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362 Data Visualization courses

Power BI: Dashboard in a Day

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for The Power BI in a Day course is designed for beginners and intermediate users of Power BI. Overview #NAME? Students will discover the full capabilities of Power BI in a one-day, hands-on workshop. Please Note: This workshop is primarily self-directed and students will work at their own pace while having access to an instructor for questions. 1 - Accessing & Preparing data Data Set Power BI Desktop Power BI Desktop ? Accessing Data Power BI Desktop ? Data Preparation 2 - Data Modeling and Exploration Power BI Desktop ? Data Modeling and Exploration Power BI Desktop ? Data Exploration Continued References 3 - Data Visualization Power BI Desktop Power BI Desktop ? Data Visualization References 4 - Publishing & Accessing Reports Power BI Desktop ? Creating Mobile View Power BI Service Power BI Service ? Publishing Report Power BI Mobile ? Accessing Report on Mobile Device Power BI Service ? Collaboration and Distribution References 5 - Dashboard and Collaboration Power BI Service Building Dashboard References Additional course details: Nexus Humans Power BI: Dashboard in a Day 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 Power BI: Dashboard in a Day 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: Dashboard in a Day
Delivered Online
£595

An Introduction to Real Estate (12 Hours Online Self-Study)

4.3(5)

By Bayfield Training

Are you looking to enter the dynamic world of real estate? Our course is designed to equip you with the knowledge and tools you need to communicate effectively with real estate professionals and develop key skills in real estate investment strategy and analytics. At the end of the course, you'll be able to read and interpret real estate market reports, and have a firm grasp of how iconic buildings, cities, and companies fit into the overall picture of the real estate sector. On this course, you will… Become familiar with the players, structure, general terminology and overall needs of Real Estate. Learn what is Real Estate and why it is different from other asset classes Get to grips with the overall size and structure of the UK Real Estate Market Learn and analyse the links between the different parts of the property market Understand who works in the Real Estate Market, their qualifications and their job descriptions Recognise how and when to use basic real estate concepts: Rent, Value, Yield, Risk and Return, etc… Learn how to read a real estate market report Understand how current affairs, politics and economics affects Real Estate Investment Use household names and iconic companies, cities and buildings to help consolidate your appreciation of this exciting sector Who will benefit from this course: Graduates or undergraduates studying economics, finance. Professionals working in Marketing or Accounting teams within Real Estate firms. APC students. Anyone interested in Real Estate. School leavers/A-Level Students looking to gain an understanding of Real Estate. Non cognate students who wish to transfer into Real Estate/Finance careers. Course Outline Module 1: What is and why buy Real Estate? The property Market The Size and Structure of the UK property market The impact of Real Estate in the Economy Module 2: The Real Estate Market System The Space Market The Asset Market The Development Market Module 3: How to value Real Estate An Introduction to Financial Mathematics The difference between Price, Value and Worth Property Yield Conventional Valuation Methods Module 4: How to read a Real Estate Market Report Property Market Indicators: Stock Indicators Property Market Indicators: Investment Indicators Module 5: Who works in Real Estate? The build Environment by Cobalt Recruitment Rea; Estate Agents Examples of Real Estate Market Agents CVs Real Estate Network

An Introduction to Real Estate (12 Hours Online Self-Study)
Delivered in person or Online + more
£1,500

Master JavaScript with Data Visualization

5.0(10)

