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Explore the world of cartography with the QGIS Cartography course. Uncover the power of Geographic Information Systems (GIS) and learn to create visually compelling maps. Delve into sections covering labels, symbology, base layers, and project setup. Discover techniques for styling water and land elements, and access valuable resources to enhance your cartography skills. Learning Outcomes: Understand the fundamentals of cartography and Geographic Information Systems (GIS). Learn to effectively label features on maps for clarity and readability. Explore various symbology techniques to visualize data and convey information. Create and customize base layers to provide context to your maps. Set up projects in QGIS, including organizing data and defining map layouts. Develop skills in styling water elements to enhance map aesthetics. Master the art of land styling, emphasizing topography and terrain representation. Access additional resources to expand your knowledge and cartographic expertise. Why buy this QGIS Cartography?  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 QGIS Cartography you will be able to take the MCQ test that will assess your knowledge. 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 course for? This QGIS Cartography course is ideal for GIS enthusiasts interested in mastering cartographic techniques. Geographers, urban planners, and environmental scientists seeking to enhance their mapping skills. Professionals involved in spatial data visualization and analysis. Students and researchers in fields related to geography, geospatial sciences, and urban planning. Prerequisites This QGIS Cartography 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 GIS Analyst - Average Earnings: £25,000 - £40,000 per year. Cartographer - Average Earnings: £25,000 - £35,000 per year. Geospatial Data Specialist - Average Earnings: £30,000 - £45,000 per year. Urban Planner - Average Earnings: £25,000 - £40,000 per year. Environmental Scientist - Average Earnings: £25,000 - £40,000 per year. Course Curriculum Section 01: Introduction Introduction 00:01:00 Section 02: Labels Labeling Basics 00:03:00 Labeling - Text Properties 00:02:00 Label Formatting 00:06:00 Label Buffers 00:04:00 Labels - Backgrounds 00:03:00 Label Shadows 00:03:00 Labeling Callouts (Leader Lines) 00:03:00 Labels - Placement 00:04:00 Labels - Rendering 00:05:00 Labeling Over Orthos 00:06:00 Fine Tuning Labels 00:03:00 Section 03: Symbology Styling Single Points Lines and Polygons 00:11:00 Styling Categorical Data 00:08:00 Styling Graduated Data 00:04:00 Shapeburst Fills 00:03:00 Texture Fills 00:04:00 Inverted Polygons 00:03:00 Advanced Lines 00:08:00 Section 04: Base Layers XYZ Tile Basemaps 00:04:00 Getting Data from the OSM Website 00:07:00 Getting Basemaps from the QuickMapServices Plugins 00:05:00 Getting OSM Data with Overpass Turbo 00:06:00 Rule Based Symbology 00:10:00 Rule Based Labeling 00:03:00 Bringing in Mapbox Baselayers (an Introduction) 00:13:00 Natural Earth Data 00:07:00 Section 05: Project Setup Setting Up a Page Layout 00:14:00 Layout Templates 00:05:00 Creating Map Grids (Lat & Long Graticules) 00:08:00 Inset or Overview Maps 00:05:00 Global Overview Maps 00:05:00 Adding a Legend 00:07:00 Adding Text to a Layout 00:03:00 Adding Images 00:05:00 Section 06: Water Styling Coastal Glow Effect 00:03:00 Concentric Water Lines (Equally Spaced) 00:05:00 Concentric Water Lines (Variably Spaced) 00:08:00 Half Tone Coastal Fill Pattern 00:06:00 Section 07: Land Styling Getting DEMs from USDA/NRCS 00:08:00 Creating Contour Lines from DEMs (in Feet and Meters) 00:11:00 Labeling Contour Lines 00:06:00 Drop Shadowing Polygon Features 00:03:00 Section 08: Resources Resources - QGIS Cartography 00:00:00 Assignment Assignment - QGIS Cartography 00:00:00

