329 Linear courses

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms. Course Outline: Supervised Machine Learning: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting Reinforcement learning Algorithms: Q-Learning Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: Python Machine Learning Certificate on completion Python Machine Learning notes Practical Python Machine Learning exercises and code examples After the course, 1 free, online session for questions or revision Python Machine Learning. Max group size on this Python Machine Learning is 4. Refund Policy No Refunds

Welcome to the Bootcamp course. You will obtain a firm understanding of machine learning with this course. By doing so, you will be able to develop machine learning solutions for various challenges you might encounter and be prepared to start using machine learning at work or in technical interviews.

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python 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! This Data Science & Machine Learning with Python Course will help you to learn: 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 the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. 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. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python 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 You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python 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 Data Science & Machine Learning with Python 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 Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

In this course, we will process massive streams of real-time data using Spark Streaming and create Spark applications using the Scala programming language (v2.12). We will also get our hands-on with some real live Twitter data, simulated streams of Apache access logs, and even data used to train machine learning models.

Quality Guarantee: Promising training excellence, satisfaction gurantee Accredited by: CPD UK & Quality License Scheme Tutor Support: Unlimited support via email, till you complete the course Recognised Certification: Accepted by thousands of professional bodies Start Anytime: With 1 year access to the course materials Online Learning: Learn from anywhere, whenever you want This course will help you understand the basics of project management, how to design a plan for effective project management and identify the potential factors that may affect its execution. This course at a glance Accredited by CPD UK Endorsed by Quality Licence Scheme Understand the fundamentals of project management Demonstrate how to initiate a project Know how to design a plan for effective project management Identify the reasons why a project may fail or go wrong Know how to plan a project by working with the project team Understand how to lead a project management team Recognise the goals and objects of your project Understand the boundaries and scope of your project Recognise the tools for creating the Gantt chart and the linear responsibility chart Know how to perform risk analysis and use strategies to manage risks Know how to manage the project's progress Gain knowledge on how to close a project Why Project Management Training Course right for you? This Project Management Training Course is ideal for those who want to learn how to manage a whole project on their own. Project managers or aspiring project managers who want to refresh their credentials and develop their skills can also take this project management course online. This project management training online course discusses stages of project management in detail, such as the definition stage, planning stage, delivery stage, and closure stage. You will gain knowledge about work breakdown structure and tools for creating the Gantt chart and the linear responsibility chart, with this online project management course. You will also learn about the risk management process, including risk analysis, risk register and risk management strategies. Upon successfully completing this Project Management Training Course, you will be equipped with essential project management skills and knowledge to manage and handle a project easily. You can also contact us for more information. Project Management Training Course Details Accredited by CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field.   The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Course Curriculum Project Management Fundamentals: Know the Principles and Get It Right What is a Project The Four Stage Project Lifecycle Project Stages and Boundaries One Reason Why Projects Go Wrong Terminology Used in the Project Stages More on Project Gateways / Stage Gates Project Definition Stage: the Vital Foundation to Your Success Define Your Project: Goals and Objectives Understanding Project Scope Dealing With Scope Creep Project Definition: Summary Project Planning Stage: Failing to Plan = Planning to Fail The Book of the Plan The Stakeholder Engagement Process Stakeholder Analysis Milestones Are Your Best Friends The Work Breakdown Structure The Gantt Chart Tools for Creating a Gantt Chart The Linear Responsibility Chart (Lrc) Aka the Raci Chart The Risk Management Process Risk Analysis The Six Strategies for Managing Risks The Risk Register (or Risk Log) Project Delivery Stage: Don't You Love It When a Plan Comes Together The Four Essentials of Leading Your Team Project Delivery - the Three Key Cycles Project Closure Stage: Deep Sigh - You're Nearly Done Closing Your Project in an Orderly Manner Closing Words Who should take this course? This Project Management Training Course is primarily aimed at: Project managers Team leaders Project team members Aspiring project managers Beginners in project