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It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Learning Objectives Learn the fundamental skills you require to be an expert Explore different techniques used by professionals Find out the relevant job skills & knowledge to excel in this profession Get a clear understanding of the job market and current demand Update your skills and fill any knowledge gap to compete in the relevant industry CPD accreditation for proof of acquired skills and knowledge Who is this Course for? Whether you are a beginner or an existing practitioner, our CPD accredited Flourish Studio Masterclass : Create Animated Visualisation is perfect for you to gain extensive knowledge about different aspects of the relevant industry to hone your skill further. It is also great for working professionals who have acquired practical experience but require theoretical knowledge with a credential to support their skill, as we offer CPD accredited certification to boost up your resume and promotion prospects. Entry Requirement Anyone interested in learning more about this subject should take this Flourish Studio Masterclass : Create Animated Visualisation. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path The Flourish Studio Masterclass : Create Animated Visualisation will help you to enhance your knowledge and skill in this sector. After accomplishing this course, you will enrich and improve yourself and brighten up your career in the relevant job market. Course Curriculum Introduction to Flourish Studio Welcome 00:04:00 Flourish Studio Background Story 00:01:00 Features of Flourish Studio 00:02:00 Flourish Studio Plans (Free, Business, Enterprise) 00:02:00 Getting Started with Flourish Signing up 00:02:00 Home Page Interface Walkthrough 00:06:00 Creating our First Flourish Visualisation 00:04:00 Adding and Managing Data in Flourish Templates Managing Data in Visualisations 00:08:00 Column Bindings 00:06:00 Merge Datasets 00:07:00 Creating Visualisations in Flourish Studio from scratch Creating a Bar or Line Chart in Flourish Studio - First Steps 00:08:00 Changing Settings to update Chart's look and feel - 1 00:21:00 Changing Settings to update Chart's look and feel - 2 00:10:00 Changing Settings to update Chart's look and feel - 3 00:12:00 More Visualisation Templates in Flourish Studio Table Charts (including mini visualisations) 00:09:00 Creating a Hierarchy Visualisation 00:05:00 Scatter Plot 00:06:00 More interesting variations of Scatter Plot 00:04:00 Map & Projection Charts + 3D Maps 00:08:00 Survey Charts 00:07:00 Gantt Chart 00:06:00 Radar Chart in Flourish Studio 00:06:00 Creating a Story and other Options How to create a Story in Flourish 00:13:00 Exporting, Publishing and Sharing 00:05:00 Flourish's Embed Options 00:06:00 How to Delete Projects 00:02:00 Other Exciting and Important Features Controlling access to Visualisations and stories with different Account Types 00:03:00 How to create a video or GIF from Flourish Visualisation/Story 00:04:00 How to generate the thumbnail of your visualisation 00:02:00 Customise colours in Flourish palettes 00:02:00 How to show published projects on your profile page 00:03:00 How to colour parts of your text with custom HTML 00:03:00 Add Social icons in Footer 00:02:00 Data Visualisation Tips & Resources How to select the right Visualisation Template 00:05:00 Dashboard Development Best Practices 00:04:00 Sources to get Datasets to use in Visualisations 00:02:00 Useful Resources to get Help & Continue Learning 00:06:00 Congratulations Congratulations on Course Completion 00:01:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00
Spreadsheet chaos? Sorted. This Microsoft Excel: 8 in 1 Premium Courses Bundle goes far beyond basic number crunching. You’ll explore not just Excel, but also the full Microsoft Office suite—Word, PowerPoint, Outlook, Access, Project—plus Power BI and SQL for those ready to flirt with data like it’s the office gossip. Whether you're spreadsheet shy or pivot table proud, this bundle keeps things tidy, stylish and fully functional. The content takes you through formulas, formatting, business reporting, data visualisation, and database management with clear, structured learning. No fluff, no filler—just focused skills that help you navigate office software with the confidence of someone who actually knows what they're doing. Upgrade your workflow one formula at a time. Learning Outcomes: Build and manage Excel spreadsheets with confidence and clarity. Create professional documents and reports using MS Word. Deliver sharp, engaging slides with MS PowerPoint tools. Handle email, tasks and calendars using MS Outlook efficiently. Analyse data using Power BI