80 Data Engineering courses in London delivered On Demand

Deal with large numbers and key information in this Big Data Course Are interested in understanding and protecting big data? Do you want to utilize any data that have been presented to you to its full extent? This Innovative Course will solve all of your problems! Big data is a term that describes the large volume of data - both structured and unstructured - that inundates a business on a day-to-day basis. Interpreting data is of immense importance when you handle data. Only then you can fully use it to your business. At the same time when you use data online, there is always a chance that your data can be stolen. Learn how to protect your information in this data bundle course. Make your own database and reap its benefits. Since there are people who do not like to deal with database, scripts and all the technical parts, this hinders them to start learning because they already have the mindset that it is difficult. Understanding Big Data course will give you a clear perception on how to deal with large data and ways you can easily handle them. This course has multiple units designed to help your data managing skills. Course Highlights Understanding Big Data is an award winning and the best selling course that has been given the CPD Certification & CiQ accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Understanding Big Data into 6 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 6 hours hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose Understanding Big Data Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Understanding Big Data is CPD certified and CiQ accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Understanding Big Data is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and CiQ accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Understanding Big Data What Is Big Data? Hint: You're a Part of It Every Day FREE 01:00:00 Why Is Big Data Important? FREE 01:00:00 Why IBM for Big Data? 01:00:00 All About Hadoop: The Big Data Lingo Chapter 01:00:00 InfoSphere BigInsights: Analytics for Big Data at Rest 01:00:00 IBM InfoSphere Streams: Analytics for Big Data in Motion 01:00:00 Mock Exam Final Exam

Are interested in understanding and protecting big data? Do you want to utilize any data that have been presented to you to its full extent? This Bundle Course will solve all of your problems!  Interpreting data is of immense importance when you handling data. Only then you can fully use it to your business. At the same time when you use data online, there is always a chance that your data can be stolen. Learn how to protect your information in this data bundle course. Make you own database and reap its benefits. In this course, you will know how to create your database and database user.You will then master how to import database tables since most new scripts come with a built-in installer, the scripts create all database, but when the time comes that there is no installer provided, then you have to create one manually. Upon completion of the course the students will possess a solid knowledge of data protection law, as well as an understanding of the practical implications for different organisations. Course Highlights Data Bundle Course is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Data Bundle Course into several modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 20/30 hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose Data Bundle Course Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Data Bundle Course is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Data Bundle Course is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Module 1: Database Basics What is a Database FREE 01:00:00 Definition of Terms FREE 01:00:00 Database Users and Languages 01:00:00 Components of a Database System 01:00:00 Basic Set Concepts 01:00:00 Relations as a Database 01:00:00 Relational Database Operators 01:00:00 Database keys 01:00:00 Module 2: Understanding Big Data What Is Big Data? Hint: You're a Part of It Every Day FREE 01:00:00 Why Is Big Data Important? FREE 01:00:00 Why IBM for Big Data? 01:00:00 All About Hadoop: The Big Data Lingo Chapter 01:00:00 InfoSphere BigInsights: Analytics for Big Data at Rest 01:00:00 IBM InfoSphere Streams: Analytics for Big Data in Motion 01:00:00 Module 3: Data Protection Why Internet Marketers Need More Protection FREE 01:00:00 You Can't Be Anonymous FREE 00:15:00 Start With Basic Security Measures 01:00:00 Using Disclaimers 01:00:00 Proper Use Of Email 01:00:00 Protecting Product Rights 01:00:00 Protecting Your Website 01:00:00 Terms Of Use Or Service 00:30:00 Privacy Policy 01:00:00

Overview In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of 'Data Science & Machine Learning with R from A-Z,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R. Learning Outcomes: Understand the foundational concepts of data science and machine learning. Familiarise oneself with the R environment and its functionalities. Master data types, structures, and advanced techniques in R. Acquire proficiency in data manipulation and visual representation using R. Generate comprehensive reports using R Markdown and design web applications with R Shiny. Gain a thorough understanding of machine learning methodologies and their applications. Gain insights into initiating a successful career in the data science sector. Why buy this Data Science & Machine Learning with R from A-Z course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Data Science & Machine Learning with R from A-Z there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Data Science & Machine Learning with R from A-Z course for? This course is ideal for Individuals keen on exploring the intricacies of machine learning and data science. Aspiring data analysts and scientists looking to specialise in Machine Learning with R. IT professionals aiming to diversify their skill set in the emerging data-driven market. Researchers seeking to harness the power of R for data representation and analysis. Academics and students aiming to bolster their understanding of modern data practices with R. Prerequisites This Data Science & Machine Learning with R from A-Z does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Science & Machine Learning with R from A-Z was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Scientist - Average salary range: £35,000 - £70,000 Per Annum Machine Learning Engineer - Average salary range: £50,000 - £80,000 Per Annum Data Analyst - Average salary range: £28,000 - £55,000 Per Annum R Developer - Average salary range: £30,000 - £60,000 Per Annum R Shiny Web Developer - Average salary range: £32,000 - £65,000 Per Annum Machine Learning Researcher - Average salary range: £40,000 - £75,000 Per Annum Course Curriculum Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Getting Started with R Getting Started 00:11:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Assignment Assignment - Data Science & Machine Learning with R 00:00:00