management Anyone looking to enhance their project management skills However, this course is not restricted to any single profession or field of work. This course can also benefit anyone who wants to learn more about project management in order to handle their own projects.. Entry Requirements There are no academic entry requirements for this Project Management Training Course, and it is open to students of all academic backgrounds. However, you are required to have a laptop/desktop/tablet or smartphone and a good internet connection. Assessment Method This Project Management Training Course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Check out our Leadership & Management Training Diploma Course and gain the skills required to become a successful leader. Certification Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35. FAQs What is a project management training course? A project management course online teaches you to be responsible for handling projects within a limited time frame and budget in an organisation. This course helps you to meet deadlines, manage your budget and achieve goals. Why Should I Do this Course Online? This project administrator course will enhance your work quality and help you achieve goals faster, learn about budgets, meet more deadlines, etc. Where can I work after doing this course? You can work in many places, such as: in the construction industry, IT, healthcare, finance and more. These organisations have posts like project coordinator, program manager and more, and these posts require people with project management skills. How much does a project manager earn in the UK? A project manager earns £52,144 per year on average. However, it may vary depending on places, company and country. Is a Project Manager job a high demand in the UK? YES, The project manager job has a high- demand in the UK and worldwide. Many organisations are paying handsome compensation for doing this job. How will I purchase this course? First, select your desired course plan among the multiple existing course plans on the right side of your screen, then select the payment type, and once you made the payment, you can access the course any time you want. I made my payment. How will I get access to this trainig course? A confirmation email will be sent to your registered email after payment. Hereafter anytime, you can start your learning journey with Lead Academy. I am from outside the UK. Will I get access to the Course? Yes, you can. Since it is an e-learning course, anyone from anywhere can enrol in our courses. Can I pay after completing the course? Paying after completing the course is not an option. However, you do have the opportunity to pay in instalments during the checkout process. Why should I do a CPD accredited course? CPD refers to Continuing Professional Development, and the CPD-accredited course is developed for individuals who want to continuously improve and update their skills within their professional field continuously. This certificate claims that the certificate holder's knowledge is up-to-date in their work area.

Why Choose Character Animation in 3ds Max Training Course? Click here for more info. Top character animation course in 3ds Max, this course provides an accessible learning experience. Learning character animation enables you to create your own short films. It's not just a means of income; it evolves into a passion.  Duration: 20 hrs Method: 1-on-1, Personalized attention. Schedule: Tailor your own hours of your choice, available from Monday to Saturday between 9 am and 7 pm. Enroll in our exclusive "Character Animation Fundamentals in 3ds Max" course at London Design Training, guided by experienced tutors Sitwat Ali, Qasim Ali, and Jess. Gain in-depth insights into animating 3D characters, covering essential techniques like character rigging, pose creation, and seamless pose-to-pose animation. 3ds Max Character Animation Course Duration: 20 hours Course Overview: Master the art of character animation in 3ds Max with our comprehensive course. Ideal for beginners and those with some 3D modeling and animation experience, this course covers everything you need to know to bring characters to life. Course Outline: Introduction to Character Animation Explore animation principles Get familiar with 3ds Max animation tools Learn to create character rigs and manage the timeline Basic Animation Principles Understand keyframes and animation cycles Apply the 12 principles of animation Work with the graph editor and ease-in/out techniques Advanced Animation Techniques Utilize the reaction manager for complex animations Master non-linear animation methods Animate with inverse kinematics, custom controllers, expressions, and scripts Creating Characters Craft a character model with proper topology Create UV maps and apply textures Prepare characters for rigging Facial Animation Learn facial animation principles Create blend shapes and morph targets Master lip syncing techniques Body Animation Animate walk cycles and character motion Achieve believable character poses Implement character physics Advanced Character Animation Work with motion capture data Use CAT and Biped tools Understand motion blur and create special effects Render and output animations Character Animation Projects Bring all skills together in practical projects Create basic and complex character animations Course Requirements: Computer with 3ds Max installed Basic computer operations knowledge Passion for character animation Course Goals: Upon completion, you'll have a thorough grasp of character animation in 3ds Max, capable of creating realistic and sophisticated character animations using advanced techniques. You'll be equipped with the skills to continue honing your character animation abilities independently.

