442 Algorithm courses

Embark on a riveting journey from ChatGPT novice to maestro with our 'ChatGPT Masterclass: A Complete ChatGPT Zero to Hero!' This isn't just a course; it's your passport to mastering the intricacies of ChatGPT. In the initial sections, we handhold you through the basics, ensuring a solid foundation. As you progress, delve into the world of developers, discovering how ChatGPT can be harnessed for coding marvels. But this course isn't limited to tech whizzes; entrepreneurs can scale their business using the prowess of ChatGPT in Section 04. For students, Section 05 unveils the academic wonders of ChatGPT, while Section 08 ventures into artistic realms with Dall-E 2. Brace yourself for a transformative experience as you explore the power of ChatGPT across diverse domains, from Excel to graphic art. Learning Outcomes Master the fundamentals of ChatGPT, progressing from the basics to advanced applications. Harness ChatGPT for coding and development, unlocking its potential for developers. Scale your business using ChatGPT, understanding its applications in entrepreneurship. Explore academic applications, discovering how ChatGPT enhances student learning. Unleash the artistic side of ChatGPT, creating graphic art with Dall-E 2. Why choose this ChatGPT Masterclass: A Complete ChatGPT Zero to Hero 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 ChatGPT Masterclass: A Complete ChatGPT Zero to Hero course for? Aspiring ChatGPT enthusiasts eager to transition from zero to hero. Developers seeking to integrate ChatGPT into their coding repertoire. Entrepreneurs aiming to leverage ChatGPT for business growth. Students exploring the academic applications of conversational AI. Creatives and graphic artists interested in the artistic possibilities of ChatGPT. Career path Conversational AI Developer: £50,000 - £80,000 Entrepreneurial AI Strategist: £60,000 - £90,000 AI-enhanced Education Specialist: £45,000 - £70,000 Creative AI Artist: £40,000 - £60,000 AI Solutions Architect: £55,000 - £85,000 Innovative Tech Entrepreneur: £70,000 - £100,000 Prerequisites This ChatGPT Masterclass: A Complete ChatGPT Zero to Hero! does not require you to have any prior qualifications or experience. You can just enrol and start learning.This ChatGPT Masterclass: A Complete ChatGPT Zero to Hero! 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 Section 01: Getting Started Introduction 00:04:00 Start on Windows, macOS, and Linux 00:01:00 How to ask great questions 00:02:00 FAQs 00:01:00 Section 02: ChatGPT - Basic What is ChatGPT 00:05:00 Create a ChatGPT account 00:06:00 How to use ChatGPT 00:10:00 ChatGPT for day-to-day activities 00:04:00 Advanced ChatGPT Plus 00:05:00 Section 03: ChatGPT for Developers ChatGPT for programmers 00:12:00 Improve Problem-solving skills 00:06:00 Create an Algorithms 00:06:00 How to build a website with ChatGPT 00:05:00 Develop a Stunning Landing page for product sales 00:07:00 Create a Documentation 00:03:00 Code Debugging with ChatGPT 00:05:00 Section 04: Build, and Scale your Business Using ChatGPT The Best Businesses Ideas to start with ChatGPT 00:05:00 SEO Basics for your website 00:06:00 How to make an online course using ChatGPT 00:05:00 Selling Competitive products with ChatGPT 00:04:00 Exercise on real-world sales query 00:01:00 Solution for an exercise 00:02:00 ection 05: ChatGPT for Students ChatGPT to Prepare Resume 00:03:00 Interview preparation with ChatGPT 00:05:00 ChatGPT for PowerPoint content 00:03:00 Innovative Job Searching using ChatGPT 00:04:00 Write a short film with ChatGPT for Creative Fiction and Screenplays 00:03:00 Section 06: The Power of ChatGPT Make the best diet plan for a day 00:03:00 Suggest a meal plan with seafood as the special ingredient 00:03:00 Write a Business Email for the franchise 00:03:00 Create Legal documents like sale deeds etc. 00:03:00 Section 07: ChatGPT for Excel professionals Sum with ChatGPT 00:05:00 VLOOKUP with ChatGPT 00:05:00 Section 08: Generate Incredible Graphic Art with Dall-E 2 Introduction to Dall-E 2 00:04:00 Dall-E 2 Creating 3D Graphic design 00:03:00 Dall-E 2 Deep Dive in Editing your own image 00:04:00 How to Make Money with Dall-E 2 00:03:00 Section 09: The Best Tools and Extensions using ChatGPT Integrating ChatGPT with Google Search 00:06:00

