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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

Are you looking to enhance your Tree Surgeon skills? If yes, then you have come to the right place. Our comprehensive course on Tree Surgeon will assist you in producing the best possible outcome by mastering the Tree Surgeon skills. The Tree Surgeon course is for those who want to be successful. In the Tree Surgeon course, you will learn the essential knowledge needed to become well versed in Tree Surgeon. Our Tree Surgeon course starts with the basics of Tree Surgeon and gradually progresses towards advanced topics. Therefore, each lesson of this Tree Surgeon course is intuitive and easy to understand. Why would you choose the Tree Surgeon course from Compliance Central: Lifetime access to Tree Surgeon course materials Full tutor support is available from Monday to Friday with the Tree Surgeon course Learn Tree Surgeon skills at your own pace from the comfort of your home Gain a complete understanding of Tree Surgeon course Accessible, informative Tree Surgeon learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Tree Surgeon Study Tree Surgeon in your own time through your computer, tablet or mobile device. A 100% learning satisfaction guarantee with your Tree Surgeon Course Tree Surgeon Curriculum Breakdown of the Tree Surgeon Course Course Outline: Module 01: Introduction to Horticulture Module 02: Structure and Function of Horticulture Plants Module 03: Growth of Horticulture Plants Module 04: Impact of Temperature Module 05: Impact of Light Module 06: Impact of Soil and Water Module 07: Plant Propagation Module 08: Plant Nutrition Module 09: Harvesting, Training and Pruning Module 10: Growing Plant Indoors Module 11: Ornamental Horticulture and Garden Design Module 12: Cut Floral Design and Landscaping Module 13: Plant Pathology, Entomology and Weed Control Module 14: Permaculture and Arboriculture Module 15: Professional Opportunities in Horticulture Module 16: Biotechnology Applications in Horticulture CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Tree Surgeon course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Tree Surgeon. It is also great for professionals who are already working in Tree Surgeon and want to get promoted at work. Requirements To enrol in this Tree Surgeon course, all you need is a basic understanding of the English Language and an internet connection. Career path Arborist: £20,000 to £40,000 per year Tree Climber: £18,000 to £35,000 per year Tree Consultant: £25,000 to £50,000 per year Tree Inspector: £22,000 to £40,000 per year Urban Forester: £25,000 to £45,000 per year Tree Officer: £28,000 to £50,000 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

Our comprehensive program is meticulously crafted to equip you with the essential skills and knowledge required to thrive in your chosen field. Developed by seasoned professionals with years of industry experience, this course is ideal for those seeking to kickstart their careers or enhance their existing skill set. Featuring an engaging audio-visual presentation and easily digestible modules, our program facilitates a self-paced learning experience. Our dedicated online support team is available on weekdays to provide assistance throughout your journey. Key Learning Outcomes: Grasp the fundamentals and their practical applications. Cultivate the necessary skills for success in your field. Apply newfound knowledge to real-world scenarios. Develop effective solutions for relevant topics. Elevate your employability and career prospects.   Designed to give you a competitive edge in the job market, this course offers lifetime access to materials and the flexibility to learn at your own pace, from the comfort of your home. Why Choose Us? Learn at your own pace with 24/7 online access to course materials. Benefit from full tutor support available Monday through Friday. Acquire essential skills in the convenience of your home through informative video modules. Enjoy 24/7 assistance and advice via email and live chat. Study on your preferred device - computer, tablet, or mobile. Gain a thorough understanding of the course content. Improve professional skills and earning potential upon completion. Access lifetime course materials and expert guidance. Enjoy the convenience of online learning with flexible schedules. Why Enroll in This Course? Our program provides a comprehensive introduction to the subject matter, laying a solid foundation for further study. It empowers students to acquire knowledge and skills applicable to both their professional and personal lives. Assessment: The course incorporates quizzes to evaluate your understanding and retention of the material. These quizzes pinpoint areas for further practice, allowing you to review course materials as needed. Successfully passing the final quiz qualifies you for a certificate of achievement. Career Path: Our course is meticulously designed to equip you for success in your chosen field. Upon completion, you'll have the qualifications to pursue diverse career opportunities across various industries. Course Content Arboriculture - Tree Biology & Planting Techniques Module 1: Introduction to Arboriculture Module 2: Tree Biology and Physiology Module 3: Tree Identification and Taxonomy Module 4: Tree Health and Assessment Module 5: Tree Pruning and Maintenance Module 6: Advanced Tree Care Techniques Module 7: Tree Planting and Establishment Module 8: Urban Forestry and Planning

This course aims to teach you how to use Python for machine learning and data science.

