4102 Software courses in Edinburgh delivered On Demand

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Welcome to a brand-new course, where you can learn how to create modern and beautiful web projects and templates; if you want to develop and customize your portfolio, become an experienced developer, then this is the right course for you. Level-up your HTML, CSS, and JavaScript coding skills with this course.

Are you looking to enhance your Game Development skills? If yes, then you have come to the right place. Our comprehensive course on Game Development will assist you in producing the best possible outcome by mastering the Game Development skills. The Game Development course is for those who want to be successful. In the Game Development course, you will learn the essential knowledge needed to become well versed in Game Development. Our Game Development course starts with the basics of Game Development and gradually progresses towards advanced topics. Therefore, each lesson of this Game Development course is intuitive and easy to understand. Why would you choose the Game Development course from Compliance Central: Lifetime access to Game Development course materials Full tutor support is available from Monday to Friday with the Game Development course Learn Game Development skills at your own pace from the comfort of your home Gain a complete understanding of Game Development course Accessible, informative Game Development learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Game Development Study Game Development in your own time through your computer, tablet or mobile device. A 100% learning satisfaction guarantee with your Game Development Course Game Development Curriculum Breakdown of the Game Development Course Section 01: Introduction Section 02: Basic Building Blocks Section 03: Putting Blocks Together Section 04: Winning Managers Section 05: Creating Basic Game Section 06: Advanced Scratching And Winning Options Section 07: Finishing The Game Section 08: Creating Custom Animation System Section 09: Creating Game Animations Section 10: Building Your Game Section 11: Initial Scratching CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Game Development course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Game Development. It is also great for professionals who are already working in Game Development and want to get promoted at work. Requirements To enrol in this Game Development course, all you need is a basic understanding of the English Language and an internet connection. Career path The Game Development course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Game Development. Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

The Statistical Analysis Training Course is pivotal in the modern world, offering essential skills that are increasingly demanded across various industries. As businesses and organizations generate vast amounts of data, the ability to analyze and interpret this data becomes crucial. Learning from The Statistical Analysis Training Course equips individuals with expertise in key areas such as probability, hypothesis testing, regression analysis, and predictive analytics, enhancing their employability. In the UK, proficiency gained from this Statistical Analysis Training course can significantly boost job opportunities, with data analysts and statisticians earning an average salary of £35,000 to £50,000 annually. The demand for statistical analysis skills is on the rise, with the sector experiencing a growth rate of 33% over the past five years. Advantages of the Statistical Analysis Training course include a comprehensive understanding of both foundational and advanced statistical concepts, which are integral in roles across finance, healthcare, marketing, and technology. The Statistical Analysis Training Course ensures that learners are well-versed in modern analytical techniques, making them valuable assets in a data-driven economy. As the importance of data analytics continues to grow, so does