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 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: 00:04:00 •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: 00:06:00 •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

Course Overview: Are you ready to unlock the world of digital possibilities by understanding the art and science of data analytics? We live in an era where data back every decision and every action requires insightful analysis. Clive Humby said, "Data is the new oil, and it's the new oil, so it's an invaluable resource for companies worldwide. This comprehensive course covers a broad spectrum of data analytics, starting with an engaging 'Introduction to the World of Data,' before delving into the fundamental components like the 'Basics of Data Analytics,' 'Statistics for Data Analytics,' and the 'Actions Taken in the Data Analysis Process.' Each subsequent module is carefully designed to guide you through various stages of data analytics. You'll explore 'Data Mining,' work with 'Excel for Data Analytics,' and discover 'Tools for Data Analytics.' The curriculum wraps up with a focus on 'Data-Analytic Thinking' and 'Data Visualisation.' Enrol today and start your journey to becoming a data analytics expert! Key Features of the Course: This course comes with a CPD certificate, affirming your proficiency in data analytics. It offers 24/7 learning assistance to ensure you get the most out of your learning journey. The content is presented in easy-to-understand and engaging learning materials, carefully curated to make your journey in data analytics enlightening. Who is This Course For? This course suits professionals seeking to leverage data analytics in their respective fields, individuals aspiring to venture into the data science arena, and students keen to acquire contemporary skills for the digital age. What You Will Learn: Understand the fundamental concepts of data analytics. Apply statistical techniques to analyse large data sets. Implement effective strategies for data collection and storage. Master the art of data mining and extraction of valuable insights. Utilise Excel and other tools effectively for data analysis. Develop a data-analytic mindset for problem-solving. Translate data insights into compelling visualisations. Why Enrol in This Course: This course will open doors to many opportunities. You will learn from top-notch professionals, utilise quality learning materials and have access to trending and recently updated curriculum. Requirements: A basic understanding of computers A willingness to learn Career Path: The expertise gained from this Data Analytics course can pave your way into a variety of professions, such as: Data Analyst (£30,000-£60,000) Business Analyst (£35,000-£70,000) Market Research Analyst (£27,000-£55,000) Operations Analyst (£31,000-£62,000) Quantitative Analyst (£45,000-£85,000) Data Scientist (£50,000-£90,000) Data Engineer (£35,000-£75,000) Certification: On successful completion of this course, you will receive a CPD certificate, testifying your mastery in the field of data analytics. With this recognition, you can confidently showcase your skills and expertise in the professional world. Data analytics is a powerful tool that can be used to make better decisions, improve efficiency, and drive innovation. If you want to join this growing field, this course is for you! FAQ What do you mean by data analytics? Data analytics is the process of collecting, cleaning, analyzing, and interpreting data to extract insights. What data analytics actually do? Data analytics helps businesses make better decisions by providing them with insights into their data. This can include insights into customer behavior, market trends, and product performance. What are the 5 data analytics? The 5 data analytics are: Descriptive analytics: This type of analytics describes what has happened in the past. Diagnostic analytics: This type of analytics identifies the root cause of problems. Predictive analytics: This type of analytics predicts what will happen in the future. Prescriptive analytics: This type of analytics recommends actions to take based on the predictions. Visual analytics: This type of analytics uses visual representations of data to make it easier to understand. What is data analytics examples? Here are some examples of data analytics: A retailer uses data analytics to track customer behaviour and identify trends. A bank uses data analytics to predict which customers are likely to default on their loans. A healthcare provider uses data analytics to identify patients who are at risk for certain diseases. What are 4 types of analytics? The 4 types of analytics are: Descriptive analytics: This type of analytics describes what has happened in the past. Diagnostic analytics: This type of analytics identifies the root cause of problems. Predictive analytics: This type of analytics predicts what will happen in the future. Prescriptive analytics: This type of analytics recommends actions to take based on the predictions. Why do we use data analytics? We use data analytics to make better decisions, improve efficiency, and drive innovation. Here are some of the benefits of using data analytics: Better decision-making: Data analytics can help businesses make better decisions by providing them with insights into their data. Improved efficiency: Data analytics can help businesses improve efficiency by identifying areas where they can save time and money. Driven innovation: Data analytics can help businesses drive innovation by identifying new opportunities and trends. Course Curriculum 13 sections • 13 lectures • 12:25:00 total length •Introduction to the World of Data: 01:00:00 •Basics of Data Analytics: 00:40:00 •Statistics for Data Analytics: 01:00:00 •Actions Taken in the Data Analysis Process: 00:55:00 •Gathering the Right Information: 01:00:00 •Storing Data: 01:15:00 •Data Mining: 01:00:00 •Excel for Data Analytics: 01:20:00 •Tools for Data Analytics: 01:20:00 •Data-Analytic Thinking: 01:10:00 •Data Visualisation That Clearly Describes Insights: 00:45:00 •Data Visualization Tools: 01:00:00 •Assignment - Data Analytics: 00:00:00