About Course Master the statistical skills you need to understand and analyze biomedical research data with this Biostatistics Online Course Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods.Biostatistics Online Course modules: Module 1: Introduction to Biostatistics This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. Module 2: Probability This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. Module 3: Descriptive Statistics This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. Module 4: Inferential Statistics This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. Module 5: Regression Analysis This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. Module 7: Statistical Software and Tools This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. Module 8: Ethical Considerations and Reporting Guidelines This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing. Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics. Enroll today and start your journey to becoming a biostatistics expert! To find more course in this topic, search more . What Will You Learn? Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively Course Content Introduction to Biostatistics Introduction to Biostatistics Probability Module 2 Probability Descriptive Statistics Descriptive Statistics Inferential Statistics Inferential Statistics Regression Analysis Regression Analysis Biostatistics Tools Biostatistics Tools Statistical Software and Tools Statistical Software and Tools Ethical Considerations and Reporting Guidelines Ethical Considerations and Reporting Guidelines A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics

Python Data Analytics boot camp. 12 1 day lessons, learn Python Basics through to machine learning and front-ends. With practical project to give you full confidence and credibility.

Dive into the enthralling world of numbers and equations with 'High School Math (Pure Mathematics 1),' a course designed to unravel the mysteries of mathematics. Your journey begins with an Introduction that lays the foundation, not just in terms of concepts but igniting a passion for the beauty of math. As you progress, Functions become more than just equations; they turn into a language that describes the universe. Imagine the elegance of Quadratic Equations unfolding before your eyes, revealing patterns and solutions that were once hidden. Embark on an adventure through Co-ordinate Geometry, where every point and line tells a story of space and dimensions. Sequence and Series will no longer be just about numbers; they will be about the rhythm and flow of mathematical logic. The course takes a deeper dive with the Binomial Theorem, Differentiation, Tangents and Normals, each module building on the last, turning complexity into simplicity. Stationary Points & Curve Sketching, and the Second Derivative Test open new vistas in understanding the nature of graphs. As you master Simultaneous Linear Equations, you're not just solving problems; you're unlocking a new perspective on mathematical relationships. The Essential Revision at the end is your bridge to excellence, consolidating your knowledge and skills. Learning Outcomes Develop a foundational understanding of key mathematical concepts and functions. Master the intricacies of quadratic equations and co-ordinate geometry. Explore and apply the principles of sequences, series, and the binomial theorem. Gain proficiency in differentiation and its practical applications in tangents and normals. Understand and implement techniques in curve sketching, stationary points, and optimisation. Why choose this High School Math (Pure Mathematics 1) 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 High School Math (Pure Mathematics 1) course for? High school students seeking to excel in mathematics. Individuals preparing for college-level math courses. Math enthusiasts looking to deepen their understanding of pure mathematics. Students requiring a comprehensive revision of key mathematical concepts. Anyone aspiring to pursue a career involving advanced mathematics. Career path Mathematician: £30,000 - £60,000 Data Analyst: £25,000 - £50,000 Actuarial Analyst: £28,000 - £55,000 Research Scientist (Mathematics): £32,000 - £60,000 Engineering Consultant: £27,000 - £55,000 Academic Tutor (Mathematics): £24,000 - £40,000 Prerequisites This High School Math (Pure Mathematics 1) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This High School Math (Pure Mathematics 1) 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 Introduction Introduction 00:03:00 Functions What is Function? 