196 Probability courses

This course is designed for beginners, although we will go deep gradually, and is a highly focused course designed to master your Python skills in probability and statistics, which covers the major part of machine learning or data science-related career opportunities.

Statistics and Probability are a part of everyday life that we all have to master, not only because you might use it to analyse data but also because it can improve your understanding of the world through using numbers and other quantitative data. The primary purpose of the Statistics and Probability course is to help you in knowledge provision, probability calculation, record keeping and improved decision-making. This course will cover topics such as central tendency, measures dispersion, correlation, regression analysis, probability, and sampling. You will also be adept in hypothesis testing and interpretation of data through charts and graphs. Take this Statistics and Probability course to enhance your competency and facilitate your career growth. Learning Outcome * Study essential concepts of statistical analysis. * Learn how to test hypotheses to improve your forecasts. * Study dispersion, sampling, and probability * Become familiar with correlation and regression analysis * Know about common statistical mistakes and how to avoid them What will Make You Stand Out? On completion of this Statistics and Probability online course, you will gain: * CPD QS Accredited course * After successfully completing the Course, you will receive a FREE PDF Certificate as evidence of your newly acquired abilities. * Lifetime access to the whole collection of learning materials. * Enroling in the Course has no additional cost. * 24x7 Tutor Support * You can study and complete the course at your own pace. Course Curriculum Statistics and Probability * Module 01: Introduction to Statistics * Module 02: Measuring Central Tendency * Module 03: Measures of Dispersion * Module 04: Correlation and Regression Analysis * Module 05: Probability * Module 06: Sampling * Module 07: Charts and Graphs * Module 08: Hypothesis Testing * Module 09: Ten Common Statistical Mistakes Show off your new skills with a certificate of completion. After successfully completing the course, you can order your CPD Accredited Certificates as proof of your achievement absolutely free. Please Note: The delivery charge inside the U.K. is £4.99, and international students have to pay £8.99. CPD 10 CPD hours / points Accredited by CPD Quality Standards WHO IS THIS COURSE FOR? Is This Course the Right Option for You? This Statistics and Probability course is open to everybody. You can access the course materials from any location in the world and there are no requirements for enrolment. REQUIREMENTS Without any formal requirements, you can delightfully enrol in this Statistics and Probability course. Just get a device with internet connectivity and you are ready to start your learning journey. Thus, complete this course at your own pace. CAREER PATH The aim of this exclusive Statistics and Probability course is to help you toward your dream career. So, complete this course and enhance your skills to explore opportunities in relevant areas.

Course Overview Lean Six Sigma is a proven combination of tools and techniques that has been used by leading organizations to improve efficiency, productivity and customer satisfaction. It achieves this by providing a rigorous and structured methodology and team approach to problem solving which leads to quality and performance improvements. Our Lean Six Sigma Black Belt workshop is an eight (8) day programme designed to develop Lean Six Sigma Green Belts into Black Belts, qualifying them to become agents of change within an organization, enhancing their current skills, by developing a thorough understanding of the DMAIC methodology and its applications, to manage a culture of problem solving and continuous improvement in your organization. It therefore allows key personnel to support your company’s larger goals and objectives. It is suited to those who will have a company-wide role in Six Sigma, including the deployment of the methodology, project selection work, and leadership responsibilities. The course uses a blend of theory and practical exercises to ensure that delegates have the confidence and capability to identify opportunities for improvement and lead in the delivery of more complex business improvement projects and transformations.  Black Belts can develop individual projects, or they can engage in a macro Black Belt project which can incorporate several Green Belt projects as support. The tools acquired during training will enable them to solve more challenging problems and use team dynamics to lead improvement teams towards the implementation of change within the organization. Key topics covered at Green Belt level are refreshed, focusing on how to use data to pinpoint processes that need to be analysed and improved using the Six Sigma Tool sets, with a view to problem solving, increasing operational efficiency, improving productivity and customer satisfaction and the company’s overall business results. In addition, subjects dealt with in the Black Belt course include project mandate preparation, team leadership and facilitation techniques, as well as project management skills. On the data analysis side, Statistical analysis plays a major part of this course. Means to deal with non-normal data are considered, there are also sections on probability, the binomial and Poisson distributions, and multiple factor analysis. Design of experiments is also considered – this is a structured approach to experimentation to help determine which inputs are important in a process.  Our Lean Six Sigma Black Belt programme incorporates a project to be undertaken in your own organization during and after the training modules. This allows you to apply the tools, in your own working environment, to processes that are known to you, making the training relevant, and also leaving a improvement with measurable results in your organization. MINITAB (trial version can be downloaded free) and Excel software are used by participants during the training sessions and to complete their projects. Structure of the Course This 8-day training programme is divided into three modules as follows:  * Define / Measure Phase - 3 days from April 8th to 10th,  2024 * Analyse Phase - 3 days on May 13th to 15th, 2024 * Improve / Control Phase - 2 days on June 17th & 18th, 2024 A gap of 4 weeks between each module provides an opportunity for trainees to work on a project within their workplace, applying the methodology and tools learned during the previous module. Extra support can be provided between modules for each trainees with their project work. We provide a Lean Six Sigma Black Belt Manual for all delegates, and a Certification is awarded upon completion of the Black Belt training and ONE project by each trainee in which the targeted outcomes have been achieved. An outcome report and/or project presentation which demonstrates the use of the tools and methodology is required. Cost: £2,200 + VAT per person. What is included * Eight days of face-to-face training delivered in 3 modules as detailed above * Project review and support for all participants during modules 2 & 3.  * Remote support available for the duration of the programme for trainees to consult with the trainer. * All training material, and a Lean Six Sigma Black Belt Manual for all delegates * Refreshments and lunch provided each day of training * Free car park for all delegates * Lean Six Sigma Black Belt certificate In-house Option This workshop can also be delivered in-house as a stand-alone training workshop or integrated into wider improvement activities. Contact us for more details at compete@cforc.org and we will be happy to discuss in the context of your own business needs. If you are not yet a member but are already thinking about joining CforC, you can find more information on how to become a member and the benefits by clicking here [http://www.cforc.org/join-us].