Medical Coding Certification: Clinical Coding Online Course at QLS Level 3 is the translation of medical documentation into standardised codes. This practice is integral for managing patient data, billing, and ensuring a streamlined healthcare delivery system. This meticulous process requires a comprehensive understanding of medical terminology, clinical jargon, and various coding systems such as ICD-10, OPCS-4, and SNOMED CT. Our Medical Coding Online Course provides a comprehensive curriculum that includes an introduction to clinical records, ICD-10 coding, OPCS-4, SNOMED CT, and the legal and ethical aspects of working in a clinical environment.  The Clinical Coding Online Course meticulously covers these crucial areas, ensuring you are well-equipped with the necessary knowledge and skills. By delving deep into the intricacies of clinical coding, the course prepares you to navigate the complexities of this field confidently. This is not just a course; it's your stepping stone towards mastering Medical Coding, and setting a solid foundation for your future in the healthcare sector. Understanding the significance of confidentiality in clinical records, the course also emphasises the legal and ethical aspects of working in a clinical environment. Through engaging modules and practical insights, you will explore the world of clinical coding in a structured, comprehensive manner. This Medical Coding Online Course is your gateway to unlocking new opportunities and overcoming the challenges in the ever-evolving landscape of clinical coding. Learning Outcomes Understand the principles of clinical coding. Recognise the importance of record confidentiality. Identify various clinical terminology and jargon. Apply the general coding standards of ICD-10. Utilise ICD-10 5th edition codes effectively. Comprehend the basics of OPCS-4 and SNOMED CT. Recognise the legal and ethical aspects of clinical environments. Why Choose This Medical Coding Certification: Clinical Coding Online Course at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Medical Coding Certification: Clinical Coding Online Course at QLS Level 3 for? Healthcare professionals seeking to enhance their coding skills. Individuals interested in a career in healthcare administration. Medical students or recent graduates. Data analysts and researchers in the healthcare sector. Anyone with an interest in medical coding. Career Path Clinical Coder: £21,000 - £35,000 Medical Records Clerk: £18,000 - £25,000 Health Information Manager: £31,000 - £50,000 Clinical Auditor: £26,000 - £41,000 Coding Trainer or Educator: £30,000 - £45,000 Prerequisites No prior qualifications or experience is required to enrol in our Course. Created by industry professionals, the course is compatible with all PCs, Macs, tablets, and smartphones. As long as you have a stable internet connection, you can access the course from anywhere, at any time. Certification Upon completion of the course material for the Course, you'll have the opportunity to undertake a written assignment test, which can be taken either during or upon completion of the course. Successful completion of the test enables you to claim your PDF certificate at a cost of £4.99. Should you require an original hard copy certificate, it can be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Module 01: Introduction to Clinical Coding Introduction to Clinical Coding 00:44:00 Module 02: Introduction to Clinical Records Its Confidentiality Introduction to Clinical Records and Its Confidentiality 00:51:00 Module 03: Clinical Terminology and Jargons Clinical Terminology and Jargons 00:44:00 Module 04: Introduction to ICD-10 Coding Introduction to ICD-10 Coding 00:34:00 Module 05: General Coding Standards of ICD-10 General Coding Standards of ICD-10 00:44:00 Module 06: ICD-10 5th Edition Codes (Chapter 1 to 4) ICD-10 5th Edition Codes (Chapter 1 to 4) 00:46:00 Module 07: ICD-10 5th Edition Codes (Chapter 5 to 10) ICD-10 5th Edition Codes (Chapter 5 to 10) 01:02:00 Module 08: ICD-10 5th Edition Codes (Chapter 11 to 15) ICD-10 5th Edition Codes (Chapter 11 to 15) 01:00:00 Module 09: ICD-10 5th Edition Codes (Chapter 16 to 22) ICD-10 5th Edition Codes (Chapter 16 to 22) 01:04:00 Module 10: Introduction to OPCS-4 Introduction to OPCS-4 00:48:00 Module 11: Introduction to SNOMED CT Introduction to SNOMED CT 00:41:00 Module 12: Other types of Clinical Coding Other types of Clinical Coding 00:34:00 Module 13: Legal and Ethical Aspects of Working in a Clinical Environment Legal and Ethical Aspects of Working in a Clinical Environment 00:35:00 Assignment Assignment - Medical Coding Certification: Clinical Coding Online Course at QLS Level 3 04:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