By Apex Learning

Overview This comprehensive course on Master JavaScript with Data Visualization will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Master JavaScript with Data Visualization comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Master JavaScript with Data Visualization. It is available to all students, of all academic backgrounds. Requirements Our Master JavaScript with Data Visualization is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 11 sections • 76 lectures • 06:21:00 total length •Introduction to Getting Started: 00:02:00 •Course Curriculum: 00:05:00 •How to Get Pre-Requisites: 00:02:00 •Getting Started on Windows, Linux or Mac: 00:01:00 •How to ask a Great Questions: 00:02:00 •FAQ's: 00:01:00 •What is JavaScript: 00:09:00 •Choosing Code Editor: 00:03:00 •Installing Code Editor (Sublime Text): 00:04:00 •Installing Code Editor(Visual Studio Code): 00:07:00 •Hello World Program: 00:14:00 •Getting Output: 00:11:00 •Summary: 00:02:00 •Introduction: 00:02:00 •Internal JavaScript: 00:13:00 •External JavaScript: 00:09:00 •Inline JavaScript: 00:04:00 •Async and defer: 00:06:00 •Variables: 00:13:00 •Data Types: 00:10:00 •Numbers: 00:06:00 •Boolean: 00:04:00 •Arrays(): 00:12:00 •Objects: 00:06:00 •Comments: 00:05:00 •Summary: 00:01:00 •Introduction: 00:02:00 •Strings: 00:06:00 •String Formatting: 00:05:00 •String Methods: 00:12:00 •Summary: 00:02:00 •Introduction: 00:02:00 •Arithmetic operators: 00:07:00 •Assignment operators: 00:03:00 •Comparison operators: 00:06:00 •Logical operators: 00:08:00 •Summary: 00:02:00 •Introduction: 00:02:00 •If statement: 00:04:00 •If-else statement: 00:05:00 •If-else-if statement: 00:04:00 •Switch-case statement: 00:09:00 •Summary: 00:01:00 •Introduction: 00:02:00 •While loop: 00:09:00 •Do-while loop: 00:03:00 •For loop: 00:08:00 •Break: 00:02:00 •Continue: 00:03:00 •Coding Exercise: 00:02:00 •Solution for Coding Exercise: 00:02:00 •Summary: 00:02:00 •Introduction: 00:02:00 •Creating a Function: 00:07:00 •Function Call(): 00:07:00 •Function with parameters: 00:05:00 •Function Bind(): 00:06:00 •Summary: 00:01:00 •Introduction: 00:01:00 •How to Use Google chart script: 00:04:00 •Line Graph chart: 00:14:00 •Scatter plots chart: 00:02:00 •Bar chart: 00:04:00 •Pie chart: 00:02:00 •3D Pie chart: 00:02:00 •Summary: 00:01:00 •Introduction: 00:01:00 •Try-catch: 00:05:00 •Try-catch-finally: 00:17:00 •Summary: 00:01:00 •Introduction: 00:01:00 •On Submit Validation: 00:09:00 •Input Numeric Validation: 00:12:00 •Login Form Validation: 00:05:00 •Password Strength Check Validation: 00:04:00 •Summary: 00:01:00

Master JavaScript with Data Visualization
Delivered Online On Demand6 hours 21 minutes
£12

How to Process Time Series Data with JavaScript

By Packt

In this course, learn how to process data to pull out relevant information, structure the data for visualizing using JavaScript's map and filter methods, use D3.js's scale functions, and more. Basic HTML and CSS skills, some JavaScript programming, and a basic understanding of D3js are required.

How to Process Time Series Data with JavaScript
Delivered Online On Demand1 hour 18 minutes
£37.99

Spatial Data Visualization and Machine Learning in Python Level 4

5.0(10)

By Apex Learning

Overview This comprehensive course on Spatial Data Visualization and Machine Learning in Python Level 4 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Spatial Data Visualization and Machine Learning in Python Level 4 comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Spatial Data Visualization and Machine Learning in Python Level 4. It is available to all students, of all academic backgrounds. Requirements Our Spatial Data Visualization and Machine Learning in Python Level 4 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 8 sections • 21 lectures • 04:40:00 total length •Introduction: 00:14:00 •Python Installation: 00:03:00 •Installing Bokeh: 00:04:00 •Data Preparation: 00:24:00 •Creating a Bar Chart: 00:18:00 •Creating a Line Chart: 00:12:00 •Creating a Doughnut Chart: 00:22:00 •Creating a Magnitude Plot: 00:31:00 •Creating a Geo Map Plot: 00:20:00 •Creating a Grid Plot: 00:12:00 •Data Pre-processing: 00:21:00 •Building a Predictive Model: 00:21:00 •Building a Prediction Dataset: 00:07:00 •Adding predicted data to our plots - Part 1: 00:13:00 •Adding predicted data to our plots - Part 2: 00:14:00 •Adding predicted data to our plots - Part 3: 00:15:00 •Adding the Grid Plot: 00:08:00 •Installing Visual Studio Code: 00:01:00 •Creating the Project and Virtual Environment: 00:08:00 •Building and Running the Server: 00:12:00 •Resources: 00:00:00

Spatial Data Visualization and Machine Learning in Python Level 4
Delivered Online On Demand4 hours 40 minutes
£12