and basic SQL queries. Organise databases using Access and manage projects in MS Project. Who is this Course For: Professionals handling spreadsheets and reports on a regular basis. Office staff looking to improve Microsoft Office fluency. Admins managing communication, scheduling and document creation. Individuals working in finance, HR or operations roles. Data beginners who want to explore Power BI and SQL basics. Project coordinators managing deadlines and resource tracking. Job seekers looking to polish their office software knowledge. Anyone who thinks “VLOOKUP” sounds like tech wizardry. Career Path: Data Entry Clerk – £21,000 average salary Office Administrator – £24,500 average salary Business Analyst Assistant – £28,000 average salary Project Coordinator – £32,000 average salary Junior Data Analyst – £30,500 average salary Executive Assistant – £33,000 average salary
Learn how to create an automated trading bot using Python with this comprehensive course. Master Python basics, understand trading fundamentals, build and integrate the bot with a broker API, and run it effectively. Learning Outcomes: Gain proficiency in Python programming for trading purposes. Understand the fundamental concepts of trading and market dynamics. Build a structured trading bot using Python and Github version control. Integrate the bot with a broker API for real-time trading functionality. Successfully run and manage the automated trading bot for efficient execution. Why buy this Making Automated Trading Bot Using Python? 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 Making Automated Trading Bot Using Python 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 Making Automated Trading Bot Using Python 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 Making Automated Trading Bot Using Python does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Making Automated Trading Bot Using Python 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 Making Automated Trading Bot Using Python is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction About the course structure 00:05:00 Why working is important? 00:04:00 The free and perfect tools 00:07:00 Our editor: Atom 00:04:00 Version control: Github 00:07:00 Python download (Mac) 00:05:00 Python download (Windows) 00:02:00 Section 02: Python Basics for Trading Introduction 00:03:00 Python Libraries 00:05:00 Iterators: for 00:08:00 Iterators: while 00:08:00 Conditionals: if & else 00:10:00 Logic gates: and & or 00:09:00 Error handling: try & except 00:09:00 Functions and calls to libraries 00:13:00 Objects and classes (1) 00:10:00 Objects and classes (2) 00:07:00 Debugging the code 00:12:00 Closing and wrap up 00:01:00 Section 03: Trading Basics Introduction 00:03:00 Fundamental vs Technical Analysis 00:04:00 Stocks vs CFDs 00:05:00 Long and Short positions 00:04:00 Takeprofit and Stoploss 00:03:00 Setting a real Stoploss 00:08:00 Limit and Market orders 00:10:00 Don't forget the spread 00:04:00 Stock data visualisation: candles 00:08:00 Technical Indicators: about 00:05:00 Exponential Moving Average 00:08:00 EMA use and interpretation 00:06:00 Relative Strength Index 00:07:00 Stochastic Oscillator 00:09:00 Closing and wrap up 00:01:00 Section 04: Bot Code General Structure Introduction 00:02:00 Overview 00:08:00 The Entry Strategy 00:10:00 About Tradingview 00:12:00 When to enter (1) 00:08:00 When to enter (2) 00:08:00 Open and hold a position 00:12:00 Closing a position 00:08:00 Review (1) 00:06:00 Review (2) 00:13:00 Closing 00:02:00 Section 05: Github Basics Introduction 00:04:00 Download and install Github 00:01:00 Create a repo 00:10:00 Working with branches 00:13:00 Section 06: Building Your Bot Introduction 00:05:00 Create the first bot file 00:07:00 Building the bot scheme 00:08:00 Complete your code scheme (1) 00:11:00 Complete your code scheme (2) 00:11:00 Complete your code scheme (3) 00:18:00 A logger to remember (1) 00:14:00 A logger to remember (2) 00:14:00 Organising your code 00:07:00 Main function: run bot 00:23:00 Link the bot and the library 00:08:00 Traderlib control functions (1) 00:12:00 Traderlib control functions (2) 00:13:00 Check if tradable function 00:06:00 Set stoploss function 00:10:00 Set takeprofit function 00:04:00 Load historical data function 00:01:00 Get open positions function 00:04:00 Submit and cancel order functions 00:04:00 Check positions function 00:09:00 The Tulipy libraries 00:07:00 Importing all the libraries 00:03:00 First filter: get general trend 00:19:00 Second filter: get instant trend 00:14:00 Third filter: RSI 00:08:00 Fourth filter: Stochastic Oscillator 00:14:00 Enter position (1) 00:13:00 Enter position (2) 00:11:00 Enter position (3) 00:15:00 Enter position (4) 00:08:00 Last check before opening 00:13:00 Exit position and get out 00:10:00 Linking everything (1) 00:12:00 Linking everything (2) 00:12:00 Linking everything (3) 00:15:00 Fixing a mistake: going Short 00:05:00 Handling all your variables 00:18:00 Closing and wrap up 00:01:00 Run function scheme clarification and rebuild 00:13:00 Section 07: Integrating the Broker API Introduction 00:03:00 The Alpaca Python API Wrapper 00:07:00 Initialising the REST API 00:09:00 Running the program (crash!) 