2270 Software Development courses delivered On Demand

Data is the lifeblood of any business, and data administrators are responsible for ensuring that it is accurate, secure, and accessible. With the rise of big data, the demand for skilled data administrators in the UK is skyrocketing, with an impressive growth rate of 15% in job demand over the past year alone. What's more, professionals in this domain command handsome salaries, ranging between £50,000 to £85,000 annually. If you're interested in a career in data administration, or if you're looking to advance your existing career, our Data Administration Processes course is the perfect place to start. This comprehensive course will teach you everything you need to know about data administration, from the basics of data modeling and database design to more advanced topics such as data security and disaster recovery. Embracing this course can be a pivotal stepping stone in solidifying your career as a top-tier data administrator. Why would you choose the Data Administration Processes course from Compliance Central: Lifetime access to Data Administration Processes course materials Full tutor support is available from Monday to Friday with the Data Administration Processes course Learn Data Administration Processes skills at your own pace from the comfort of your home Gain a complete understanding of Data Administration Processes course Accessible, informative Data Administration Processes learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Data Administration Processes Study Data Administration Processes in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Data Administration Processes Course Data Administration Processes Curriculum Breakdown of the Data Administration Processes Course Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding Data Administration Processes Course Learning Outcomes: Grasp foundational principles of data administration processes. Analyse and interpret various data visualisation tools. Understand and implement effective performance measurement structures. Recognize and address data variations strategically. Employ techniques to drive improvement through data. Present performance data with clarity and precision. Apply theoretical knowledge in real-world scenarios. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Data Administration Processes course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Data Administration Processes. It is also great for professionals who are already working in Data Administration Processes and want to get promoted at work. Requirements To enrol in this Data Administration Processes course, all you need is a basic understanding of the English Language and an internet connection. Career path The Data Administration Processes course will enhance your knowledge and improve your confidence. Data Analyst: £25,000 to £60,000 per year Data Entry Specialist: £18,000 to £30,000 per year Database Administrator: £30,000 to £65,000 per year Data Quality Manager: £35,000 to £70,000 per year Business Intelligence Analyst: £30,000 to £60,000 per year 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

Unlock the fundamentals of Islamic finance with our comprehensive online course. Whether you're new to the field or seeking to deepen your understanding, this course offers a structured exploration into the principles that govern ethical financial practices in Islam. Key Features: CPD Certified Free Certificate from Reed CIQ Approved Developed by Specialist Lifetime Access In this course on Fundamentals of Islamic Finance, learners delve into the ethical principles and operational framework of financial practices aligned with Islamic law (Shariah). They explore the fundamental concepts that distinguish Islamic finance from conventional finance, such as the prohibition of interest (riba) and the emphasis on profit-sharing arrangements (mudarabah and musharakah). The course covers practical applications of Islamic finance in various financial products and services, including Takaful (Islamic insurance) and Islamic funds. It also addresses risk management strategies unique to Islamic finance contexts. Learners gain insights into the adaptation and implementation of Islamic financial principles within the regulatory environment of the United Kingdom. Overall, the curriculum equips learners with a comprehensive understanding of how Islamic finance operates ethically and effectively within global financial systems, preparing them to navigate and contribute to this specialized field. Course Curriculum Module 01: Ethics and Principles of Islamic Finance Module 02: Fundamentals of Islamic Finance Module 03: Islamic Finance in Practice Module 04: Takaful Module 05: Islamic Funds and Risk Management Module 06: Islamic Finance in the UK Learning Outcomes: Explain key principles of Islamic finance ethics and regulations confidently. Apply fundamental concepts of Islamic finance in theoretical scenarios effectively. Analyse practical applications of Islamic finance principles in real-world contexts. Describe the principles and operations of Takaful insurance accurately. Evaluate risk management strategies within Islamic funds comprehensively. Discuss the development and challenges of Islamic finance in the UK. CPD 10 CPD hours / points Accredited by CPD Quality Standards Fundamentals of Islamic Finance 1:26:06 1: Module 01: Ethics and Principles of Islamic Finance 11:06 2: Module 02: Fundamentals of Islamic Finance 14:52 3: Module 03: Islamic Finance in Practice 10:22 4: Module 04: Takaful 14:03 5: Module 05: Islamic Funds and Risk Management 18:28 6: Module 06: Islamic Finance in the UK 16:15 7: CPD Certificate - Free 01:00 Who is this course for? Financial professionals seeking knowledge in Islamic finance principles. Students interested in understanding ethical financial practices in Islamic contexts. Researchers exploring the application of Sharia-compliant finance in global markets. Individuals pursuing careers in Islamic banking and finance sectors. Consultants advising on financial services compliant with Islamic law. Career path Islamic Finance Analyst Sharia Compliance Officer Takaful Insurance Specialist Islamic Investment Advisor Financial Risk Manager Islamic Finance Consultant Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

A beginner-level course that will help you learn all you need to know about building applications using Python 3, FAST API, MongoDB, and NoSQL as well as front-end technologies such as HTML, CSS, JSX, and REACT JS with live demonstrations. You need to know the basics of HTML, CSS, and JavaScript to get started

This course is a comprehensive and concise resource for learning flexbox. You will learn the key properties of flexbox and discover techniques to build advanced responsive website layouts in no time.