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics 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 Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics 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 Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

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

Isn't it interesting that you searched for something on the internet and some relevant results appeared? Alternatively, you can enter your daily data into a health app that automatically recommends a diet and exercise routine for you. All of this would not have been possible without data science. The modern world is entirely dependent on Machine Learning, Artificial Intelligence, Neural networks or data science in one phrase. Data science is a new field with no established leaders. It's too difficult to decide which one to learn, which leads to even more frustration because you can't make any progress. It is becoming more important, but the market for skilled data scientists is limited and competitive. What if you are one of those individuals? If you have a background in maths or statistics, we have good news: you can become a data scientist with little training! Anyone can become a data scientist with the help of our Data Science courses. Whatever your background, this training will teach you how to analyse and interpret data to generate new insights that lead to better decisions and results. Our interactive materials set us apart and make us more effective for our students. So don't be late to take your place. Enrol now! Learning Outcomes Understanding of the basic concepts and techniques in data science, such as data exploration, cleaning, and preprocessing Knowledge of statistical analysis methods, including hypothesis testing, regression analysis Learn probability theory and it's use in Data science Knowledge of Advanced regression & machine learning algorithms Ability to communicate data science results effectively to a non-technical audience. Key Highlights for Data Science Course: Developed by industry experts Instant e-certificate and hard copy dispatch by the next working day Interactive course with audio voice-over 24/7 Learning Assistance Lifetime access & update without any limits Unlimited Retake Exam and premium support for life Easy Accessibility to the Course Materials- Anytime, Anywhere - From Any Smart Device (Laptop, Tablet, Smartphone Etc.) 100% Learning satisfaction guarantee Covers to explore multiple job positions One-stop solution for entrepreneurs and Jobseekers Fastest growing sector Boost your salary on program completion Learn from diligent experts Expert-verified response for quality education So, You should not wait too long. Now is the time to enrol! Learn at your own pace from the comfort of your home, as the rich learning materials of this course are accessible from any place at any time. The curriculums are divided into tiny bite-sized modules by industry specialists. And you will get answers to all your queries from our experts. So, enrol and excel in your career with Compliance Central. Curriculum Breakdown of the Course Section 01: Let's get started Section 02: Descriptive statistics Section 03: Distributions Section 04: Probability theory Section 05: Hypothesis testing Section 06: Regressions Section 07: Advanced regression & machine learning algorithms Section 08: ANOVA (Analysis of Variance) Section 09: Wrap up CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this course. Requirements To enrol in this Data Science course, all you need is a basic understanding of the English Language and an internet connection. Career path After completing this course, you can explore trendy and in-demand jobs related to Data Science, such as- Data Analyst: £25,000 to £45,000 per year Data Scientist: £35,000 to £60,000 per year Business Intelligence (BI) Analyst: £30,000 to £50,000 per year Machine Learning Engineer: £40,000 to £70,000 per year Data Engineer: £35,000 to £60,000 per year Data Consultant: £45,000 to £75,000 per year Certificates CPD Accredited Hard Copy Certificate Hard copy certificate - Included CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: £3.99 each Outside of the UK: £9.99 each CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate

Become a Python developer and build a rewarding career in tech. Python is one of the most popular and in-demand programming languages in the world. Python is used by companies of all sizes, from startups to Fortune 500 companies, to develop a wide range of applications, including web applications, data science tools, and machine learning algorithms. The demand for Python developers is rising rapidly in the UK, with job postings for Python developers increasing by 22% in the past year. The average salary for a Python developer in the UK is £65,000, making it one of the highest-paid programming languages. Our Python Programming - Beginner to Advanced course will teach you everything you need to know to become a Python developer. You will learn the fundamentals of Python programming, as well as more advanced topics such as object-oriented programming, data structures, and algorithms. You will also learn how to use popular Python libraries and frameworks, such as Django and NumPy. Why would you choose the Python Programming course from Compliance Central: Lifetime access to Python Programming course materials Full tutor support is available from Monday to Friday with the Python Programming course Learn Python Programming skills at your own pace from the comfort of your home Gain a complete understanding of Python Programming course Accessible, informative Python Programming learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Python Programming Study Python Programming in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Python Programming course Python Programming Curriculum Breakdown of the Python Programming Course Section 01: Introduction & Getting Started Section 02: Downloading and Installing Python Editor Section 03: Getting Started Section 04: Variables and Basic Data Types in Python Section 05: Comments Section 06: Input Section 07: Exercise - Build a Program to Say Hello Section 08: Exercise - Build a Simple Calculator Section 09: Conditional Statements Section 10: Loops - For Loop Section 11: Loops - While Loop Section 12: Exercise - Building a Username Password App. Python Programming - Beginner to Advanced Course Learning Outcomes: Familiarise with Python's core principles and setup. Understand fundamental data types and variable operations in Python. Recognise the significance and application of comments in Python. Master the art of obtaining and processing user input in Python. Employ conditional structures with proficiency. Navigate confidently within both "For" and "While" loops. Conceptualise and draft rudimentary Python applications. Certificate of Achievement After successfully completing this Python course, you can get a digital and a hardcopy certificate for free. The delivery charge of the hardcopy certificate inside the UK is £3.99 and international students need to pay £9.99 to get their hardcopy certificate. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Python Programming course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Python Programming. It is also great for professionals who are already working in Python Programming and want to get promoted at work. Requirements To enrol in this Python Programming course, all you need is a basic understanding of the English Language and an internet connection. Career path The Python Programming course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Python Programming. Python Developer: £35,000 to £70,000 per year Data Analyst (Python): £30,000 to £55,000 per year Software Engineer (Python): £40,000 to £75,000 per year Machine Learning Engineer: £45,000 to £80,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

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

Overview Join our Bioinformatics course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Bioinformatics course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Bioinformatics course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! You Will Learn Following Things: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers everything you must know to stand against the tough competition. The future is truly yours to seize with this Bioinformatics. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-to-one support from a dedicated tutor throughout your course. Study online - whenever and wherever you want. Instant Digital/ PDF certificate 100% money back guarantee 12 months access This course covers everything you must know to stand against the tough competition. The future is truly yours to seize with this Bioinformatics. Enrol today and complete the course to achieve a certificate that can change your career forever. Process of Evaluation Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo. Certificate of Achievement After completing the Bioinformatics course, you will receive your CPD-accredited Digital/PDF Certificate for £5.99. To get the hardcopy certificate for £12.99, you must also pay the shipping charge of just £3.99 (UK) and £10.99 (International). Who Is This Course for? This Bioinformatics is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Bioinformatics course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career path The certification and skills you get from this Bioinformatics Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Module 01: Introduction to Bioinformatics Introduction to Bioinformatics 00:10:00 Module 02: Topics in Computational Genomics Topics in Computational Genomics 00:10:00 Module 03: Algorithms in Computational Biology Algorithms in Computational Biology 00:10:00 Module 04: Applied Bioinformatics Tools Applied Bioinformatics Tools 00:10:00 Module 05: Structure and Function of Proteins Structure and Function of Proteins 00:10:00 Assignment Assignment - Bioinformatics 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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