00:07:00 Vertical Line Test 00:04:00 Value of a Function Graphically 00:08:00 Domain Range of a function Algebraically 00:13:00 Domain Range of a function Graphically 00:06:00 Even & Odd Functions 00:07:00 One to one Function 00:05:00 Composite Functions 00:09:00 How to draw Rational Functions- 1 00:04:00 How to draw Rational Functions- 2 00:10:00 Inverse of a function Algebraically 00:05:00 Inverse of a function Graphically 00:09:00 Practice Problems 00:15:00 Practice Problems 00:11:00 Resources Downloads 00:40:00 Quadratic Equations Introduction to Quadratic Equations 00:04:00 Solving Quadratic Equations by Factorization method 00:10:00 Writing in completed square form 00:08:00 Solving by completed square method 00:08:00 Sketching of Quadratic Graphs 00:11:00 Quadratic graphs using Transformations 00:06:00 Quadratic inequalities 00:11:00 Deriving Quadratic formula 00:05:00 Solving problems using Quadratic Formula 00:06:00 Equations reducible to Quadratic 00:07:00 Nature of Roots of Quadratic Equations 00:04:00 Nature of roots continues 00:12:00 Quadratic Equations (Resources) 00:50:00 Co-ordinate Geometry Distance formula 00:15:00 Mid point formula 00:05:00 Gradient of a line 00:10:00 Graphing using gradient and y intercept 00:02:00 Some standard lines 00:04:00 Slope intercept form y = m x +c 00:05:00 Point slope form and two point form 00:10:00 Intersection of line and parabola 00:09:00 Practice Problems from past papers (part 3) 00:12:00 Sequence and series Sequence and series ( video) 00:08:00 Arithmetic Sequence 00:10:00 General term of an A.P. 00:07:00 Finding given term is which term? 00:05:00 Writing sequence when two terms are known 00:08:00 Condition for three terms to be in A.P. 00:05:00 Sum to n terms of A.P. 00:06:00 Practice Problems 1 (A.P.) 00:08:00 Practice problems 3 (A.P.) 00:07:00 Practice problems 4 (A.P.) 00:10:00 Geometric Progressions 00:11:00 Sum to n terms in G.P. 00:14:00 Sum to infinite Terms in G.P. 00:13:00 Practice Problems 1 (GP) 00:13:00 Practice Problems 2 (GP) 00:06:00 Practice Problems based on AP and GP both 00:15:00 Sequence and series Text 1 00:40:00 Sequence and series Text 2 00:55:00 Binomial Theorem What is Factorial? 00:06:00 n-choose -r problems 00:06:00 Properties of n - choose -r 00:05:00 Expanding using Binomial Theorem 00:11:00 Finding the indicated term in the Binomial expansion 00:10:00 Finding the indicated term from end 00:09:00 Finding the coefficient for given exponent (index) of the variable 00:08:00 Finding the term independent of variable 00:05:00 Expanding in increasing and decreasing powers of x 00:09:00 Practice problems 1 00:12:00 Practice Problems 2 00:09:00 Practice problems 3 00:10:00 Past papers problems 1 00:15:00 Past Paper problems 2 00:13:00 Past Paper problems 3 00:09:00 Resources in this section 00:50:00 Differentiation What is Derivative? 00:07:00 Derivation of formula for Derivative 00:06:00 Differentiation by definition or First Principle 00:06:00 Power Rule 00:20:00 Practice Problems on Power Rule 1 00:07:00 Practice Problems on Power Rule 2 00:07:00 Practice Problems on Power Rule 3 00:05:00 Practice Problems on Power Rule 4 00:11:00 Practice Problems on Power Rule 5 00:07:00 Tangents and Normals Tangents and Normals- Basics 00:12:00 Practice- Tangents and Normals Part 1 00:16:00 Practice- Tangents and Normals Part 2 00:13:00 Practice- Tangents and Normals Part 3 00:11:00 Practice- Tangents and Normals Part 4 00:14:00 Stationary Points & Curve Sketching Stationary Points - Basics 00:13:00 Practice- Increasing Decreasing & Maxima Minima part 1 00:11:00 Practice- Increasing Decreasing & Maxima Minima part 2 00:12:00 Practice- Increasing Decreasing & Maxima Minima part 3 00:10:00 Second Derivative Test (Maximum & Minimum Points) Concavity-Basics 00:02:00 Concavity & Second Derivative 00:08:00 Second Derivative Test 00:09:00 Practice Problems on second derivative 00:04:00 Practice Problem of Maxima Minima using second