00:06:00 Integration with check account (1) 00:08:00 Integration with check account (2) 00:05:00 Clean open orders function 00:10:00 Importing the trading library 00:04:00 Running the main 00:05:00 Check position function 00:09:00 Check if asset exists function 00:08:00 Fetching barset data (theory) 00:07:00 Fetching barset data (practice) 00:12:00 Updating the code for the Alpaca API V2 (explanation) 00:03:00 Updating the code for the Alpaca API V2 (implementation) 00:08:00 Organizing data with Pandas 00:06:00 Get general trend function (1) 00:08:00 Reframing the timeframe with Pandas 00:23:00 Get general trend function (2) 00:13:00 Get instant trend function 00:08:00 Get RSI function 00:06:00 Get Stochastic function 00:10:00 Get current price function 00:05:00 Finishing get shares amount 00:09:00 Opening a position (1) 00:12:00 Opening a position (2) 00:09:00 Check the open position 00:07:00 Cancelling the order (1) 00:20:00 Cancelling the order (2) 00:08:00 Making sure we cancelled 00:03:00 Get average entry price function 00:10:00 Fixing bugs when getting price 00:18:00 Check Stochastic crossing 00:02:00 Holding an open position 00:11:00 Submitting the exit order 00:08:00 Closing position and out (1) 00:08:00 Closing position and out (2) 00:10:00 Closing and wrap up 00:01:00 Section 08: Running the Trading Bot Introduction 00:03:00 Filtering asset by price and volume 00:07:00 Get the bot ready to trade 00:04:00 Running the Trading Bot with AAPL 00:09:00 A real open position 00:08:00 Debugging and bug fixing 00:12:00 Fixing one (last) bug 00:02:00 Running the bot with TSLA 00:10:00 Discussing EMA implementations 00:12:00 Closing and wrap up 00:02:00
Confused by self assessment or VAT? Learn to handle tax returns, accounting, and reports online with this detailed training bundle. 🔹 Overview: The Self Assessment Tax Return Mini Bundle takes a focused look at the structure and reporting involved in personal tax declarations. You’ll study the principles behind tax returns, VAT rules, and how to organise everything through accounting and data visualisation software—without ever printing another spreadsheet. The courses in this bundle are built for individuals who want to make sense of numbers and deadlines, with added emphasis on financial analysis and digital reporting. From VAT calculation to Power BI charts that actually make sense, this bundle aims to turn tax confusion into organised clarity—one module at a time. 🔹 Learning Outcomes: Understand how to complete a self assessment tax return Analyse VAT data for personal and freelance tax planning Use Power BI to generate useful financial tax dashboards Apply accounting methods to individual tax records Gain financial insights through structured data interpretation Explore UK tax structure from income to VAT components 🔹 Who is this Course For: Individuals required to submit a self assessment each year Freelancers dealing with VAT and income tax submissions New accountants interested in personal tax reporting Business owners learning about tax return obligations Students studying tax reporting, VAT and analytics Budget-conscious individuals aiming to reduce tax errors Data-savvy users learning Power BI for tax analysis People managing their finances independently with structure 🔹 Career Path: VAT Analyst – £28,000–£36,000 per year Self Assessment Support Advisor – £24,000–£32,000 per year Finance Officer (Tax Focus) – £30,000–£40,000 per year Tax and VAT Assistant – £25,000–£34,000 per year BI Reporting Analyst (Finance) – £32,000–£45,000 per year Accounting Associate – £23,000–£30,000 per year