the value of this training, making it an indispensable tool for career advancement. Key Features: CPD Certified Statistical Analysis Course Free Certificate from Reed CIQ Approved Statistical Analysis Course Developed by Specialist Lifetime Access Course Curriculum: Statistical Analysis Training Module 01: The Realm of Statistics Module 02: Basic Statistical Terms Module 03: The Center of the Data Module 04: Data Variability Module 05: Binomial and Normal Distributions Module 06: Introduction to Probability Module 07: Estimates and Intervals Module 08: Hypothesis Testing Module 09: Regression Analysis Module 10: Algorithms, Analytics and Predictions Module 11: Learning From Experience: The Bayesian Way Module 12: Doing Statistics: The Wrong Way Module 13: How We Can Do Statistics Better Learning Outcomes: Grasp fundamental statistical concepts for data analysis proficiency. Understand measures of central tendency and dispersion in datasets. Apply probability theory to make informed statistical decisions. Utilize hypothesis testing techniques to draw meaningful conclusions. Master regression analysis for predictive modelling and trend identification. Embrace Bayesian methods and enhance statistical inference capabilities. CPD 10 CPD hours / points Accredited by CPD Quality Standards Statistical Analysis Training 4:44:42 1: Module 01: The Realm of Statistics Preview 15:23 2: Module 02: Basic Statistical Terms 27:51 3: Module 03: The Center of the Data 10:00 4: Module 04: Data Variability 21:00 5: Module 05: Binomial and Normal Distributions 21:00 6: Module 06: Introduction to Probability 23:42 7: Module 07: Estimates and Intervals 21:35 8: Module 08: Hypothesis Testing 21:51 9: Module 09: Regression Analysis 21:00 10: Module 10: Algorithms, Analytics and Predictions 31:05 11: Module 11: Learning From Experience: The Bayesian Way 20:08 12: Module 12: Doing Statistics: The Wrong Way 23:39 13: Module 13: How We Can Do Statistics Better 25:28 14: CPD Certificate - Free 01:00 Who is this course for? This Statistical Analysis Training course is accessible to anyone eager to learn more about this topic. Through this course, you'll gain a solid understanding of Statistical Analysis Training. Moreover, this course is ideal for: Aspiring data analysts seeking statistical foundations for career advancement. Professionals in research roles aiming to refine statistical analysis skills. Students pursuing degrees in mathematics, economics, or related disciplines. Business professionals looking to leverage data-driven insights for strategic decisions. Anyone interested in enhancing statistical literacy and analytical reasoning abilities. Requirements There are no requirements needed to enrol into this Statistical Analysis Training course. We welcome individuals from all backgrounds and levels of experience to enrol into this Statistical Analysis Training course. Career path After finishing this Statistical Analysis Training course you will have multiple job opportunities waiting for you. Some of the following Job sectors of Statistical Analysis Training are: Data Analyst - £30K to £45K/year. Statistician - £35K to £50K/year. Market Research Analyst - £25K to £40K/year. Business Intelligence Analyst - £35K to £55K/year. Healthcare Data Analyst - £30K to £50K/year. Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Overview This comprehensive course on R Programming for Data Science will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This R Programming for Data Science 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 R Programming for Data Science. It is available to all students, of all academic backgrounds. Requirements Our R Programming for Data Science 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 23 sections • 129 lectures • 06:25:00 total length •Introduction to Data Science: 00:01:00 •Data Science: Career of the Future: 00:04:00 •What is Data Science?: 00:02:00 •Data Science as a Process: 00:02:00 •Data Science Toolbox: 00:03:00 •Data Science Process