Visual Data With Tableau Course

4.6(12)

By PCWorkshops

This course in Visual Data With Tableau covers the Fundamentals of Tableau Desktop. Tableau is brilliant software, very intuitive, for this purpose of data visualization. It is powerful in transforming data to reflect the insights that you plan to visualise

Visual Data With Tableau Course
Delivered Online & In-PersonFlexible Dates
FREE

Data Visualization and Reporting with Power BI

5.0(10)

By Apex Learning

Overview This comprehensive course on Data Visualization and Reporting with Power BI will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Visualization and Reporting with Power BI comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Visualization and Reporting with Power BI. It is available to all students, of all academic backgrounds. Requirements Our Data Visualization and Reporting with Power BI is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 15 sections • 140 lectures • 14:25:00 total length •Welcome!: 00:01:00 •What is Power BI?: 00:03:00 •Download & Installing Power BI Desktop: 00:04:00 •Getting to know the interface: 00:03:00 •Mini Project: Transform Data: 00:07:00 •Mini Project: Visualize Data: 00:05:00 •Mini Project: Creating a Data Model: 00:07:00 •Course Outline: What will you learn in this course?: 00:05:00 •How to learn best with this course?: 00:03:00 •Creating our initial project file: 00:04:00 •Working with the attached project files: 00:04:00 •Exploring the Query Editor: 00:06:00 •Connecting to our data source: 00:07:00 •Editing rows: 00:08:00 •Changing data types: 00:08:00 •Replacing values: 00:03:00 •Close & Apply: 00:03:00 •Connecting to a csv file: 00:03:00 •Connecting to a web page: 00:05:00 •Extracting characters: 00:06:00 •Splitting & merging columns: 00:09:00 •Creating conditional columns: 00:06:00 •Creating columns from examples: 00:09:00 •Merging Queries: 00:17:00 •Pivoting & Unpivoting: 00:06:00 •Appending Queries: 00:08:00 •Practice & Solution: Population table: 00:15:00 •The Fact-Dimension-Model: 00:09:00 •Practice: Load the dimension table: 00:04:00 •Organizing our queries in groups: 00:03:00 •Entering data manually: 00:05:00 •Creating an index column: 00:03:00 •Workflow & more transformations: 00:05:00 •Module summary: 00:05:00 •Exercise 1 - Instruction: 00:02:00 •Exercise 1 - Exercise Solution: 00:11:00 •Advanced Editor - Best practices: 00:09:00 •Performance: References vs. Duplicating: 00:10:00 •Performance: Enable / Disable Load & Report Refresh: 00:05:00 •Group by: 00:05:00 •Mathematical Operations: 00:05:00 •Run R Script: 00:15:00 •Using Parameters to dynamically transform data: 00:06:00 •M formula language: Basics: 00:07:00 •M formula language: Values, Lists & Tables: 00:14:00 •M formula language: Functions: 00:13:00 •M formula language: More functions & steps: 00:05:00 •Exercise 2 - Instructions: 00:01:00 •Exercise 2 - solution: 00:05:00 •Understanding the relationship: 00:05:00 •Create & edit relationships: 00:06:00 •One-to-many & one-to-one relationship: 00:06:00 •Many-to-many (m:n) relationship: 00:08:00 •Cross filter direction: 00:06:00 •Activate & deactivate relationships: 00:06:00 •Model summary: 00:03:00 •Exercise 3 Create Model: 00:02:00 •Exercise 3 Solution: 