Course Overview Master CSS programming language in no time, with this complete training course for learners of all levels.  The CSS Web Development Course Beginner to Advanced course will teach you all you need to know about web development with CSS. Broken down into 3 key modules, it will take you through the process of building high-quality websites, writing future-proof CSS, and styling web pages like a pro.  Through this comprehensive training program, you will gain a wide range of industry skills needed to take your web development career to the next level. It covers up-to-date knowledge that every aspiring developer should know, with easy-to-follow video tutorials, to ensure you get the best out of your learning experience. This best selling CSS Web Development Course Beginner to Advanced has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth CSS Web Development Course Beginner to Advanced is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The CSS Web Development Course Beginner to Advanced is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The CSS Web Development Course Beginner to Advanced is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the CSS Web Development Course Beginner to Advanced, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the CSS Web Development Course Beginner to Advanced will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the CSS Web Development Course Beginner to Advanced to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

In today's rapidly evolving digital era, the fusion of finance and technology has paved the way for unprecedented opportunities. Enter the world of FinTech, Cryptocurrency, and the power of Data Analysis. With this 'Data Analytics (Data Analysis), FinTech and Cryptocurrency' bundle, you're taking the first step into a realm where Data Analysis isn't just a tool-it's the core of decision-making. Dive deep into the nuances of modern finance, learn the intricacies of Cryptocurrency, and harness the might of Data Analysis to make informed strategies. In the UK, professionals in these fields can enjoy impressive salary ranges, with earnings starting from £35,000 per year and reaching up to £80,000 per year, making it an enticing career choice. This bundle includes three courses that will equip you with the essential knowledge and skills to excel in this domain. This comprehensive Data Analysis bundle provides a valuable opportunity to explore the world of finance, technology, and data. By enrolling in these Data Analysis bundles, you will gain a deep understanding of the innovations shaping the financial industry, such as blockchain and artificial intelligence, and how they intersect with technology. Each Data Analytics (Data Analysis) course in FinTech and Cryptocurrency bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Data Analysis bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Immerse yourself in these diverse, enthralling subjects, each designed to fuel your curiosity and enhance your knowledge. Dive in now! The courses in this Data Analysis bundle include: Course 1: FinTech Course 2: Cryptocurrency Course 3: Data Analytics Learning Outcomes: By completing this Data Analysis bundle, you will achieve the following learning outcomes: Understand the principles and applications of FinTech in the financial industry. Leverage Data Analysis for informed decision-making in finance and digital currencies. Use Data Analysis to forecast market trends in FinTech and Cryptocurrency. Apply statistical analysis techniques to interpret data effectively. Elevate financial proficiency by integrating insights from Data Analysis. Develop a strategic mindset for leveraging data analytics in FinTech and Cryptocurrency. The first course, FinTech, delves into the fascinating intersection of finance and technology. Gain a deep understanding of the technological innovations that are revolutionising the financial industry, including blockchain, artificial intelligence, and mobile banking. Explore the impact of digital currencies, peer-to-peer lending, and robo-advisors on traditional financial systems. The second course, Cryptocurrency, uncovers the secrets of this decentralised digital currency phenomenon. Discover the fundamentals of cryptocurrencies, such as Bitcoin and Ethereum, and explore the underlying blockchain technology. Dive into topics like mining, digital wallets, smart contracts, and the future of cryptocurrencies. Develop a solid foundation to navigate the complex world of digital assets. The third course, Data Analytics, equips you with the essential skills to extract insights from vast amounts of data. Learn the techniques and tools used to collect, clean, and analyze data, allowing you to make informed decisions and predictions. Dive into statistical analysis, data visualisation, and machine learning algorithms. Harness the power of data to drive business growth and enhance decision-making processes. CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Data Analytics (Data Analysis) in FinTech and Cryptocurrency course is suitable for: Professionals aspiring to work in the FinTech or Cryptocurrency sectors. Financial analysts seeking to enhance their data analytics skills. Entrepreneurs who are interested in leveraging technology to innovate in the financial industry. Graduates looking to enter the finance or technology sectors with a competitive edge. Business professionals aiming to stay ahead of industry trends. Requirements You can delightfully enrol in this Data Analytics (Data Analysis) in FinTech and Cryptocurrency course without any formal requirements. Career path You can pursue various exciting career paths in FinTech and Cryptocurrency, including: Financial Data Analyst: £35,000 - £50,000 per year. Blockchain Developer: £45,000 - £75,000 per year. Cryptocurrency Investment Analyst: £50,000 - £80,000 per year. FinTech Consultant: £40,000 - £65,000 per year. Data Scientist (Financial Sector): £55,000 - £90,000 per year. Certificates Certificate Of Completion Digital certificate - Included Certificate Of Completion Hard copy certificate - £9.99

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