Explained: 00:05:00 •What's Next?: 00:01:00 •Engine and coding environment: 00:03:00 •Installing R and RStudio: 00:04:00 •RStudio: A quick tour: 00:04:00 •Arithmetic with R: 00:03:00 •Variable assignment: 00:04:00 •Basic data types in R: 00:03:00 •Creating a vector: 00:05:00 •Naming a vector: 00:04:00 •Vector selection: 00:06:00 •Selection by comparison: 00:04:00 •What's a Matrix?: 00:02:00 •Analyzing Matrices: 00:03:00 •Naming a Matrix: 00:05:00 •Adding columns and rows to a matrix: 00:06:00 •Selection of matrix elements: 00:03:00 •Arithmetic with matrices: 00:07:00 •Additional Materials: 00:00:00 •What's a Factor?: 00:02:00 •Categorical Variables and Factor Levels: 00:04:00 •Summarizing a Factor: 00:01:00 •Ordered Factors: 00:05:00 •What's a Data Frame?: 00:03:00 •Creating Data Frames: 00:20:00 •Selection of Data Frame elements: 00:03:00 •Conditional selection: 00:03:00 •Sorting a Data Frame: 00:03:00 •Additional Materials: 00:00:00 •Why would you need lists?: 00:01:00 •Creating a List: 00:06:00 •Selecting elements from a list: 00:03:00 •Adding more data to the list: 00:02:00 •Additional Materials: 00:00:00 •Equality: 00:03:00 •Greater and Less Than: 00:03:00 •Compare Vectors: 00:03:00 •Compare Matrices: 00:02:00 •Additional Materials: 00:00:00 •AND, OR, NOT Operators: 00:04:00 •Logical operators with vectors and matrices: 00:04:00 •Reverse the result: (!): 00:01:00 •Relational and Logical Operators together: 00:06:00 •Additional Materials: 00:00:00 •The IF statement: 00:04:00 •IFELSE: 00:03:00 •The ELSEIF statement: 00:05:00 •Full Exercise: 00:03:00 •Additional Materials: 00:00:00 •Write a While loop: 00:04:00 •Looping with more conditions: 00:04:00 •Break: stop the While Loop: 00:04:00 •What's a For loop?: 00:02:00 •Loop over a vector: 00:02:00 •Loop over a list: 00:03:00 •Loop over a matrix: 00:04:00 •For loop with conditionals: 00:01:00 •Using Next and Break with For loop: 00:03:00 •Additional Materials: 00:00:00 •What is a Function?: 00:02:00 •Arguments matching: 00:03:00 •Required and Optional Arguments: 00:03:00 •Nested functions: 00:02:00 •Writing own functions: 00:03:00 •Functions with no arguments: 00:02:00 •Defining default arguments in functions: 00:04:00 •Function scoping: 00:02:00 •Control flow in functions: 00:03:00 •Additional Materials: 00:00:00 •Installing R Packages: 00:01:00 •Loading R Packages: 00:04:00 •Different ways to load a package: 00:02:00 •Additional Materials: 00:00:00 •What is lapply and when is used?: 00:04:00 •Use lapply with user-defined functions: 00:03:00 •lapply and anonymous functions: 00:01:00 •Use lapply with additional arguments: 00:04:00 •Additional Materials: 00:00:00 •What is sapply?: 00:02:00 •How to use sapply: 00:02:00 •sapply with your own function: 00:02:00 •sapply with a function returning a vector: 00:02:00 •When can't sapply simplify?: 00:02:00 •What is vapply and why is it used?: 00:04:00 •Additional Materials: 00:00:00 •Mathematical functions: 00:05:00 •Data Utilities: 00:08:00 •Additional Materials: 00:00:00 •grepl & grep: 00:04:00 •Metacharacters: 00:05:00 •sub & gsub: 00:02:00 •More metacharacters: 00:04:00 •Additional Materials: 00:00:00 •Today and Now: 00:02:00 •Create and format dates: 00:06:00 •Create and format times: 00:03:00 •Calculations with Dates: 00:03:00 •Calculations with Times: 00:07:00 •Additional Materials: 00:00:00 •Get and set current directory: 00:04:00 •Get data from the web: 00:04:00 •Loading flat files: 00:03:00 •Loading Excel files: 00:05:00 •Additional Materials: 00:00:00 •Base plotting system: 00:03:00 •Base plots: Histograms: 00:03:00 •Base plots: Scatterplots: 00:05:00 •Base plots: Regression Line: 00:03:00 •Base plots: Boxplot: 00:03:00 •Introduction to dplyr package: 00:04:00 •Using the pipe operator (%>%): 00:02:00 •Columns component: select(): 00:05:00 •Columns component: rename() and rename_with(): 00:02:00 •Columns component: mutate(): 00:02:00 •Columns component: relocate(): 00:02:00 •Rows component: filter(): 00:01:00 •Rows component: slice(): 00:04:00 •Rows component: arrange(): 00:01:00 •Rows component: rowwise(): 00:02:00 •Grouping of rows: summarise(): 00:03:00 •Grouping of rows: across(): 00:02:00 •COVID-19 Analysis Task: 00:08:00 •Additional Materials: 00:00:00 •Assignment - R Programming for Data Science: 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python 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 Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python 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 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Overview This comprehensive course on Ultimate PHP & MySQL Web Development Course & OOP Coding will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Ultimate PHP & MySQL Web Development Course & OOP Coding 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 Ultimate PHP & MySQL Web Development Course & OOP Coding. It is available to all students, of all academic backgrounds. Requirements Our Ultimate PHP & MySQL Web Development Course & OOP Coding 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 • 133 lectures • 10:06:00 total length •Introduction: 00:02:00 •Setup On Windows: 00:15:00 •Setup On Mac: 00:11:00 •Setup On Linux: 00:12:00 •Online Code Editor: 00:03:00 •Basic File Syntax: 00:05:00 •Printing (echo): 00:06:00 •Comments: 00:05:00 •Variables: 00:06:00 •Variable Data Types: 00:07:00 •Variable Naming: 00:03:00 •Constants: 00:02:00 •Arrays: 00:05:00 •Associative Arrays: 00:06:00 •Multidimensional Arrays: 00:04:00 •if Statement: 00:06:00 •ifelse Statement: 00:02:00 •ifelseifelse Statement: 00:05:00 •Switch Statement: 00:06:00 •while Loop: 00:06:00 •doWhile Loop: 00:03:00 •for Loop: 00:03:00 •foreach Loop: 00:05:00 •Break Statement: 00:02:00 •Continue Statement: 00:02:00 •Basic Function: 00:03:00 •Passing Function Arguments: 00:03:00 •Passing Function Arguments By Reference: 00:04:00 •Default Argument Value: 00:02:00 •Function Returning Values: 00:05:00 •Dynamic Function Calls: 00:03:00 •Variable Scope: 00:04:00 •Simple HTML Form: 00:07:00 •GET vs POST: 00:05:00 •$_SERVER ['PHP_SELF']: 00:07:00 •Validating Form Data With PHP: 00:07:00 •Required Fields: 00:05:00 •Display Error Messages: 00:05:00 •Validate Name: 00:03:00 •Validate Email: 00:03:00 •Validate URL: 00:07:00 •Keep The Values In The Form: 00:04:00 •Read File (readfile()): 00:02:00 •Open, Read & Close A File (fopen(), fread(), fclose()): 00:04:00 •Read Single Line (fgets()): 00:03:00 •Check End-Of-File (feof()): 00:02:00 •Read Single Character (fgetc()): 00:02:00 •Write To File (fwrite()): 00:03:00 •Configure php.ini File For File Uploading: 00:02:00 •Front End HTML Upload Form: 00:04:00 •PHP Upload Script: 00:15:00 •Check If File Exists: 00:03:00 •Limit File Size: 00:05:00 •Limit File Type: 00:04:00 •MySQL vs MySQLi vs PDO: 00:05:00 •Creating A Database & Table (phpMyAdmin): 00:06:00 •Connecting To A Database: 00:06:00 •Get Data Using SELECT Query: 00:10:00 •WHERE Property For Filtering: 00:03:00 •LIKE Property For Pattern Search: 00:02:00 •Sorting Results Using ORDER BY Property: 00:01:00 •Using JOINS: 00:08:00 •Insert Data Using INSERT Query: 00:04:00 •Get ID Of The Last Inserted Row: 00:02:00 •Insert Multiple Rows: 00:05:00 •Update Data Using UPDATE Query: 00:03:00 •Delete Data Using DELETE Query: 00:02:00 •Delete All Rows In A Table Using TRUNCATE Query: 00:02:00 •Delete Table Using DROP Query: 00:02:00 •Limit Data Selections Using LIMIT, ROWNUM: 00:04:00 •Create Table Using CREATE Query: 00:03:00 •Clone/Duplicate Table: 00:03:00 •Alter Table: 00:05:00 •Create Database: 00:02:00 •Drop Database: 00:02:00 •SQL Injection & Prepared Statements: 00:09:00 •What Is XML?: 00:02:00 •What Is SimpleXML?: 00:02:00 •Parse XML String: 00:08:00 •Parse XML File: 00:02:00 •Get Node Values: 00:02:00 •Get Node Values of Specific Elements: 00:03:00 •Get Node Values - Loop: 00:03:00 •Get Attribute Values: 00:02:00 •What Is The XML Expat Parser?: 00:02:00 •Initializing The XML Expat Parser: 00:10:00 •Load and Output XML Using DOM Parser: 00:02:00 •Looping Through XML Using DOM Parser: 