Overview This comprehensive course on Develop Big Data Pipelines with R & Sparklyr & Tableau will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Develop Big Data Pipelines with R & Sparklyr & Tableau 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 Develop Big Data Pipelines with R & Sparklyr & Tableau. It is available to all students, of all academic backgrounds. Requirements Our Develop Big Data Pipelines with R & Sparklyr & Tableau 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 6 sections • 20 lectures • 02:59:00 total length •Introduction: 00:12:00 •R Installation: 00:05:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:03:00 •Installing Sparklyr: 00:07:00 •Data Extraction: 00:06:00 •Data Transformation: 00:18:00 •Data Exporting: 00:07:00 •Data Pre-processing: 00:18:00 •Building the Predictive Model: 00:10:00 •Creating the Prediction Dataset: 00:10:00 •Installing Tableau: 00:02:00 •Loading the Data Sources: 00:05:00 •Creating a Geo Map: 00:12:00 •Creating a Bar Chart: 00:08:00 •Creating a Donut Chart: 00:15:00 •Creating the Magnitude Chart: 00:09:00 •Creating the Dashboard: 00:15:00 •Source Code: 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with R 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 R comes with accredited certification, 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 R. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with R 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 10 sections • 69 lectures • 22:07:00 total length •Data Science and Machine Learning Introduction: 00:03:00 •What is Data Science: 00:10:00 •Machine Learning Overview: 00:05:00 •Who is This Course for: 00:03:00 •Data Science and Machine Learning Marketplace: 00:05:00 •Data Science and Machine Learning Job Opportunities: 00:03:00 •Getting Started: 00:11:00 •Basics: 00:06:00 •Files: 00:11:00 •RStudio: 00:07:00 •Tidyverse: 00:05:00 •Resources: 00:04:00 •Unit Introduction: 00:30:00 •Basic Type: 00:09:00 •Vector Part One: 00:20:00 •Vectors Part Two: 00:25:00 •Vectors - Missing Values: 00:16:00 •Vectors - Coercion: 00:14:00 •Vectors - Naming: 00:10:00 •Vectors - Misc: 00:06:00 •Creating Matrics: 00:31:00 •List: 00:32:00 •Introduction to Data Frames: 00:19:00 •Creating Data Frames: 00:20:00 •Data Frames: Helper Functions: 00:31:00 •Data Frames Tibbles: 00:39:00 •Intermediate Introduction: 00:47:00 •Relational Operations: 00:11:00 •Conditional Statements: 00:11:00 •Loops: 00:08:00 •Functions: 00:14:00 •Packages: 00:11:00 •Factors: 00:28:00 •Dates and Times: 00:30:00 •Functional Programming: 00:37:00 •Data Import or Export: 00:22:00 •Database: 00:27:00 •Data Manipulation in R Introduction: 00:36:00 •Tidy Data: 00:11:00 •The Pipe Operator: 00:15:00 •The Filter Verb: 00:22:00 •The Select Verb: 00:46:00 •The Mutate Verb: 00:32:00 •The Arrange Verb: 00:10:00 •The Summarize Verb: 00:23:00 •Data Pivoting: 00:43:00 •JSON Parsing: 00:11:00 •String Manipulation: 00:33:00 •Web Scraping: 00:59:00 •Data Visualization in R Section Intro: 00:17:00 •Getting Started: 00:16:00 •Aesthetics Mappings: 00:25:00 •Single Variable Plots: 00:37:00 •Two Variable Plots: 00:21:00 •Facets, Layering, and Coordinate Systems: 00:18:00 •Styling and Saving: 00:12:00 •Creating with R Markdown: 00:29:00 •Introduction to R Shiny: 00:26:00 •A Basic R Shiny App: 00:31:00 •Other Examples with R Shiny: 00:34:00 •Machine Learning Part 1: 00:22:00 •Machine Learning Part 2: 00:47:00 •Starting a Data Science Career Section Overview: 00:03:00 •Data Science Resume: 00:04:00 •Getting Started with Freelancing: 00:05:00 •Top Freelance Websites: 00:05:00 •Personal Branding: 00:05:00 •Importance of Website and Blo: 00:04:00 •Networking Do's and Don'ts: 00:04:00