Take on a transformative journey in arboriculture, where you'll delve into the intricate world of trees and their management. This course isn't just about learning the basics; it's about mastering techniques crucial for sustainable arboriculture practices. As urban spaces expand, the demand for skilled arborists grows exponentially. Understanding tree biology, pruning techniques, and disease management is essential for maintaining green spaces. By mastering arboriculture, you'll be equipped to tackle challenges like tree selection, planting, and maintaining soil health for optimal growth. Not only does this knowledge enhance your daily life by fostering a deeper connection with nature, but it also opens doors to lucrative career opportunities, particularly in the UK where the demand for certified arborists is high. With a median salary ranging from £20,000 to £35,000 per annum, the financial rewards are substantial. The sector is rapidly expanding, with a projected increase of 8% in job opportunities over the next decade. So, seize the opportunity to carve a flourishing career path in arboriculture, where your skills will be in high demand, shaping a greener and more sustainable future for generations to come. Key Features: CPD Certified Foundations of Arboriculture Course Free Certificate from Reed CIQ Approved Foundations of Arboriculture Course Developed by Specialist Lifetime Access Course Curriculum Module 01: Introduction to Arboriculture Module 02: Tree Planting Techniques Module 03: Tree Selection for Arboricult Module 04: Tree Biology Module 05: Soil and Tree Growth Module 06: Pruning Trees Module 07: Tree Diseases and Management Module 08: Arboriculture Equipments and Operations Module 09: Workplace Health and Safety Learning Outcomes: Understand tree biology, fostering optimal growth and development. Implement effective tree planting techniques for thriving arboreal ecosystems. Identify and manage tree diseases, safeguarding arboreal health and vitality. Navigate soil dynamics to promote robust tree growth and sustainability. Execute precise pruning methods to enhance tree aesthetics and health. Operate arboriculture equipment proficiently, ensuring efficient tree care practices. CPD 10 CPD hours / points Accredited by CPD Quality Standards Foundations of Arboriculture: Techniques, Safety, and Management 2:41:36 1: Module 01: Introduction to Arboriculture Preview 14:01 2: Module 02: Tree Planting Techniques 09:34 3: Module 03: Tree Selection for Arboricult 16:22 4: Module 04: Tree Biology 20:04 5: Module 05: Soil and Tree Growth 21:04 6: Module 06: Pruning Trees 17:50 7: Module 07: Tree Diseases and Management 22:15 8: Module 08: Arboriculture Equipments and Operations 18:31 9: Module 09: Workplace Health and Safety 20:55 10: CPD Certificate - Free 01:00 Who is this course for? This Foundations of Arboriculture course is accessible to anyone eager to learn more about this topic. Through this course, you'll gain a solid understanding of Foundations of Arboriculture. Moreover, this course is ideal for: Aspiring arborists seeking comprehensive knowledge in tree care techniques. Landscapers aiming to expand their expertise into tree management. Environmental enthusiasts passionate about preserving arboreal ecosystems. Gardeners looking to elevate their understanding of tree biology and care. Horticulture professionals keen on mastering advanced tree care practices. Requirements There are no requirements needed to enrol into this Foundations of Arboriculture course. We welcome individuals from all backgrounds and levels of experience to enrol into this Foundations of Arboriculture course. Career path After finishing this Foundations of Arboriculture course you will have multiple job opportunities waiting for you. Some of the following Job sectors of Foundations of Arboriculture are: Certificates Digital certificate Digital certificate - Included Reed Courses Certificate of Completion Digital certificate - Included Will be downloadable when all lectures have been completed.

Embark on a journey of creativity and sustainability with our Garden Design & Planning course. Learn the art of garden aesthetics, practical planting techniques, and maintenance strategies to transform any space into a thriving, beautiful garden. Ideal for aspiring garden designers and enthusiasts.

Dive into the enriching world of Gardening and Horticulture. From landscaping design to hydroponics, plant nutrition, and pest management, this course offers comprehensive knowledge and practical skills. Unearth opportunities for a career in this green and growing field.

Dive into the enriching world of Gardening and Horticulture. From landscaping design to hydroponics, plant nutrition, and pest management, this course offers comprehensive knowledge and practical skills. Unearth opportunities for a career in this green and growing field.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Hands-on Predicitive Analytics with Python (TTPS4879) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.