00:03:00 •What Is AJAX?: 00:02:00 •Load Simple Data Using AJAX Front End: 00:08:00 •Load Simple Data Using AJAX Back End: 00:05:00 •Load Data From A Database Using AJAX: 00:08:00 •Send A Plain Text Email: 00:04:00 •Send A HTML Email: 00:06:00 •Email Attachments: 00:17:00 •PHPMailer Setup: 00:03:00 •Send Email Using PHPMailer: 00:04:00 •Send HTML Email Using PHPMailer: 00:04:00 •Email Attachments Using PHPMailer: 00:02:00 •What Is Object Oriented Programming (OOP)?: 00:03:00 •Basic Class With Variables: 00:04:00 •Functions: 00:05:00 •Constructor: 00:04:00 •Destructor: 00:02:00 •Inheritance: 00:06:00 •Multi Class Inheritance: 00:03:00 •Function Overriding: 00:03:00 •Public vs Private vs Protected: 00:05:00 •Interfaces: 00:04:00 •Constants: 00:03:00 •Abstract Class: 00:06:00 •Static Keyword: 00:03:00 •Final Keyword: 00:02:00 •Initiating Parent Constructor: 00:02:00 •die() Function: 00:02:00 •Custom Error Handler: 00:04:00 •Triggering An Exception: 00:03:00 •Exception Handling: 00:05:00 •Create Database & Table: 00:04:00 •User Class & Database Connection: 00:15:00 •Register User Form: 00:09:00 •Inserting User Data Into Database: 00:10:00 •Registration Form Field Validation: 00:12:00 •Securing User Password: 00:03:00 •Check If Username or Email Already Exists: 00:11:00 •Retain Data After Failed Registration: 00:03:00 •Validate an Integer Within a Range: 00:04:00 •Validate IPv6 Address: 00:03:00 •Validate URL - Must Contain QueryString: 00:03:00 •Remove Characters With ASCII Value > 127: 00:04:00 •Including & Requiring External PHP Files: 00:05:00 •Resource: 00:00:00 •Assignment - Ultimate PHP & MySQL Web Development Course & OOP Coding: 00:00:00

Overview This comprehensive course on Social Media Website Development Using Wordpress will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Social Media Website Development Using Wordpress 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 Social Media Website Development Using Wordpress. It is available to all students, of all academic backgrounds. Requirements Our Social Media Website Development Using Wordpress 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 12 sections • 22 lectures • 03:10:00 total length •1.1 Instructor Introduction: 00:03:00 •1.2 Course Introduction: 00:06:00 •2.1 Installing WordPress on Localhost: 00:12:00 •2.2 Domain and Hosting: 00:08:00 •2.3 WordPress and SSL Installation on Subdomain: 00:08:00 •2.4 Website Walkthrough: 00:06:00 •2.5 Installing Themes and Plugins: 00:08:00 •3.1 Landing Page: 00:15:00 •3.2 2nd and 3rd Section of Homepage: 00:07:00 •3.3 Call to Action: 00:08:00 •3.4 Latest Post: 00:07:00 •3.5 Newsletter: 00:06:00 •4.1 General Settings, Profile Fields, Create User Account and Friend Request: 00:20:00 •5.1 Creating Groups: 00:05:00 •6.1 About Us Page: Part-1: 00:10:00 •6.2 About Us Page: Part-2: 00:10:00 •7.1 Contact Us Page: 00:15:00 •8.1 FAQ Page: 00:05:00 •9.1 Blog Page: 00:03:00 •10.1 Main Menu and Left Panel Menu: 00:07:00 •11.1 Designing the Footer: 00:12:00 •12.1 Creating Events and Group Points: 00:09:00

Overview This comprehensive course on Make Cinematics Using Unreal Engine 5 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Make Cinematics Using Unreal Engine 5  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 Make Cinematics Using Unreal Engine 5. It is available to all students, of all academic backgrounds. Requirements Our Make Cinematics Using Unreal Engine 5 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 2 sections • 15 lectures • 02:08:00 total length •Introduction: 00:02:00 •Download Unreal Engine 5: 00:02:00 •How To Create New Project: 00:03:00 •Unreal Engine Shortcuts: 00:14:00 •How To Import Assets: 00:11:00 •How To Use Sequencer: 00:11:00 •How To Use The Camera: 00:08:00 •How To Use Camera Rail: 00:07:00 •How To Use Camera Crane: 00:03:00 •Let's Animate The Scene: 00:28:00 •Animating The Characters: 00:06:00 •Combining The Sequencers: 00:04:00 •Adding Effects: 00:17:00 •Activate Sequence: 00:08:00 •Blueprints Features: 00:04:00