00:02:00 •Our first visual: 00:08:00 •The format tab: 00:12:00 •Understanding tables: 00:10:00 •Conditional formatting: 00:09:00 •The Pie Chart: 00:06:00 •All about the filter visual: 00:13:00 •The filter pane for developers: 00:09:00 •Cross filtering & edit interactions: 00:04:00 •Syncing slicers across pages: 00:07:00 •Creating drill downs: 00:08:00 •Creating drill throughs: 00:07:00 •The tree map visual: 00:07:00 •The decomposition tree: 00:05:00 •Understanding the matrix visual: 00:05:00 •Editing pages: 00:07:00 •Buttons & Actions: 00:09:00 •Bookmarks to customize your report: 00:10:00 •Analytics and Forecasts with line charts: 00:10:00 •Working with custom visuals: 00:07:00 •Get data using R Script & R Script visual: 00:08:00 •Asking questions - Q&A visual: 00:04:00 •Wrap up - data visualization: 00:08:00 •Python in Power BI - Plan of attack: 00:03:00 •Setting up Python for Power BI: 00:03:00 •Transforming data using Python: 00:11:00 •Creating visualizations using Python: 00:08:00 •Violin plots, pair plots & ridge plots using Python: 00:15:00 •Machine learning (BayesTextAnalyzer) using Python: 00:00:00 •Performance & Troubleshooting: 00:03:00 •Introduction: 00:01:00 •Show Empathy & Identify the Requirement: 00:03:00 •Finding the Most Suitable KPI's: 00:02:00 •Choose an Effective Visualization: 00:04:00 •Make Use of Natural Reading Pattern: 00:03:00 •Tell a Story Using Visual Cues: 00:05:00 •Avoid Chaos & Group Information: 00:02:00 •Warp Up - Storytelling with Data: 00:02:00 •Introduction: 00:03:00 •The project data: 00:04:00 •Measures vs. Calculated Columns: 00:15:00 •Automatically creating a date table in DAX: 00:08:00 •CALENDAR: 00:05:00 •Creating a complete date table with features: 00:04:00 •Creating key measure table: 00:03:00 •Aggregation functions: 00:06:00 •The different versions of COUNT: 00:14:00 •SUMX - Row based calculations: 00:09:00 •CALCULATE - The basics: 00:11:00 •Changing the context with FILTER: 00:07:00 •ALL: 00:08:00 •ALL SELECTED: 00:03:00 •ALL EXCEPT: 00:07:00 •How to go on now?: 00:03:00 •Power BI Pro vs Premium & Signing up: 00:04:00 •Exploring the interface: 00:04:00 •Discovering your workspace: 00:03:00 •Connecting Power BI Desktop & Cloud: 00:04:00 •Understanding datasets & reports: 00:03:00 •Working on reports: 00:04:00 •Updating reports from Power BI Desktop: 00:04:00 •Creating and working with workspaces: 00:07:00 •Installing & using a data gateway: 00:13:00 •Get Quick Insights: 00:03:00 •Creating dashboards: 00:04:00 •Sharing our results through Apps: 00:10:00 •Power BI Mobile App: 00:05:00 •Creating the layout for the Mobile App: 00:04:00 •Wrap up - Power BI Cloud: 00:07:00 •Introduction: 00:03:00 •Creating a Row-Level Security: 00:05:00 •Row-Level Security in the Cloud: 00:04:00 •Row-Level Security & Data Model: 00:05:00 •Dynamic Row-Level Security: 00:07:00 •Dynamic Many-to-Many RLS: 00:04:00 •Hierarchical Row-Level Security: 00:13:00 •JSON & REST API: 00:10:00 •Setting up a local MySQL database: 00:14:00 •Connecting to a MySQL database in Power BI: 00:05:00 •Connecting to a SQL database (PostgreSQL): 00:05:00 •Congratulations & next steps: 00:06:00 •The End: 00:01:00 •Resources - Data Visualization and Reporting with Power BI: 00:00:00

