350 Data Visualization courses delivered Online

R Programming for Statistics and Data Science is the course that will take you from a complete beginner in programming with R to a professional who can complete data manipulation on demand. It gives you the complete skillset to tackle a new data science project with confidence and be able to critically assess your and others' work.

Unleash the power of data with our Data Analysis in Excel course, where you'll journey through the realm of spreadsheet analysis and uncover the secrets hidden within your data. In today's data-driven world, the ability to navigate, interpret, and extract insights from data is a coveted skill. Whether you're a professional looking to enhance your analytical capabilities or a student aiming to excel in data-driven fields, this course empowers you to harness Excel's full potential for data analysis. From modifying worksheets to forecasting future trends, you'll master the art of data manipulation, visualization, and analysis with confidence and precision. Learning Outcomes Master the art of modifying Excel worksheets to suit your data analysis needs. Discover advanced data analysis techniques, including working with lists and lookup functions. Create compelling data visualizations using charts, PivotTables, and PivotCharts. Effortlessly manage multiple worksheets and workbooks, making data organization a breeze. Apply data forecasting techniques and automate workbook functionality, saving time and boosting productivity. Why choose this Data Analysis in Excel course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Data Analysis in Excel course for? Professionals seeking to enhance their data analysis skills. Students preparing for careers in data-driven industries. Analysts, researchers, and data enthusiasts eager to upskill. Business professionals looking to make data-driven decisions. Anyone interested in harnessing Excel for powerful data analysis. Career path Data Analyst: £25,000 - £47,000 Business Analyst: £26,000 - £50,000 Financial Analyst: £26,000 - £56,000 Market Research Analyst: £24,000 - £40,000 Operations Analyst: £23,000 - £48,000 Business Intelligence Analyst: £27,000 - £56,000 Prerequisites This Data Analysis in Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Analysis in Excel was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Recommended Materials Workbook - Data Analysis in Excel 00:00:00 Assignment Assignment - Data Analysis in Excel 00:00:00

Embark on a captivating journey into the realm of IoT and ESP32 with our 'Beginners Course on ESP32 and IoT.' This course is your gateway to unraveling the secrets of ESP32, a versatile microcontroller, and delving into the exciting world of Internet of Things (IoT). Imagine yourself seamlessly navigating the course introduction, understanding ESP32 board intricacies, and mastering digital inputs and outputs. With hands-on tasks and real-world applications, this course transforms complex concepts into an engaging learning experience. Picture yourself confidently interfacing sensors, controlling devices over WiFi, and even creating your own IoT projects with Adafruit and Alexa integration. From the fundamentals of serial communication to the intricacies of MQTT protocol, this course is a comprehensive exploration of ESP32 and IoT. Each module is crafted to empower beginners with practical knowledge, making the learning process dynamic and enjoyable. Join us in this transformative journey, where the power of IoT and ESP32 becomes an exciting landscape waiting to be explored. Learning Outcomes Acquire a comprehensive understanding of ESP32, from board basics to practical applications. Master digital input and output interfaces, including serial communication, relay switching, and capacitive touch inputs. Explore sensor interfacing and network communication, enabling you to control devices over WiFi. Dive into the world of IoT, learning about protocols like MQTT and creating projects with Thingspeak, Adafruit, and Alexa integration. Develop practical skills to apply IoT concepts, from weather monitoring to creating your own Alexa-based IoT projects. Why choose this Beginners Course on ESP32 and IoT course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Beginners Course on ESP32 and IoT course for? Technology enthusiasts eager to explore IoT and ESP32 from scratch. Students and beginners with a keen interest in microcontrollers and Internet of Things. Hobbyists looking to enhance their skills in sensor interfacing and network communication. DIY enthusiasts aiming to create their own IoT projects with real-world applications. Anyone curious about the convergence of technology, connectivity, and IoT possibilities. Career path IoT Developer: £35,000 - £55,000 Embedded Systems Engineer: £40,000 - £60,000 Hardware Engineer: £30,000 - £50,000 Automation Engineer: £35,000 - £55,000 IoT Solutions Architect: £45,000 - £70,000 Technical Consultant (IoT): £40,000 - £65,000 Prerequisites This Beginners Course on ESP32 and IoT does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Beginners Course on ESP32 and IoT was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Introduction To ESP32 Course Introduction and Agenda 00:03:00 Getting Started with ESP32 inside Arduino 00:13:00 Getting to Know about ESP32 Board 00:11:00 Things Needed for This Course 00:02:00 Getting Started with ESP32 inside Arduino 00:13:00 Input / Output Interfaces With ESP32 Serial Communication Basics on ESP32 00:07:00 Serial Data Print using ESP32 00:12:00 Serial Data Read using ESP32 00:09:00 Digital Outputs with ESP32 00:12:00 Accepting Logic Inputs, Pull-up and Pull-down concepts 00:06:00 Read Digital Inputs on ESP32 00:13:00 Practice Tasks with Digital Input on ESP32 00:06:00 Switching Circuit - DC Load Switching 00:06:00 Relay Switching Circuit interfacing with ESP32 00:17:00 Relay Switching Circuit with ESP32 - 2 00:07:00 Reading Capacitive Touch Inputs on ESP32 00:10:00 Sensor And Network Interfacing DHT22 Sensor Interfacing with ESP32 00:17:00 ESP32 Wifi Based Device Control 00:14:00 ESP32 Weather Monitoring over Wifi (LAN) 00:07:00 ESP32 Weather Monitoring over Wifi (LAN) - Code Explained 00:07:00 Internet Of Things What is the Internet of things? 00:16:00 IoT Protocols and thingspeak 00:13:00 Sending Values to Thingspeak from ESP32 00:11:00 Data Visualizations in Thingspeak 00:05:00 Analytics in Thingspeak 00:16:00 What is MQTT Protocol? 00:10:00 Adafruit IoT Project - Part 1 00:11:00 Adafruit IoT Project - Part 2 00:09:00 Adafruit IoT Project - Part 3 00:08:00 Adafruit IoT Project - Part 4 00:06:00 Alexa Based Lamp Control 00:12:00 Conclusion Concluding Remarks 00:01:00