In an era awash with data, understanding it is the key to unlocking significant opportunities. Enter the realm of 'SQL For Data Analytics & Database Development'. Dive deep into the heart of data manipulation, exploration, and insight generation. This course unfurls the magic behind SQL, drawing back the curtain on the tools that empower businesses globally. Understanding SQL's profound capabilities opens doors to a world where data-driven decision-making is not just an advantage but an imperative. It isn't simply about data storage. This course unravels the art of analytics, shedding light on how to glean valuable insights from vast data lakes. The path of SQL isn't merely technical; it's the spine of transformative decisions in today's leading industries. Offering a systematic approach to database development, we invite you to embark on this illuminative journey, stitching the threads of raw data into the fabric of meaningful stories. Come harness the power of SQL. Whether your intent is data analytics or the intricate craft of database development, this is your gateway. Let us guide you, from the rudimentary steps to mastering advanced commands, constructing your data narrative, and informing the future. Learning Outcomes: Comprehend the fundamental architecture of SQL and its environment. Acquire proficiency in basic and advanced SQL statements. Understand and implement GROUP BY statements for data aggregation. Master the concepts and applications of JOINS in databases. Cultivate the ability to create and structure databases and tables. Delve into advanced SQL commands, enhancing data manipulation and querying capabilities. Construct efficient database models, fostering optimal data storage and retrieval.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/SQL-DATA-ANALYSIS.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why choose this SQL For Data Analytics & Database Development course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the SQL For Data Analytics & Database Development Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this SQL For Data Analytics & Database Development course for? Aspirants seeking to transition into data-driven roles in various industries. Database administrators aiming to broaden their analytical capabilities. Business analysts eager to enhance their data querying skills. Researchers in need of comprehensive data management tools. Tech enthusiasts wanting to grasp the underpinnings of database systems. Career path Data Analyst - Average salary: £35,000 - £50,000 Per Annum Database Developer - Average salary: £40,000 - £55,000 Per Annum Business Intelligence Analyst - Average salary: £38,000 - £52,000 Per Annum SQL Developer - Average salary: £42,000 - £58,000 Per Annum Database Administrator (DBA) - Average salary: £45,000 - £60,000 Per Annum Data Engineer - Average salary: £47,000 - £63,000 Per Annum Prerequisites This SQL For Data Analytics & Database Development was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Course Introduction Introduction 00:04:00 Course Curriculum Overview 00:05:00 Overview of Databases 00:10:00 SQL Environment Setup MySQL Installation 00:16:00 MySQL Workbench Installation 00:09:00 Connecting to MySQL using Console 00:09:00 SQL Statement Basics Overview of Challenges 00:04:00 SQL Statement Basic 00:16:00 SELECT Statement 00:09:00 SELECT DISTINCT 00:05:00 Column AS Statement 00:12:00 COUNT built-in Method usage 00:11:00 SELECT WHERE Clause - Part One 00:05:00 SELECT WHERE Clause - Part Two 00:11:00 SQL Statement Basic 00:16:00 SQL Limit Clause Statement 00:09:00 SQL Using BETWEEN with Same Column Data 00:11:00 How to Apply IN Operator 00:11:00 Wildcard Characters with LIKE and ILIKE 00:11:00 GROUP BY Statements Overview of GROUP BY 00:06:00 Aggregation function SUM() 00:09:00 Aggregation MIN() and MAX() 00:05:00 GROUP BY - One 00:09:00 GROUP BY - Two 00:12:00 HAVING Clause 00:05:00 JOINS Overview of JOINS 00:04:00 Introduction to JOINS 00:04:00 AS Statement table 00:03:00 INNER Joins 00:14:00 FULL Outer Join 00:11:00 LEFT Outer JOIN 00:08:00 RIGHT JOIN 00:08:00 Union 00:07:00 Advanced SQL Commands / Statements Timestamps 00:12:00 EXTRACT from timestamp 00:10:00 Mathematical Functions 00:12:00 String Functions 00:22:00 SUBQUERY 00:13:00 Creating Database and Tables Basic of Database and Tables 00:06:00 DataTypes 00:10:00 Primarykey and Foreignkey 00:06:00 Create Table in SQL Script 00:13:00 Insert 00:11:00 Update 00:07:00 Delete 00:04:00 Alter Table 00:09:00 Drop Table 00:05:00 NOT NULL Constraint 00:08:00 UNIQUE Constraint 00:09:00 Databases and Tables Creating a Database backup 00:12:00 10a Overview of Databases and Tables 00:05:00 10c Restoring a Database 00:07:00