Course Overview: According to a report by the World Economic Forum, data analysts and scientists are among the top emerging job roles. The "Data Analytics with Tableau" course is tailored to equip learners with the vital skills required to excel in this dynamic field. The course delves into the intricacies of data visualisation and analysis using Tableau, a leading software in the industry. It's not merely about understanding data but transforming it into actionable insights that drive business decisions. The course is structured to provide a comprehensive understanding of various aspects of data analytics, including sales, HR, and shipping analytics.Don't miss this opportunity to advance your career with cutting-edge skills in data analytics. Enrol in "Data Analytics with Tableau" now and embark on a journey of professional growth and endless possibilities! Key Features of the Course: CPD Certificate: Upon completion, you will receive a prestigious Continuing Professional Development (CPD) certificate, recognised globally for enhancing your career prospects. 24/7 Learning Assistance: Our dedicated support team ensures you receive prompt assistance, providing a seamless learning experience. Who is This Course For? This course is tailored for individuals who aspire to become data analysts, business intelligence professionals, marketing strategists, or decision-makers seeking to leverage data effectively. No experience with Tableau or coding is required, making it accessible and engaging for beginners. What You Will Learn: Data Analytics with Tableau, This course covers a wide range of topics, starting with connecting and preparing data, where you will learn how to import, clean, and transform data to make it analysis-ready within Tableau. Next, you will master the art of building insightful charts and visualisations using Tableau's rich set of tools, enabling you to communicate data trends and insights effectively. Additionally, you will explore the creation of captivating headline cards and interactive dashboards, gaining expertise in presenting key information and facilitating data exploration. Real-world projects, including Discount Mart, Green Destinations, Super Store, Northwind Trade, and Tesla, will provide you with outstanding experience in applying Tableau to solve practical data challenges. Lastly, you will develop a solid understanding of database concepts and learn to create compelling data stories using Tableau's storytelling features. By the end of this course, you will have the skills and confidence to make data-driven decisions and communicate insights effectively using Tableau. Why Enrol in This Course: Join the recently updated top-reviewed Data Analytics course with Tableau to keep you at the forefront of the field. Expand your analytical skills, unlock career opportunities, and stay current in the rapidly evolving world of data analytics by mastering Tableau, the industry-standard tool for visual analytics. Requirements: No prior experience with Tableau or coding is required. All you need is a computer with internet access, a curious mind, and a passion for exploring the world of data analytics. Career Path: By acquiring data analytics skills with Tableau, you open doors to exciting career paths, such as: Data Analyst (Average Salary: £35,000 - £45,000) Business Intelligence Analyst (Average Salary: £40,000 - £55,000) Marketing Analyst (Average Salary: £30,000 - £40,000) Financial Analyst (Average Salary: £35,000 - £50,000) Data Visualization Specialist (Average Salary: £40,000 - £60,000) Database Administrator (Average Salary: £40,000 - £55,000) Data Scientist (Average Salary: £45,000 - £70,000) Certification: Upon successful completion of the course, you will receive a CPD certificate, internationally recognised for its validation of your expertise in data analytics with Tableau. Enrol now and embark on a transformative journey to become a proficient data analyst and visualisation expert with Tableau! Course Curriculum 9 sections • 41 lectures • 06:47:00 total length •Introduction to the Course: 00:02:00 •What is Tableau? An Introduction to Tableau: 00:03:00 •How this course is Structured: 00:01:00 •Installing the Free Full Version of Tableau: 00:02:00 •Project Brief for Discount Mart: 00:03:00 •Connecting and Preparing Data for Discount Mart: 00:15:00 •Building Charts on Tableau for Discount Mart (Part 1): 00:33:00 •Building Charts on Tableau for Discount Mart (Part 2): 00:16:00 •Creating Headline Cards on Tableau for Discount Mart: 00:10:00 •Building and Publishing Dashboards on Tableau: 00:15:00 •Project Brief for Green Destinations: 00:02:00 •Connecting and Preparing Data for Green Destinations: 00:09:00 •Building Charts on Tableau (Part 1) for Green Destinations: 00:28:00 •Building Charts on Tableau (Part 2) for Green Destinations: 00:08:00 •Creating Headline Cards on Tableau: 00:15:00 •Building a Dashboard for Green Destinations: 00:12:00 •Publish your Dashboard to Tableau Public: 00:02:00 •Project Brief for Super Store: 00:02:00 •Connecting and Preparing Data for Super Store: 00:17:00 •Building Charts on Tableau (Part 1) for Super Store: 00:34:00 •Building Charts on Tableau (Part 2) for Super Store: 00:23:00 •Building a Dashboard: 00:18:00 •Publish your Dashboard to Tableau Public: 00:03:00 •Project Brief for Northwind Trade: 00:03:00 •Connecting and Preparing Data for Northwind Trade: 00:14:00 •Building Charts on Tableau for Northwind Trade: 00:37:00 •Building and Publishing Dashboards for Northwind Trade: 00:10:00 •Project Brief for Tesla: 00:02:00 •Creating a Data Source through Google Sheet Functions: 00:05:00 •Connect to the Data for Tesla: 00:04:00 •Building Charts on Tableau for Tesla: 00:22:00 •Building Headline Cards: 00:09:00 •Building a Tesla Dashboard: 00:08:00 •Publish your Dashboard to Tableau Public: 00:03:00 •Introduction to Database Concepts: 00:01:00 •Understanding Relational Databases: 00:04:00 •Relationships of Database Entities: 00:02:00 •Primary and Foreign Keys: 00:01:00 •Data types and Naming Conventions: 00:04:00 •Creating Stories on Tableau: 00:05:00 •Resources - Data Analytics with Tableau: 00:00:00

