164 Courses in Leeds delivered Online

Microsoft Power BI Training Course Overview: The Microsoft Power BI Training course is designed to equip learners with the knowledge and skills to use Power BI effectively for data analysis and reporting. This course covers the core features of Power BI, from data import and transformation to the creation of reports and visualizations. Learners will explore how to analyse data, generate insights, and create dynamic dashboards for reporting purposes. Whether you are looking to improve your analytical skills or advance your career, this course provides the foundation needed to become proficient in using Power BI for various data analysis tasks. By the end of the course, learners will be able to handle large data sets, create compelling visual reports, and make data-driven decisions. Course Description: This comprehensive Microsoft Power BI course delves into the essential components of the Power BI platform. Learners will start by exploring how to import and work with data, before progressing to designing reports and visualizations. The course includes an in-depth look at the various types of visualizations available, enabling learners to display data in an intuitive, easy-to-understand format. Additionally, learners will explore the Power BI Web App to access and share their reports online. As they move through the course, participants will gain valuable skills in data transformation, reporting, and visualization, all of which are applicable to industries requiring data-driven decision-making. By completing this course, learners will have a solid understanding of Power BI and the ability to create impactful reports and dashboards for business or personal use. Microsoft Power BI Training Curriculum: Module 01: Getting Started Module 02: Working with Data Module 03: Working with Reports and Visualizations Module 04: A Closer Look at Visualizations Module 05: Introduction to the Power BI Web App (See full curriculum) Who is this course for? Individuals seeking to understand Power BI and data analysis. Professionals aiming to enhance their data reporting skills. Beginners with an interest in business intelligence and data analytics. Anyone looking to improve their ability to visualise data for better decision-making. Career Path: Data Analyst Business Intelligence Analyst Reporting Specialist Data Visualisation Specialist Business Analyst

Excel Data Analysis Course Overview The Excel Data Analysis course is designed to equip learners with the essential skills needed to analyse and interpret data using Microsoft Excel. This course covers a range of tools and techniques that are vital for processing, summarising, and visualising data. Learners will explore functions, pivot tables, charts, and data manipulation strategies that will enable them to work efficiently with data sets. By the end of the course, learners will be able to transform raw data into meaningful insights, making it an invaluable skill for professionals across various industries. Whether you're looking to improve your data skills or progress in your career, this course offers the foundational knowledge required for data analysis in Excel. Course Description This course delves into the core aspects of Excel Data Analysis, starting with basic functions and advancing to complex data manipulation techniques. Learners will explore how to create and manage pivot tables, perform data filtering, and apply functions such as VLOOKUP and INDEX MATCH. Visualisation tools like charts and graphs will be covered, enabling learners to present their findings in a clear and impactful way. Additionally, learners will be introduced to data modelling, conditional formatting, and advanced formula techniques that will enhance their data analysis capabilities. The course is structured to provide a comprehensive understanding of Excel’s data analysis features, building competency for a wide range of practical applications in both personal and professional settings. Excel Data Analysis Curriculum Module 01: Introduction to Excel for Data Analysis Module 02: Using Excel Functions for Data Manipulation Module 03: Working with Pivot Tables and Pivot Charts Module 04: Data Visualisation: Creating Charts and Graphs Module 05: Advanced Excel Functions for Complex Data Analysis Module 06: Data Filtering and Sorting Techniques Module 07: Conditional Formatting for Data Insights Module 08: Introduction to Data Modelling and Forecasting Module 09: Data Analysis Best Practices and Case Studies (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to advance in data-centric roles. Beginners with an interest in data analysis and Excel. Anyone looking to improve their Excel knowledge for career development. Career Path Data Analyst Business Analyst Financial Analyst Marketing Analyst Operations Manager Administrative Assistant Project Manager Research and Development Analyst

Microsoft Power BI Masterclass 2021 Course Overview: The "Microsoft Power BI Masterclass 2021" provides learners with the skills to become proficient in data analysis and visualization using Power BI. This comprehensive course covers the core functionalities of Power BI, from data preparation and transformation to creating impactful reports and dashboards. Learners will gain valuable insights into data modelling, visualisation, and the use of DAX for advanced calculations. By the end of the course, participants will be able to apply their knowledge to real-world projects, improving their ability to communicate data-driven insights effectively. This course is ideal for professionals and beginners who want to leverage Power BI to unlock the potential of their data. Course Description: This masterclass delves into the essential features of Microsoft Power BI, guiding learners through every stage of data analysis. Starting with project setup and data transformation in the Query Editor, the course progresses to advanced topics such as DAX functions and data storytelling. Learners will explore how to build data models, create dashboards, and employ Python in Power BI to enhance their reports. The course also covers Power BI Service for cloud-based analytics, row-level security for data protection, and integrating additional data sources. With a focus on empowering users to communicate insights clearly, the course ensures learners gain the expertise to manage data efficiently, make informed decisions, and stay up to date with evolving tools and features. Microsoft Power BI Masterclass 2021 Curriculum: Module 01: Introduction Module 02: Preparing our Project Module 03: Data Transformation - The Query Editor Module 04: Data Transformation - Advanced Module 05: Creating a Data Model Module 06: Data Visualization Module 07: Power BI & Python Module 08: Storytelling with Data Module 09: DAX - The Essentials Module 10: DAX - The CALCULATE function Module 11: Power BI Service - Power BI Cloud Module 12: Row-Level Security Module 13: More data sources Module 14: Next steps to improve & stay up to date (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to advance their data visualization expertise. Beginners with an interest in data science or business analytics. Business analysts or data professionals looking to upskill in Power BI. Career Path: Data Analyst Business Intelligence Analyst Data Scientist Power BI Developer Reporting Analyst Data Visualisation Expert