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Acquire essential skills to efficiently navigate and manipulate data in Microsoft Excel, such as organising, sorting, filtering, and writing formulas. Gain proficiency in creating professional presentations in Microsoft PowerPoint, utilising features like multimedia, transitions, animations, and smart graphics. Master the art of document creation and formatting in Microsoft Word, including tables, styles, page layouts, envelopes, labels, and mail merges. Understand advanced features like pivot tables, charts, and data analysis tools in Microsoft Excel, enabling effective data visualisation and decision-making. This course covers everything you must know to stand against the tough competition. The future is truly yours to seize with this Mastering Microsoft Office: Word, Excel, PowerPoint, and 365. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-to-one support from a dedicated tutor throughout your course. Study online - whenever and wherever you want. Instant Digital/ PDF certificate 100% money back guarantee 12 months access This course covers everything you must know to stand against the tough competition. The future is truly yours to seize with this Mastering Microsoft Office: Word, Excel, PowerPoint, and 365. Enrol today and complete the course to achieve a certificate that can change your career forever. Process of Evaluation After studying the course, your skills and knowledge will be tested with an MCQ exam or assignment. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement After completing the Mastering Microsoft Office: Word, Excel, PowerPoint, and 365 course, you will receive your CPD-accredited Digital/PDF Certificate for £5.99. To get the hardcopy certificate for £12.99, you must also pay the shipping charge of just £3.99 (UK) and £10.99 (International). Who Is This Course for? This course is designed for individuals who want to enhance their Microsoft Office skills for personal or skilled purposes. Whether you are a student, an experienced entrepreneur, or anyone who regularly works with Microsoft Word, Excel, PowerPoint, and Office 365, this Microsoft Office skills course will provide you with a solid foundation and advanced techniques to maximise your productivity and efficiency. No prior experience is required, making it suitable for beginners and intermediate users looking to expand their knowledge and capabilities in the Microsoft Office suite. On the other hand, anyone who wants to establish their career as: like MS Office User Microsoft Office 2019 User Touch Typing Worker Audio Typist Can take this Ultimate Microsoft Office Skills Training (Word, Excel, PowerPoint, and 365) course. Requirements There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Mastering Microsoft Office: Word, Excel, PowerPoint, and 365 course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career path Administrative Assistant - £20K to £30K/year Data Analyst - £25K to £45K/year Office Manager - £25K to £40K/year Project Coordinator - £25K to £35K/year Marketing Assistant - £20K to £30K/year Course Curriculum Section 01: Getting Started Introduction 00:03:00 Getting started on Windows, macOS, and Linux 00:01:00 How to ask great questions 00:01:00 FAQ's 00:01:00 Section 02: Excel 2021: Basics Excel Overview 00:05:00 Start Excel Spreadsheet 00:04:00 Enter Text and Numbers 00:07:00 Relative References 00:04:00 Working with ranges 00:07:00 Save and Save as Actions 00:08:00 File Extensions, Share, Export, and Publish files 00:06:00 Section 03: Excel 2021: Rows, Columns, and Cells Adding Rows and Columns 00:03:00 Modifying Rows and Column lengths 00:05:00 Section 04: Excel 2021: Data Handling Copy, Cut, and Paste 00:07:00 Copying Formulas 00:03:00 Section 05: Excel 2021: Page Setting Up and Print Page setup options 00:06:00 Fit to print on One Page 00:03:00 Print Workbooks 00:03:00 Section 06: Excel 2021: Sorting and Filtering Sorting Data Ascending Order 00:04:00 Sorting Data Descending Order 00:02:00 Filter Data 00:04:00 Section 07: Excel 2021: Writing Formulas Creating Basic Formulas 00:06:00 Datetime Formulas 00:06:00 Mathematical formulas phase1 00:20:00 Mathematical formulas phase2 00:12:00 Section 08: Excel 2021: Advanced Formulas VLOOKUP formula 00:12:00 HLOOKUP formula 00:04:00 Section 09: Excel 2021: XLOOKUP only for 2021 and Office 365 XLOOKUP 00:08:00 Handling #NA and Approximates match in XLOOKUP 00:11:00 Section 10: Excel 2021: Data and Tools Split Text into columns 00:07:00 Flash Fill 00:07:00 Data Validation 00:07:00 Remove Duplicates 00:08:00 Import Data from Text files 00:06:00 Import Data from .CSV files 00:03:00 Section 11: Excel 2021: Formatting data and tables Formatting Font 00:04:00 Formatting Alignment 00:06:00 Formatting Numbers 00:05:00 Formatting Date 00:03:00 Formatting Tables 00:05:00 Section 12: Excel 2021: Pivot Tables Pivot Tables 00:07:00 Pivot Charts 00:02:00 Section 13: Excel 2021: Charts Excel Charts - Categories 00:03:00 Elements of a chart 00:04:00 Creating Charts 00:02:00 Column or Bar charts 00:04:00 Formatting charts 00:04:00 Line Charts 00:02:00 Pie and Doughnut charts 00:04:00 Section 14: PowerPoint 2021: Course Introduction Overview 00:04:00 Start PowerPoint Presentation 00:05:00 Screen setting and Views 00:05:00 Section 15: PowerPoint 2021: Basics Presentation Tips