derivative test Part 1 00:17:00 Practice Problem of Maxima Minima using second derivative test Part 2 00:10:00 Practice Problem of Maxima Minima using second derivative test Part 3 00:07:00 Practice Problem of Maxima Minima using second derivative test Part 4 00:07:00 Applications of Maxima and Minima Part 1 00:09:00 Applications of Maxima and Minima Part 2 00:07:00 Applications of Maxima and Minima Part 3 00:10:00 Applications of Maxima and Minima Part 4 00:09:00 Applications of Maxima and Minima Part 5 00:10:00 Applications of Maxima and Minima Part 6 00:08:00 Past Paper Problems on applications of maxima and minima Part 1 00:09:00 Past Paper Problems on applications of maxima and minima Part 2 00:09:00 Past Paper Problems on applications of maxima and minima Part 3 00:08:00 Past Paper Problems on applications of maxima and minima Part 4 00:07:00 Chain Rule 00:12:00 Rate of change part 1 00:05:00 Rate of change part 2 00:10:00 Rate of change part 3 00:07:00 Past Paper Problems using chain rule -1 00:06:00 Past Paper Problems using chain rule - 2 00:07:00 Past Paper Problems using chain rule 3 00:07:00 Past Paper Problems using chain rule -4 00:04:00 Simultaneous Linear equations Graphical Method of solving pair of linear equations 00:10:00 Video lecture on Graphical method 00:05:00 Method of elimination by substitution 00:10:00 Video lecture on substitution method 00:06:00 Method of elimination by equating the coefficients 00:10:00 Video lecture on equating coefficients method 00:09:00 Practice Problems on Linear equation 00:20:00 Essential Revision How to take up this course? 00:10:00 Background of Algebra 00:10:00 Language of Alg ebra 00:10:00 Finding Values of algebraic expressions 00:14:00 Fractional Indices 00:10:00 Higher Indices 00:07:00 Rules of Brackets 00:04:00 Simplification by removing brackets (BODMAS) 00:11:00 Simplifications of Algebraic Fractions 00:07:00 Solving complex Linear Equations in one variable 00:10:00 Factorization by taking out common factor 00:10:00 Factorization by grouping the terms 00:09:00 Factorize using identity a ² - b ² 00:07:00 Factorization by middle term split 00:12:00

Who is this course for? 3ds Max Character Animation Training Course. Master character animation in our 3ds Max course. All levels welcome. Learn from certified tutors in flexible in-person or online sessions. Create unique 3D characters from scratch, gaining personalized techniques to fuel your creativity. Click here for more info: Website Duration: 20 hours Method: 1-on-1 personalized attention Schedule: Flexible 1-on-1 sessions. Schedule your sessions at your convenience, choosing any hour between 9 am and 7 pm from Mon to Sat. Course Title: 3ds Max Character Animation Workshop Duration: 20 Hours Course Overview: This workshop is meticulously crafted to instill the foundational principles of character animation utilizing 3ds Max. Whether you're a novice or possess some background in 3D modeling and animation, this course caters to your learning needs. You'll delve into the art of character rigging, grasp animation essentials, and employ advanced methods to breathe life into your characters. Course Outline: Module 1: Introduction to Character Animation Grasping animation principles Exploring 3ds Max animation tools Mastering character rig creation Understanding the intricacies of the timeline Module 2: Basic Animation Principles Embracing keyframe dynamics Crafting fundamental animation cycles Applying the 12 principles of animation Navigating the graph editor Utilizing ease-in and ease-out techniques Module 3: Advanced Animation Techniques Harnessing the power of the reaction manager Crafting non-linear animations Implementing inverse kinematics for dynamic movements Designing custom controllers Exploring expressions and scripts Module 4: Character Creation Sculpting a character model from scratch Grasping the nuances of topology Perfecting UV maps and texturing techniques Preparing characters for seamless rigging Module 5: Facial Animation Mastering facial animation principles Creating expressive blend shapes Utilizing morph targets for nuanced expressions Achieving flawless lip syncing Module 6: Body Animation Crafting seamless walk cycles Animating characters in motion Creating authentic and believable poses