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

Level 7 QLS Endorsed Diploma | 180 CPD Points | +Gifts: QLS Certificate + PDF Certificate | 24/7 Learner Support

Level 7 QLS Endorsed Diploma | 180 CPD Points | +Gifts: QLS Certificate + PDF Certificate | 24/7 Learner Support

Course Overview This comprehensive course offers a deep dive into three essential technologies for data science: Python, JavaScript, and Microsoft SQL. Learners will gain foundational knowledge and practical skills in each of these key areas, which are crucial for handling data, creating interactive websites, and working with databases. By the end of the course, students will be proficient in writing Python code for data analysis, creating dynamic web content with JavaScript, and managing data with Microsoft SQL. The course is designed to equip learners with the technical skills needed to succeed in data science, making it a valuable investment for anyone looking to excel in this growing field. Course Description In this course, learners will explore the core principles of Python, JavaScript, and Microsoft SQL, all tailored to the needs of data science professionals. The curriculum covers Python’s data structures, functions, and libraries essential for data analysis, while JavaScript introduces students to web development skills, including client-side validation and data visualisation. The Microsoft SQL section focuses on data management, including filtering, joining, and structuring queries. Learners will develop a solid understanding of these technologies, which will enable them to manipulate data, automate processes, and design interactive applications. The course also includes real-world applications, ensuring learners are well-prepared for future opportunities in data science and web development. Course Modules: Module 01: JavaScript Getting Started Module 02: JavaScript Fundamentals Module 03: JavaScript Strings Module 04: JavaScript Operators Module 05: JavaScript Conditional Statements Module 06: JavaScript Control Flow Statements Module 07: JavaScript Functions Module 08: Data Visualization (Google Charts) Module 09: JavaScript Error Handling Module 10: JavaScript Client-Side Validations Module 11: Python Introduction Module 12: Python Basic Module 13: Python Strings Module 14: Python Operators Module 15: Python Data Structures Module 16: Python Conditional Statements Module 17: Python Control Flow Statements Module 18: Python Core Games Module 19: Python Functions Module 20: Python Args, KW Args for Data Science Module 21: Python Project Module 22: Publish Your Website for Live Module 23: MS SQL Statements Module 24: MS SQL Filtering Data Module 25: MS SQL Functions Module 26: MS SQL Joins Module 27: MS SQL Advanced Commands Module 28: MS SQL Structure and Keys Module 29: MS SQL Queries Module 30: MS SQL Structure Queries Module 31: MS SQL Constraints Module 32: MS SQL Backup and Restore (See full curriculum) Who is this course for? Individuals seeking to enhance their skills in data science. Professionals aiming to expand their knowledge in programming and database management. Beginners with an interest in Python, JavaScript, and SQL. Anyone looking to enter the field of data science or web development. Career Path Data Scientist Web Developer Database Administrator Data Analyst Front-End Developer Full Stack Developer Data Engineer

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.

JavaScript isn't just for fancy buttons and dropdown menus anymore. It's the backbone of modern web development and a powerful tool for crafting stunning, dynamic visual stories. This course takes you on a journey through JavaScript’s core features and then introduces you to the art of data visualisation—turning raw information into meaningful, interactive charts and graphics. Whether you're looking to sharpen your programming knowledge or want to make data a little less dull, this course keeps things sharp, smart, and structured. From plotting simple graphs to building responsive dashboards, you'll explore how JavaScript pairs beautifully with libraries like D3.js and Chart.js. Everything is broken down into digestible sections—no fluff, no filler, just the essentials taught with a touch of wit and clarity. You don’t need to be a coding wizard to join in, just a willingness to learn and a screen to learn it on. This is where data gets a makeover, and JavaScript shows off its creative side. 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: Introduction Getting Started Introduction to Getting Started Course Curriculum How to Get Pre-Requisites Getting Started on Windows, Linux or Mac How to ask a Great Questions FAQ's Setting up Local Development Environment What is JavaScript Choosing Code Editor Installing Code Editor(Sublime Text) Installing Code Editor(Visual Studio Code) Hello World Program Getting Output Summary JavaScript Fundamentals Introduction Internal JavaScript External JavaScript Inline JavaScript Async and defer Variables Data Types Numbers Boolean Arrays() Objects Comments Summary Strings Introduction Strings String Formatting String Methods Summary Operators Introduction Arithmetic operators Assignment operators Comparison operators Logical operators Summary Conditional Statements Introduction If statement If-else statement If-else-if statement Switch-case statement Summary Control Flow Statements Introduction While loop Do-while loop For loop Break Continue Coding Exercise Solution for Coding Exercise Summary Functions Introduction Creating a Function Function Call() Function with parameters Function Bind() Summary Data Visualization (Google Chart) Introduction How to Use Google chart script Line Graph chart Scatter plots chart Bar chart Pie chart 3D Pie chart Summary Error Handling Introduction Try-catch Try-catch-finally Summary Client-side Validations Introduction On Submit Validation Input Numeric Validation Login Form Validation Password Strength Check Validation Summary 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 Master JavaScript with Data Visualization 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 Master JavaScript with Data Visualization course is open to all, with no formal entry requirements. Career path Upon successful completion of the Master JavaScript with Data Visualization Course, learners will be equipped with many indispensable skills and have the opportunity to grab.