dynamic, user-friendly interfaces in both Power BI Desktop and Power BI Service. 1 Introduction Power BI ecosystem Things to keep in mind Selecting dashboard colours Importing visuals into Power BI Data sources for your analysis Joining tables in Power BI 2 Working with data Utilising a report theme Table visuals Matrix visuals Drilling into hierarchies Applying static filters Group numbers with lists Group numbers with bins 3 Creating visuals Heatmaps in Power BI Visualising time-intelligence trends Ranking categorical totals Comparing proportions View trends with sparklines 4 Comparing variables Insert key performance indicators (KPI) Visualising trendlines as KPI Forecasting with trendlines Visualising flows with Sankey diagrams Creating a scatter plot 5 Mapping options Map visuals Using a filled map Mapping with latitude and longitude Mapping with ArcGIS or ESRI 6 Creating dashboards High-level dashboard Migration analysis dashboard Adding slicers for filtering Promote interaction with nudge prompts Searching the dashboard with a slicer Creating dynamic labels Highlighting key points on the dashboard Customised visualisation tooltips Syncing slicers across pages 7 Sharing dashboards Setting up and formatting phone views Exporting data Creating PDF files Uploading to the cloud Share dashboards in SharePoint online

Teachers will become familiar with the software, aiding each learner access to their college dashboard as a designer, so they can complete a heat loss report and other heating design elements. Furthermore each learner will have access to send surveys from the heat engineer app (Apple or Android) which once sent will be received within the college dashboard. Where teachers can assess the survey.