A code-oriented interactive course that will help you build a solid foundation that is essential to excel in all areas of computer science, specifically data science and machine learning. We will apply all concepts through code and focus on the concepts that are more useful for data science, machine learning, and other areas of computer science.

COURSE OVERVIEW Discover how to become a data scientist, prove hypotheses, and build complex algorithms with this advanced course on Statistics & Probability for Data Science & Machine Learning. This intuitive training will empower you to manipulate records and understand how to break down the most complex processes in this fascinating field.           This comprehensive Data Science tutorial delivers the ideal way to learn the methodology and principles needed to excel in this sector. You will be given expert tuition in using all the relevant concepts for analysing information, gain a genuine understanding of these concepts, and attain the skills to excel in appropriate IT commercial industries. Complete this training, and you will have a unique advantage to work in such areas as automobile design, banking service, media forecasting, and much more. This best selling Statistics & Probability for Data Science & Machine Learning has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Statistics & Probability for Data Science & Machine Learning is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Statistics & Probability for Data Science & Machine Learning is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Statistics & Probability for Data Science & Machine Learning is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Statistics & Probability for Data Science & Machine Learning, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Statistics & Probability for Data Science & Machine Learning will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Statistics & Probability for Data Science & Machine Learning to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

OVERVIEW This comprehensive course on Statistics & Probability for Data Science & Machine Learning will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Statistics & Probability for Data Science & Machine Learning comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. HOW WILL I GET MY CERTIFICATE? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. WHO IS THIS COURSE FOR? There is no experience or previous qualifications required for enrolment on this Statistics & Probability for Data Science & Machine Learning. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Statistics & Probability for Data Science & Machine Learning is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. CAREER PATH Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- * Open doors of opportunities * Increase your adaptability * Keep you relevant * Boost confidence And much more! COURSE CURRICULUM 10 sections • 89 lectures • 11:27:00 total length •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 •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 •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 •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 •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 •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 •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 •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 •Wrap up: 00:01:00 •Assignment - Statistics & Probability for Data Science & Machine Learning: 00:00:00

Start your data science journey with this carefully constructed comprehensive course and get hands-on experience with Python for data science. Gain in-depth knowledge about core Python and essential mathematical concepts in linear algebra, probability, and statistics. Complete data science training with 13+ hours of content.

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? 1. Unlimited access to the course for a lifetime. 2. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. 3. Structured lesson planning in line with industry standards. 4. Immerse yourself in innovative and captivating course materials and activities. 5. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. 6. Flexibility to complete the Course at your own pace, on your own schedule. 7. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. 8. 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

This course for absolute beginners provides you with the opportunity to systematically learn core statistical and probability concepts, descriptive statistics, hypothesis testing, regression analysis, analysis of variance (ANOVA), and advanced regression/ML methods such as logistics regressions, polynomial regressions, decision trees, and more.

OVERVIEW -------------------------------------------------------------------------------- This training course is structured around the ISO 31000:2009 framework, principles and processes. It will also demonstrate how to develop internal control mechanisms and explain how to measure risk in terms of probability and potential impact, at the same time as ensuring that the organisation complies with increasingly strict international standards of corporate governance.