Embark on a thrilling journey into 'Blockchain & Cryptocurrency.' Explore the revolutionary potential of blockchain technology and unravel the mysteries of popular cryptocurrencies like Bitcoin, Ethereum, and Ripple. Dive deep into the intricacies of this digital landscape, from understanding the fundamentals to navigating the ever-evolving legal and regulatory frameworks. In this course, you'll uncover the essence of blockchain technology and its transformative impact on various industries. From exploring cryptocurrency prices and news to delving into advanced concepts, you'll gain a comprehensive understanding of this dynamic field. Navigate the complexities of blockchain explorer tools and cryptocurrency wallets, equipping yourself with the knowledge to make informed decisions in the cryptocurrency market. By the end of this course, you'll emerge with a solid grasp of blockchain fundamentals and cryptocurrency intricacies. Stay updated with the latest developments in this rapidly evolving field and explore alternative uses of blockchain beyond cryptocurrencies. Whether you're an aspiring investor, tech enthusiast, or curious learner, this course offers invaluable insights into the future of finance and technology. Learning Outcomes: Understand the fundamentals of blockchain technology and its applications. Analyze the characteristics and functionalities of popular cryptocurrencies like Bitcoin, Ethereum, and Ripple. Navigate legal and regulatory considerations surrounding blockchain and cryptocurrency. Explore advanced concepts and alternative uses of blockchain beyond cryptocurrency. Stay updated with the latest developments and updates in the blockchain and cryptocurrency space. Why buy this Blockchain & Cryptocurrency Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the Blockchain & Cryptocurrency 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 Blockchain & Cryptocurrency course for? Investors seeking to understand blockchain and cryptocurrency for investment opportunities. Tech enthusiasts interested in exploring the innovative potential of blockchain technology. Finance professionals looking to expand their knowledge of digital currencies and blockchain applications. Entrepreneurs considering blockchain-based solutions for their business ventures. Students and researchers interested in the intersection of technology, finance, and regulation. Prerequisites This Blockchain & Cryptocurrency does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Blockchain & Cryptocurrency 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 Blockchain Developer: £30,000 - £70,000 Per Annum Cryptocurrency Analyst: £25,000 - £50,000 Per Annum Blockchain Project Manager: £40,000 - £80,000 Per Annum Cryptocurrency Trader: £20,000 - £100,000+ (depending on success) Per Annum Blockchain Consultant: £35,000 - £90,000 Per Annum Cryptocurrency Compliance Officer: £30,000 - £60,000 Per Annum Course Curriculum Section 01: Introduction What Is Blockchain? 00:15:00 Centralised vs Decentralised vs Distributed Systems 00:12:00 Is Blockchain Truly Decentralised and Distributed? 00:08:00 Structure of a Block 00:10:00 What Is a Hash? 00:08:00 What Are Merkle Trees? 00:08:00 What Is a Ledger? 00:06:00 History of Blockchain 00:21:00 Why Use Blockchain? 00:10:00 What Are Cryptocurrencies? 00:09:00 What Is Cryptography? 00:09:00 Section 02: Bitcoin What Is Bitcoin? 00:12:00 Advantages and Disadvantages Compared To Fiat Currency 00:11:00 What Is Bitcoin Mining 00:12:00 What Are Mining Pools/Farms? 00:08:00 What Is A Bitcoin Wallet? 00:06:00 What Is A Bitcoin Exchange? 00:09:00 How Is The Price of Bitcoin Determined? 00:07:00 How to Use Bitcoin? 