Data Analysis: Data Analysis Training Have you ever wondered how companies get insights from massive volumes of data to stay competitive and make wise decisions? If so, then participate in our exclusive Data Analysis: Data Analysis Course. This Data Analysis Course describes the fundamentals of data, statistics, and an introduction to Data Analysis. How to get data and where to find it is explained in the Data Analysis Course. Moreover, this Data Analysis Course covers data cleansing, preprocessing, and exploratory data analysis (EDA). Additionally, the Data Analysis Course provides an introduction to Python and Excel for Data Analysis. This thorough Data Analysis Course includes lessons on data wrangling with Pandas (python) and data visualisation using Matplotlib and Seaborn (python). Enrol in our Data Analysis Course to study the fundamentals of statistical analysis and machine learning. Main Course: Data Analysis (Data Analytics) Training Free Courses included with Data Analysis: Data Analysis Training Course: Course 01: Minute Taking Course 02: GDPR Course 03: Cyber Security [ Note: Free PDF certificate as soon as completing the Data Analysis: Data Analysis Training Course] Data Analysis: Data Analysis Training Online This Data Analysis (Data Analytics) Training consists of 12 modules. Curriculum of Data Analysis (Data Analytics) Training Course Module 1: Introduction to Data Analytics Module 2: Basics of Data and Statistics Module 3: Data Collection and Sources Module 4: Data Cleaning and Preprocessing Module 5: Exploratory Data Analysis (EDA) Module 6: Introduction to Excel for Data Analytics Module 7: Introduction to Python for Data Analytics Module 8: Data Wrangling with Pandas (Python) Module 9: Data visualisation with Matplotlib and Seaborn (Python) Module 10: Introduction to Basic Statistical Analysis Module 11: Introduction to Machine Learning Module 12: Capstone Project - Exploratory Data Analysis Assessment Method of Data Analysis (Data Analytics) Training Course After completing Data Analysis: Data Analysis Training Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Data Analysis (Data Analytics) Training Course After completing the Data Analysis: Data Analysis Training Course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Data Analysis: Data Analysis Training Online For business professionals, entrepreneurs, or anybody else looking to have a thorough grasp of data analysis in a commercial setting, this Data Analysis Course is ideal. Requirements Data Analysis: Data Analysis Training Online To enrol in this Data Analysis: Data Analysis Training Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Data Analysis Training Course. Be energetic and self-motivated to complete our Data Analysis Training Course. Basic computer Skill is required to complete our Data Analysis Training Course. If you want to enrol in our Data Analysis Training Course, you must be at least 15 years old. Career path Data Analysis: Data Analysis Training Online This Data Analysis Course will assist you in obtaining positions as a business analyst, marketing analyst, data analysis, and in related fields.