Data Visualization and Reporting with Power BI
Delivered Online On Demand14 hours 25 minutes
£12

Tableau for Data-Driven Decision Makers

By Nexus Human

Duration 1 Days 6 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who receive Tableau data visualizations from data analysts or from data visualization engineers. These data report recipients want to take advantage of the many Tableau features and capabilities that enable them to explore the data behind the initial analysis, perform additional analysis to ask next-level questions of the data, and to customize visualizations and dashboards to share new insights and create compelling reports. Overview Explore Tableau reports. Analyze data to get answers and insights. Sort and group data for analysis and reporting. Filter views. Prepare reports. Troubleshoot, collaborate, and share views and analysis As data acquisition, access, analysis, and reporting are interwoven with our businesses and lives, more and more data is collected about business and personal activities. This abundance of data and the computing power to analyze it has increased the use of data analysis and data visualization across a broad range of job roles. Decision makers of all types, including managers and executives, must interact with, interpret, and develop reports based on data and analysis provided to them. Tableau© software is designed for data analysis and the creation of visualizations. Data analysts prepare data, perform initial analysis, and create visualizations that are then passed on to business data-driven decision makers. These decision makers can use Tableau's tools to explore the data, perform further analysis to find new insights, make decisions, and create customized reports to share their findings. Prerequisites To ensure your success in this course, you should have experience managing data with Microsoft© Excel© or Google Sheets? Lesson 1: Exploring Tableau Reports Topic A: Data Analysis Workflow with Tableau Topic B: Explore Views Topic C: Edit Workbooks Lesson 2: Analyzing Data to Get Answers and Insights Topic A: Configure Marks with the Marks Card Topic B: Ask New Questions by Changing Aggregation Topic C: Find Answers with Calculations Topic D: Answer Questions with Table Calculations Lesson 3: Sorting and Grouping Data for Analysis and Reporting Topic A: Sort Data Topic B: Group Data Lesson 4: Filtering Views Topic A: Filter Data to Refine Analysis Topic B: Create Interactive Filters for Reports Lesson 5: Preparing Reports Topic A: Format and Annotate Views to Tell Your Story Topic B: Emphasize Data in Reports Topic C: Animate Visualizations for Clarity Lesson 6: Troubleshooting, Sharing, and Collaborating Topic A: Troubleshoot Data Issues Topic B: Collaborate in Tableau Online Topic C: Collaborate with Non-Tableau Users

Tableau for Data-Driven Decision Makers
Delivered OnlineFlexible Dates
£695

Spatial Data Visualization and Machine Learning in Python

4.7(160)

By Janets

Register on the Spatial Data Visualization and Machine Learning in Python today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Spatial Data Visualization and Machine Learning in Python is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Spatial Data Visualization and Machine Learning in Python Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Spatial Data Visualization and Machine Learning in Python, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Section 01: Introduction Introduction 00:14:00 Section 02: Setup and Installations Python Installation 00:03:00 Installing Bokeh 00:04:00 Section 03: Data Preparation Data Preparation 00:24:00 Section 04: Data Visualization Creating a Bar Chart 00:18:00 Creating a Line Chart 00:12:00 Creating a Doughnut Chart 00:22:00 Creating a Magnitude Plot 00:31:00 Creating a Geo Map Plot 00:20:00 Section 05: Machine Learning Data Pre-processing 00:21:00 Building a Predictive Model 00:21:00 Building a Prediction Dataset 00:07:00 Section 06: Building the Dashboard Adding predicted data to our plots - Part 1 00:13:00 Adding predicted data to our plots - Part 2 00:14:00 Adding predicted data to our plots - Part 3 00:15:00 Adding the Grid Plot 00:08:00 Section 07: Creating the Dashboard Server Installing Visual Studio Code 00:01:00 Creating the Project and Virtual Environment 00:08:00 Building and Running the Server 00:12:00 Section 08: Project Source Code Project Source Code 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.

Spatial Data Visualization and Machine Learning in Python
Delivered Online On Demand4 hours 28 minutes
£25

SQL for Data Science, Data Analytics and Data Visualization

4.5(3)