00:10:00 What Is Bitcoin Cash and How Does It Differ To Bitcoin? 00:11:00 What Is SegWit2x? 00:16:00 Soft Fork vs Hard Fork 00:08:00 Section 03: Ethereum What Is Ethereum & How Does It Differ To Bitcoin? 00:10:00 Advantages and disadvantages compared to Bitcoin 00:10:00 Ethereum vs Ethereum Classic 00:09:00 Section 04: Ripple What Is Ripple & How Does It Differ To Bitcoin? 00:10:00 Advantages and Disadvantages Compared To Bitcoin 00:10:00 Section 05: Other Popular Cryptocurrencies Litecoin 00:06:00 Dash 00:12:00 Monero 00:11:00 Why Should I Just Not Use Bitcoin? 00:09:00 Section 06: Law and Regulation Monetary Policy 00:11:00 Tax Regulations 00:12:00 Illegal Activities 00:10:00 Electronic Fund Transfer Act 00:11:00 Section 07: Other Uses of Blockchain Education 00:15:00 Retail 00:21:00 Health Industry 00:18:00 Business 00:10:00 Governance 00:12:00 Last Will and Testament 00:12:00 Blood Diamonds 00:06:00 Housing 00:15:00 Proof of Ownership/Identity 00:11:00 Data Storage 00:13:00 Section 08: Advanced ICO (Initial Coin Offering) 00:11:00 2007/2008 Crisis 00:18:00 Cypherpunks 00:18:00 History of FIAT Currency 00:13:00 DAO (Decentralised Autonomous Organisations) 00:13:00 Section 09: Updates Bitcoin Update 00:06:00 Ripple Update 00:11:00 Assignment Assignment - Blockchain & Cryptocurrency 00:00:00

Do you want to master the essential mathematical skills for data science and machine learning? Do you want to learn how to apply statistics and probability to real-world problems and scenarios? If yes, then this course is for you! In this course, you will learn the advanced concepts and techniques of statistics and probability that are widely used in data science and machine learning. You will learn how to describe and analyse data using descriptive statistics, distributions, and probability theory. You will also learn how to perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data. You will gain hands-on experience with practical exercises and projects using Python and R. Learning Outcomes By the end of this course, you will be able to: Apply descriptive statistics, distributions, and probability theory to summarise and visualise data Perform hypothesis testing, regressions, ANOVA, and machine learning algorithms to make predictions and inferences from data Use Python and R to implement statistical and machine learning methods Interpret and communicate the results of your analysis using appropriate metrics and visualisations Solve real-world problems and scenarios using statistics and probability Why choose this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 course for? This course is for anyone who wants to learn the advanced concepts and techniques of statistics and probability for data science and machine learning. This course is suitable for: Data scientists, machine learning engineers, and analysts who want to enhance their skills and knowledge Students and researchers who want to learn the mathematical foundations of data science and machine learning Professionals and managers who want to understand and apply data-driven decision making Hobbyists and enthusiasts who want to explore and learn from data Anyone who loves statistics and probability and wants to challenge themselves Career path Data Scientist (£35,000 - £55,000) Machine Learning Engineer (£40,000 - £60,000) Statistician (£35,000 - £55,000) Data Analyst (£40,000 - £60,000) Business Intelligence Analyst (£45,000 - £65,000) Senior Data Analyst (£50,000 - £70,000) Prerequisites This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Statistics & Probability for Data Science & Machine Learning at QLS Level 7 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Section 01: Let's get started Welcome! 00:02:00 What will you learn in this course? 00:06:00 How can you get the most out of it? 00:06:00 Section 02: Descriptive statistics Intro 00:03:00 Mean 00:06:00 Median 00:05:00 Mode 00:04:00 Mean or Median? 00:08:00 Skewness 00:08:00 Practice: Skewness 00:01:00 Solution: Skewness 00:03:00 Range & IQR 00:10:00 Sample vs. Population 00:05:00 Variance & Standard deviation 00:11:00 Impact of Scaling & Shifting 00:19:00 Statistical moments 00:06:00 Section 03: Distributions What is a distribution? 