and Guidelines 00:06:00 Creating a New Presentation 00:04:00 Working with Slides 00:04:00 Save a Presentation 00:04:00 Print Slides 00:03:00 Section 16: PowerPoint 2021: Text and Bullet Options Formatting Text 00:05:00 Slide Text Alignments 00:03:00 Multi-Column Text Alignments 00:02:00 Adding Bullets and Numbered List Items 00:03:00 Section 17: PowerPoint 2021: Adding Graphic Assets Insert Shapes 00:03:00 Insert Icons 00:03:00 Insert Graphics 00:04:00 Add 3D Models 00:03:00 Insert Pictures 00:03:00 Section 18: PowerPoint 2021: Picture Formatting Picture Options 00:04:00 Picture Cropping 00:03:00 Applying Built-in Picture Styles 00:04:00 Section 19: PowerPoint 2021: SmartArt Graphics Add SmartArt Graphic 00:03:00 Modifying SmartArt 00:03:00 Creating a Target Chart using SmartArt 00:03:00 Section 20: PowerPoint 2021: Working with Tables Create a Table on Slide 00:04:00 Formatting Tables 00:02:00 Inserting Tables 00:02:00 Table Layouts 00:01:00 Section 21: PowerPoint 2021: Working with Charts Add a Chart 00:02:00 Formatting Charts 00:02:00 Insert Chart from Microsoft Excel 00:03:00 Section 22: PowerPoint 2021: Adding Multimedia Adding Video to a Presentation 00:03:00 Adding Audio to a Presentation 00:02:00 Screen Recording and Adding 00:02:00 Section 23: PowerPoint 2021: Working with Transition Applying Transitions to Presentation 00:04:00 Section 24: PowerPoint 2021: Animation Object Animation 00:03:00 Effect Options 00:02:00 Advanced Animation 00:02:00 Triggers to control animation 00:02:00 Section 25: PowerPoint 2021: Slideshow Effects Onscreen Presentation 00:02:00 Hiding Slides 00:02:00 Changing Order of Slides 00:02:00 Copying Slides 00:02:00 Section 26: Word 2021: Introduction Overview of MS Word 00:04:00 Start MS Word 2021 00:05:00 Section 27: Word 2021: Basics Create a new blank document 00:04:00 Creating a paragraph text 00:05:00 Non-printing characters 00:03:00 Save a document 00:03:00 Open a document 00:01:00 Find and replace 00:04:00 Section 28: Word 2021: Word Formatting AutoCorrect options 00:03:00 Formatting text 00:04:00 Copy cut and paste 00:04:00 Character formatting 00:02:00 Format painter 00:04:00 Work with numbers 00:02:00 Add bullets 00:03:00 Outline creation 00:04:00 Section 29: Word 2021: Tables Creating a table 00:03:00 Adding rows and columns to a table 00:02:00 Formatting table data 00:02:00 Borders and shading 00:02:00 Sorting in a table 00:04:00 Draw a table 00:04:00 Convert text to table 00:03:00 Convert table to text 00:02:00 Insert a spreadsheet 00:02:00 Quick tables - readily available formats 00:02:00 Section 30: Word 2021: Styles Working with styles 00:02:00 Creating styles 00:02:00 Clear formatting 00:01:00 Section 31: Word 2021: Page Layout Margins 00:02:00 Orientation 00:01:00 Page size setting 00:01:00 Adding columns 00:03:00 Page break - section break 00:02:00 Adding watermark 00:03:00 Headers and footers 00:03:00 Section 32: Word 2021: Envelops and Lables Create envelops 00:02:00 Creating labels 00:02:00 Section 33: Word 2021: Mail Merges Creating a mail merge document 00:03:00 Section 34: Word 2021: Review and Printing Thesaurus and spell check 00:01:00 Word count 00:01:00 Speech - read aloud 00:01:00 Language - translate 00:01:00 Tracking 00:01:00
Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights. Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum 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 Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00
Today’s customer doesn’t just buy — they decide, they compare, they vanish, and sometimes return. Understanding why that happens isn’t guesswork; it’s analytics. This Customer Analytics Training Course offers a focused and strategic route into the heart of customer behaviour, turning complex data into easy decisions. You’ll learn how patterns emerge from clicks, purchases, and preferences — all while brushing up on the skills that companies value when making smarter business moves. The course demystifies customer data without blinding you with science. Expect to explore customer segmentation, predictive modelling, data visualisation, churn analysis, and behavioural insights — all explained with clarity and a touch of dry wit. Whether you're managing customer relations, handling data reports, or just want to know what makes customers tick (and when they stop ticking), this course is your route to sharper thinking and sharper results. It’s digital, flexible, and structured with a clear purpose: to turn numbers into narrative and strategy into sense. Learning Outcomes: Understand the basics of customer analytics and customer life cycle Develop effective customer onboarding and activation strategies Use cross-selling techniques to increase customer retention