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.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2.5 Days 15 CPD hours This course is intended for This course is intended for those with a basic understanding of Tableau who want to pursue mastery of the advanced features. Overview The goal of this course is to present essential Tableau concepts and its advanced functionalities to help better prepare and analyze data. This course will use Tableau Hyper, Tableau Prep and more. Getting Up to Speed ? a Review of the Basics Connecting Tableau to your data Connecting to Tableau Server Connecting to saved data sources Measure Names and Measure Values Three essential Tableau concepts Exporting data to other devices Summary All About Data ? Getting Your Data Ready Data mining and knowledge discovery process models CRISP?DM All About Data ? Joins, Blends, and Data Structures All About Data - Joins, Blends, and Data Structures Introduction to joins Introduction to complex joins Exercise: observing join culling Introduction to join calculations Introduction to spatial joins Introduction to unions Understanding data blending Order of operations No dimensions from a secondary source Introduction to scaffolding Introduction to data structures Exercise: adjusting the data structure for different questions Summary Table Calculations Table Calculations A definition and two questions Introduction to functions Directional and non-directional table calculations Application of functions Summary Level of Detail Calculations Level of Detail Calculations Building playgrounds Playground I: FIXED and EXCLUDE Playground II: INCLUDE Practical application Exercise: practical FIXED Exercise: practical INCLUDE Exercise: practical EXCLUDE Summary Beyond the Basic Chart Types Beyond the Basic Chart Types Improving popular visualizations Custom background images Tableau extensions Summary Mapping Mapping Extending Tableau's mapping capabilities without leaving Tableau Extending Tableau mapping with other technology Exercise: connecting to a WMS server Exploring the TMS file Exploring Mapbox Accessing different maps with a dashboard Creating custom polygons Converting shape files for Tableau Exercise: polygons for Texas Heatmaps Summary Tableau for Presentations Tableau for Presentations Getting the best images out of Tableau From Tableau to PowerPoint Embedding Tableau in PowerPoint Animating Tableau Story points and dashboards for Presentations Summary Visualization Best Practices and Dashboard Design Visualization Best Practices and Dashboard Design Visualization design theory Formatting rules Color rules Visualization type rules Compromises Keeping visualizations simple Dashboard design Dashboard layout Sheet selection Summary Advanced Analytics Advanced Analytics Self-service Analytics Use case ? Self-service Analytics Use case ? Geo-spatial Analytics Summary Improving Performance Improving Performance Understanding the performance-recording dashboard Exercise: exploring performance recording in Tableau desktop Performance-recording dashboard events Behind the scenes of the performance- recording dashboard Hardware and on-the-fly techniques Hardware considerations On-the-fly-techniques Single Data Source > Joining > Blending Three ways Tableau connects to data Using referential integrity when joining Advantages of blending Efficiently working with data sources Tuning data sources Working efficiently with large data sources Intelligent extracts Understanding the Tableau data extract Constructing an extract for optimal performance Exercise: summary aggregates for improved performance Optimizing extracts Exercise: materialized calculations Using filters wisely Extract filter performance Data source filter performance Context filters Dimension and measure filters Table-calculation filters Efficient calculations Boolean/Numbers > Date > String Additional performance considerations Avoid overcrowding a dashboard Fixing dashboard sizing Setting expectations Summary Additional course details: Nexus Humans Advanced Tableau 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 Advanced Tableau 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