Overview This comprehensive course on Building Big Data Pipelines with PySpark MongoDB and Bokeh will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 Building Big Data Pipelines with PySpark MongoDB and Bokeh. It is available to all students, of all academic backgrounds. Requirements Our Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 7 sections • 25 lectures • 05:04:00 total length •Introduction: 00:10:00 •Python Installation: 00:03:00 •Installing Third Party Libraries: 00:03:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:06:00 •Installing MongoDB: 00:04:00 •Installing NoSQL Booster for MongoDB: 00:07:00 •Integrating PySpark with Jupyter Notebook: 00:05:00 •Data Extraction: 00:19:00 •Data Transformation: 00:15:00 •Loading Data into MongoDB: 00:13:00 •Data Pre-processing: 00:19:00 •Building the Predictive Model: 00:12:00 •Creating the Prediction Dataset: 00:08:00 •Loading the Data Sources from MongoDB: 00:17:00 •Creating a Map Plot: 00:33:00 •Creating a Bar Chart: 00:09:00 •Creating a Magnitude Plot: 00:15:00 •Creating a Grid Plot: 00:09:00 •Installing Visual Studio Code: 00:05:00 •Creating the PySpark ETL Script: 00:24:00 •Creating the Machine Learning Script: 00:30:00 •Creating the Dashboard Server: 00:21:00 •Source Code and Notebook: 00:00:00

Building and Scaling a Data Science Culture As your data and AI teams scale from one to thousands of employees, you will encounter roadblocks along the way. From handling messy data to productionization and customer adoption, these obstacles can delay or even derail otherwise strong teams. Drawing on experiences gleaned from hundreds of clients, Michael Li presents a framework that successful companies have embraced to build and scale their data teams. The talk goes over how organizations progress along three maturity curves: Analytical, Operational, and Organizational. As enterprises strive to move along each of these maturity curves, they must solve various organizational challenges and develop new capabilities and skills in order to become data-driven organizations. We will provide key takeaways for managers and executives for each step of the maturity curves. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.