Measure the effectiveness of marketing campaigns using campaign analytics Use customer analytics to drive marketing strategies and improve customer experience Our Customer Analytics Training course is designed to help you gain a deeper understanding of customer analytics and develop effective marketing strategies. With 6 comprehensive modules, you will learn how to develop effective customer onboarding and activation strategies, use cross-selling techniques to increase customer retention, measure the effectiveness of marketing campaigns, and use customer analytics to improve the customer experience. This course is perfect for anyone looking to enhance their understanding of customer analytics and take their marketing campaigns to the next level. Whether you are a business owner, marketer, or digital strategist, this course will help you master the skills you need to make informed marketing decisions and drive results. Customer Analytics Training Course Curriculum Section 01: Basics Of Customer Analytics And Customer Life Cycle Section 02: Customer Onboarding Section 03: Customer Activation Section 04: Cross Selling Section 05: Campaign Life Cycle Section 06: Conclusion How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Business owners who want to understand their customers' behavior better Marketers who want to optimise their marketing campaigns Digital strategists who want to gain a deeper understanding of customer analytics Students who want to explore the field of customer analytics Professionals who want to enhance their data analysis skills Career path Customer Analyst: £20,000 - £40,000 Digital Marketing Specialist: £25,000 - £50,000 Marketing Manager: £30,000 - £60,000 Senior Digital Strategist: £40,000 - £80,000 Head of Marketing: £60,000 - £120,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.
If data is the new oil, then coding is your refinery. Whether you're exploring the depths of machine learning or navigating databases with ease, this course sharpens your edge in the competitive world of data science. With a sharp focus on three industry-leading languages—Python, JavaScript, and Microsoft SQL—you’ll build the solid foundations needed to analyse, automate, and query data confidently. From writing clean scripts to crafting smart SQL queries, you’ll develop the mindset to speak fluently in the language of data. Delivered entirely online, the course keeps your learning agile and accessible. Python lays the groundwork for analysis and automation, JavaScript helps in data visualisation and interaction, and SQL ensures you can command databases without blinking. It's not about ticking boxes—it’s about building fluency in what matters. Whether you're upskilling or aiming for a sharper digital edge, this course speaks directly to future-focused learners ready to code with purpose. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Course Curriculum: JavaScript Section 01: Introduction Section 02: Basics Section 03: Operators Section 04: Conditional Statements Section 05: Control Flow Statements Section 06: Functions Section 07: Error Handling Section 08: Client-Side Validations Python Section 09: Introduction Section 10: Basic Section 11: Strings Section 12: Operators Section 13: Data Structures Section 14: Conditional Statements Section 15: control flow statements Section 16: core games Section 17: functions Section 18: args, KW args for Data Science Section 19: project Section 20: Object oriented programming [OOPs] Section 21: Methods Section 22: Class and Objects Section 23: Inheritance and Polymorphism Section 24: Encapsulation and Abstraction Section 25: OOPs Games Section 26: Modules and Packages Section 27: Error Handling Microsoft SQL Section 28: Introduction Section 29: Statements Section 30: Filtering Data Section 31: Functions Section 32: Joins Section 33: Advanced commands Section 34: Structure and Keys Section 35: Queries Section 36: Structure queries Section 37: Constraints Section 38: Backup and Restore Course Assessment To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%. When all tests have been successfully passed, you will be able to order a certificate endorsed by the Quality Licence Scheme. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). Who is this course for? This Learn Python, JavaScript, and Microsoft SQL for Data science course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Learn Python, JavaScript, and Microsoft SQL for Data science course is open to all, with no formal entry requirements. Career path Upon successful completion of the Learn Python, JavaScript, and Microsoft SQL for Data science Course, learners will be equipped with many indispensable skills and have the opportunity to grab.