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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

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 With the ever-increasing demand for Data Analysis Level 3 Diploma in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Data Analysis Level 3 Diploma may be. Learning about Data Analysis Level 3 Diploma or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Data Analysis Level 3 Diploma . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Data Analysis Level 3 Diploma is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Data Analysis Level 3 Diploma course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Data Analysis Level 3 Diploma course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Data Analysis Level 3 Diploma course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Data Analysis Level 3 Diploma , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Data Analysis Level 3 Diploma , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Data Analysis Level 3 Diploma , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Data Analysis Level 3 Diploma course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams.     Course Curriculum Module 1 Introduction to Data Analysis. Introduction to Data Analysis. 00:00 Module 2 Mathematics and Statistics. Mathematics and Statistics. 00:00 Module 3 Data Manipulation. Data Manipulation. 00:00 Module 4 Data Visualisation. Data Visualisation. 00:00 Module 5 Data Wrangling. Data Wrangling. 00:00 Module 6 Data Exploration. Data Exploration. 00:00 Module 7 Machine Learning Fundamentals. Machine Learning Fundamentals. 00:00 Module 8 Machine Learning Algorithms. Machine Learning Algorithms. 00:00 Module 9 Data Analysis with Python and Libraries. Data Analysis with Python and Libraries. 00:00 Module 10 Data Analysis with R and Libraries. Data Analysis with R and Libraries. 00:00

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

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Register on the Google Data Studio: Data Analytics today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Google Data Studio: Data Analytics is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Google Data Studio: Data Analytics Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Google Data Studio: Data Analytics, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Section 01: Introduction Course Overview 00:01:00 Section 02: Google Sheets Format Data in Google Sheets 00:08:00 Sheets Function 2: Vlookup & Defined Range 00:10:00 Sheets Function 3: Cross Table Calculations 00:09:00 Section 03: Google Data Studio Connect Data to Google Data Studio 00:04:00 GDS Calculated Fields 00:08:00 GDS Theme Customization 00:07:00 GDS Page Layout Design 00:17:00 GDS Charts: Scorecards 00:12:00 GDS Charts: Time Series Graphs 00:09:00 GDS Blending and Joining Data Tables 00:07:00 GDS Charts: Bar, Donut, and Treemap 00:17:00 GDS Charts: Interactive Filters 00:05:00 GDS Project Page Completion 00:17:00 GDS Client Page Completion 00:11:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. 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Get a Free CPD Accredited Certificate upon completion of Functional Skills: IT Get a free student ID card with Functional Skills: IT Training program (£10 postal charge will be applicable for international delivery) The Functional Skills: IT is affordable and simple to understand This course is entirely online, interactive lesson with voiceover audio Get Lifetime access to the Functional Skills: IT course materials The Functional Skills: IT comes with 24/7 tutor support Start your learning journey straightaway! *** Course Curriculum *** Course 01: Essential IT Skills Level 2 Module 01: Introduction: A Transforming Technology Module 02: Importance of Information Technology Module 03: Communication and Network Module 04: Future Skills Required in Information Technology Module 05: Technology as a Foundation Skill Area Module 06: Word Processing Software Module 07: Presentation Software Module 08: Creating and Editing Spreadsheet (Part 1: The Basics of Spreadsheets) Module 09: Creating and Editing Spreadsheet (Part 2: Navigation and Edit) Module 10: Storing Database Module 11: Information Technology Project Management Course 02: Fundamentals of CSS Unit 01: CSS In Context Module 01: What Was CSS Originally Intended To Do? Module 02: DEMO: The Most Basic CSS Usage Module 03: Responsive Design Module 04: Chapter Summary Unit 02: Overview Of CSS Module 01: What is CSS? Module 02: Where Can You Find CSS? Module 03: What CSS Can and Can't Do Module 04: Optional Demo - Serving an HTML Application Module 05: How Do we Add CSS to a Website? Unit 03: Styling HTML Elements With CSS Module 01: Why do We Style CSS Elements? Module 02: CSS and Fonts Module 03: DEMO: Styling Text with CSS Module 04: Sizing HTML Elements with CSS Module 05: DEMO: Sizing HTML Elements with CSS Unit 04: Arranging Elements With CSS Module 08: Summary of this Chapter Module 01: Introduction Module 02: Adding Margin with CSS Module 03: Advanced Positioning with CSS Module 04: DEMO: Positioning Elements Absolutely and Relatively Module 05: Positioning HTML Elements with Float Course 03: Office Administration & Skills Diploma Module 01: Personal Assistant Module 02: Admin Support Module 03: Administrative Management Module 04: Organisational Skills Module 05: Telephone Etiquette Module 06: Business Writing Module 07: Time Management Module 08: Body Language And Effective Communication Module 09: Meeting Management Module 10: Excel Basics Module 11: PowerPoint Basic Course 04: Time Management Module 01: Importance And Benefits Of Time Management Module 02: Assess Your Current Work Practice Module 03: Identify The Priorities Module 04: Overcome Procrastination Module 05: Set Your Goals Module 06: Plan The Work And Work The Plan Module 07: Effective Time Management Techniques Module 08: The Art Of Anticipating How will I get my Certificate? After successfully completing the course, you will be able to order your Certificates as proof of your achievement. PDF Certificate: Free (Previously it was £12.99*4 = £51) CPD Hard Copy Certificate: £29.99 CPD 40 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about the topic is advised to take this Functional Skills: IT, CSS & Office Administration bundle. This bundle is ideal for: Office professionals School leavers Job seekers Anyone seeking in-demand skills Requirements You will not need any prior background or expertise to enrol in this Functional Skills: IT, CSS & Office Administration bundle. Career path After completing this Functional Skills: IT, CSS & Office Administration bundle, you are to start your career or begin the next phase of your career. Admin Assistant IT Support Web Developer Project Manager Office Manager Business Analyst Certificates CPD Accredited Digital Certificate Digital certificate - Included Upon passing the Course, you need to order a Digital Certificate for each of the courses inside this bundle as proof of your new skills that are accredited by CPD QS for Free. CPD Accredited Hard Copy Certificate Hard copy certificate - £29.99 Please note that International students have to pay an additional £10 as a shipment fee.

Overview   With the ever-increasing demand for English in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in English may be.   Learning about English or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in English. That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on English is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates.   The self-paced online learning methodology by Compete High in this Functional Skills English Training course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course!   Instead of searching for hours, enrol right away on this Functional Skills English Training course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run.   Who is this course for?   While we refrain from discouraging anyone wanting to do this Functional Skills English Training course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of English, Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in English, Anyone looking for a certificate of completion on doing an online training on this topic, Students of English, or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity   Career Path   This Functional Skills English Training course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. Course Curriculum Module 1 - Word Word 00:00 Module 2 - Sentence Sentence 00:00 Module 3 - Parts of speech Parts of speech 00:00 Module 4 - Noun & Pronoun Noun & Pronoun 00:00 Module 5 - Adjective Adjective 00:00 Module 6 - Verb Verb 00:00 Module 7 - Adverb Adverb 00:00 Module 8 - Article Article 00:00 Module 9 - Preposition Preposition 00:00 Module 10 - Punctuation Punctuation 00:00