By Studyhub UK

This comprehensive course, 'SQL for Data Science, Data Analytics, and Data Visualization,' covers essential SQL concepts and tools for working with data. Participants will learn to manipulate, analyze, and visualize data using SQL Server, Azure Data Studio, and other relevant tools. The course also delves into advanced SQL commands, stored procedures, and data import/export, making it ideal for aspiring data professionals. Learning Outcomes: Set up and configure SQL Server and SQL Azure Data Studio for data analysis. Master SQL statements for data manipulation, data structure, and user management. Utilize SQL queries, joins, and aggregate functions for efficient data analysis. Understand SQL constraints, views, and advanced commands for in-depth data exploration. Create and implement SQL stored procedures to automate tasks. Leverage Azure Data Studio for data visualization and perform data analysis with SQL. Why buy this SQL for Data Science, Data Analytics and Data Visualization? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the SQL for Data Science, Data Analytics and Data Visualization there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This SQL for Data Science, Data Analytics and Data Visualization course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This SQL for Data Science, Data Analytics and Data Visualization does not require you to have any prior qualifications or experience. You can just enrol and start learning.This SQL for Data Science, Data Analytics and Data Visualization 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This SQL for Data Science, Data Analytics and Data Visualization is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Getting Started Introduction 00:03:00 How to get course requirements 00:03:00 Getting started on Windows, Linux or Docker 00:01:00 How to ask great questions 00:01:00 FAQ's 00:01:00 Section 02: SQL Server setting up Section Introduction 00:02:00 Microsoft SQL Server Installation 00:19:00 SQL Server Management Studio (SSMS) Installation 00:08:00 How to connect MS SQL (Windows Authentication) 00:04:00 How to connect MS SQL (SQL Server Authentication) 00:03:00 Download and Restore Sample Database 00:07:00 Section 03: SQL Azure Data Studio What is Azure Data Studio 00:06:00 Azure Data Studio Installation steps 00:07:00 Azure Data Studio to Connect SQL Server 00:09:00 Create a Database 00:07:00 Create a Table 00:09:00 Insert Data rows 00:07:00 View the Data returned by Query 00:03:00 Section 04: SQL Database basic SSMS Section Introduction 00:01:00 Overview of Databases8 00:11:00 Creating Database 00:05:00 SQL Data Types 00:03:00 Column Data Types on SSMS 00:04:00 Creating Table 00:09:00 Overview of Primary Key and Foreign Key 00:04:00 Primary Key 00:04:00 Foreign Key 00:07:00 Creating Temporary tables 00:06:00 Section 05: SQL Statements for DATA Section Introduction 00:01:00 Insert statement 00:08:00 Update statement 00:05:00 Delete statement 00:03:00 Section 06: SQL Data Structure statements Section Introduction 00:01:00 CREATE table statement 00:03:00 DROP statement 00:02:00 ALTER statement 00:05:00 TRUNCATE statement 00:04:00 COMMENT in query 00:01:00 RENAME 00:02:00 Section 07: SQL User Management Create Database user 00:04:00 GRANT permissions 00:06:00 REVOKE permissions 00:04:00 Section 08: SQL Statement Basic Section Introduction 00:01:00 SQL Statement basic 00:03:00 SELECT Statement 00:07:00 SELECT DISTINCT 00:03:00 SELECT with column headings 00:03:00 Column AS statement 00:02:00 Section 09: Filtering Data rows SELECT WHERE Clause - theory 00:04:00 SELECT WHERE Clause - practical 00:07:00 Section 10: Aggregate functions Sum() 00:08:00 Min()-Max() 00:06:00 Section 11: SQL Query statements Order By statement 00:05:00 SELECT TOP clause in SQL 00:04:00 BETWEEN command 00:08:00 IN operator 00:04:00 Wildcard Characters and LIKE 00:05:00 Section 12: SQL Group by statement Section Introduction 00:01:00 Group by - theory8 00:03:00 Group by - practical 00:05:00 HAVING statement 00:04:00 Section 13: JOINS for Multiple table Data Analysis Overview of Joins 00:02:00 What are Joins 00:02:00 Inner join 00:08:00 Left outer join 00:03:00 Right outer join 00:02:00 Full outer join 00:01:00 Union 00:03:00 Cartesian Product with the Cross Join 00:03:00 Query Exercise 00:01:00 Solution for Query Exercise 00:01:00 Section 14: SQL Constraints Section introduction 00:01:00 Check constraint 00:07:00 NOT NULL constraint 00:08:00 UNIQUE constraint 00:05:00 Section 15: Views Creating Views 00:04:00 Reporting with multiple tables 00:03:00 Section 16: Advanced SQL commands Section Introduction 00:01:00 Timestamp 00:04:00 Extract from timestamp 00:03:00 Mathematical scalar functions 00:04:00 String functions 00:05:00 Sub Query 00:03:00 SELECT with calculations 00:06:00 Section 17: SQL Stored procedures Create stored procedure 00:05:00 Stored procedure with parameter 00:04:00 Section 18: Azure Data Studio Visualization Installing SandDance Extension 00:03:00 Visualization Charts 00:05:00 Multiple Table Data Charts 00:06:00 Section 19: Azure Studio SQL for Data Analysis Type Decision for Data Analysis 00:13:00 Data Analysis with Case Statement and String Text 00:09:00 Section 20: Import & Export data Section Introduction 00:01:00 Import Flat File 00:05:00 Import .csv or excel file 00:03:00 Export Data to Excel or any format 00:06:00 Section 21: Backup and Restore Database Section Introduction 00:01:00 Creating Database backup 00:04:00 Restoring Database backup 00:04:00

SQL for Data Science, Data Analytics and Data Visualization
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