00:10:00 Normal distribution 00:09:00 Z-Scores 00:13:00 Practice: Normal distribution 00:04:00 Solution: Normal distribution 00:07:00 Section 04: Probability theory Intro 00:01:00 Probability Basics 00:10:00 Calculating simple Probabilities 00:05:00 Practice: Simple Probabilities 00:01:00 Quick solution: Simple Probabilities 00:01:00 Detailed solution: Simple Probabilities 00:06:00 Rule of addition 00:13:00 Practice: Rule of addition 00:02:00 Quick solution: Rule of addition 00:01:00 Detailed solution: Rule of addition 00:07:00 Rule of multiplication 00:11:00 Practice: Rule of multiplication 00:01:00 Solution: Rule of multiplication 00:03:00 Bayes Theorem 00:10:00 Bayes Theorem - Practical example 00:07:00 Expected value 00:11:00 Practice: Expected value 00:01:00 Solution: Expected value 00:03:00 Law of Large Numbers 00:08:00 Central Limit Theorem - Theory 00:10:00 Central Limit Theorem - Intuition 00:08:00 Central Limit Theorem - Challenge 00:11:00 Central Limit Theorem - Exercise 00:02:00 Central Limit Theorem - Solution 00:14:00 Binomial distribution 00:16:00 Poisson distribution 00:17:00 Real life problems 00:15:00 Section 05: Hypothesis testing Intro 00:01:00 What is a hypothesis? 00:19:00 Significance level and p-value 00:06:00 Type I and Type II errors 00:05:00 Confidence intervals and margin of error 00:15:00 Excursion: Calculating sample size & power 00:11:00 Performing the hypothesis test 00:20:00 Practice: Hypothesis test 00:01:00 Solution: Hypothesis test 00:06:00 T-test and t-distribution 00:13:00 Proportion testing 00:10:00 Important p-z pairs 00:08:00 Section 06: Regressions Intro 00:02:00 Linear Regression 00:11:00 Correlation coefficient 00:10:00 Practice: Correlation 00:02:00 Solution: Correlation 00:08:00 Practice: Linear Regression 00:01:00 Solution: Linear Regression 00:07:00 Residual, MSE & MAE 00:08:00 Practice: MSE & MAE 00:01:00 Solution: MSE & MAE 00:03:00 Coefficient of determination 00:12:00 Root Mean Square Error 00:06:00 Practice: RMSE 00:01:00 Solution: RMSE 00:02:00 Section 07: Advanced regression & machine learning algorithms Multiple Linear Regression 00:16:00 Overfitting 00:05:00 Polynomial Regression 00:13:00 Logistic Regression 00:09:00 Decision Trees 00:21:00 Regression Trees 00:14:00 Random Forests 00:13:00 Dealing with missing data 00:10:00 Section 08: ANOVA (Analysis of Variance) ANOVA - Basics & Assumptions 00:06:00 One-way ANOVA 00:12:00 F-Distribution 00:10:00 Two-way ANOVA - Sum of Squares 00:16:00 Two-way ANOVA - F-ratio & conclusions 00:11:00 Section 09: Wrap up Wrap up 00:01:00 Assignment Assignment - Statistics & Probability for Data Science & Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview 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? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices 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 Unit 06: Factors 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 Unit 07: Data Frames 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 Unit 08: Lists 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 Unit 09: Relational Operators 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 Unit 10: Logical Operators 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 Unit 11: Conditional Statements 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 Unit 12: Loops 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 Unit 13: Functions 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 Unit 14: R Packages 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 Unit 15: The Apply Family - lapply 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 Unit 16: The apply Family - sapply & vapply 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 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times 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 Unit 20: Getting and Cleaning Data 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 Unit 21: Plotting Data in R 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 Unit 22: Data Manipulation with dplyr 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 Assignment - R Programming for Data Science 00:00:00

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

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