Employing character physics for lifelike movements Module 7: Advanced Character Animation Implementing motion capture data for realistic animations Leveraging CAT and Biped for intricate movements Understanding motion blur nuances Adding special effects for enhanced realism Fine-tuning rendering and outputting animations Module 8: Character Animation Projects Synthesizing knowledge into practical applications Creating a fundamental character animation Crafting a nuanced walk cycle Executing complex character animations Course Requirements: Access to a computer with 3ds Max installed Basic proficiency in computer operations Enthusiasm for delving into the world of character animation Course Goals: Upon completion, you will possess a profound understanding of character animation in 3ds Max. You'll be equipped with the expertise to create intricate, lifelike character animations using advanced techniques. Moreover, you'll gain the skills necessary to continue honing your craft, ensuring a solid foundation for your future endeavors in the realm of character animation. Upon successful completion of the 3ds Max Character Animation Workshop, participants will: Master Fundamental Principles: Understand the core principles of character animation, including keyframe dynamics, timing, and the 12 principles of animation, laying a strong foundation for advanced techniques. Proficient Software Usage: Navigate 3ds Max confidently, utilizing animation tools, character rigging techniques, and specialized editors for precise control over character movements. Advanced Animation Techniques: Apply advanced techniques such as non-linear animations, inverse kinematics, and custom controller design to create dynamic and realistic character movements. Facial Animation Mastery: Demonstrate expertise in facial animation by creating expressive blend shapes, morph targets, and achieving seamless lip syncing for realistic character emotions. Body Language Proficiency: Create fluid and natural body movements, including walk cycles, dynamic poses, and character motions, capturing the essence of lifelike animations. Special Effects Integration: Integrate special effects seamlessly into character animations, enhancing visual appeal and realism in the final output. Project Implementation: Apply acquired knowledge and skills in practical projects, including basic character animations, walk cycles, and complex character animations, demonstrating proficiency in real-world scenarios. Problem-Solving Skills: Develop problem-solving abilities related to character animation challenges, employing creative solutions to achieve desired results. Collaborative Skills: Engage in collaborative projects, demonstrating effective communication and teamwork while integrating animations into broader creative contexts. Portfolio Enhancement: Build a robust portfolio showcasing diverse character animations, reflecting both technical prowess and creative expression, essential for career advancement in the animation industry. Continued Learning: Acquire the skills and confidence necessary to pursue further learning and self-improvement in the field of character animation, enabling a continuous growth trajectory in the industry. Course Title: 3ds Max Character Animation Workshop Duration: 20 Hours Key Details: Course Focus: Comprehensive training in character animation using 3ds Max, covering fundamental principles, advanced techniques, facial animation, body language, special effects integration, and project-based learning. Audience: Ideal for beginners and individuals with some background in 3D modeling and animation, aiming to enhance their skills in character animation for industries such as animation studios, gaming, and film production. Instruction Method: Interactive, instructor-led sessions combining theoretical knowledge with hands-on practical exercises, fostering a dynamic learning environment. Flexible Learning Options: Participants can choose between in-person and live online sessions, accommodating diverse schedules and geographical locations. Certified Instructors: Experienced tutors and industry professionals with certification in 3ds Max and character animation, ensuring high-quality instruction and personalized guidance. Project-Based Learning: Engage in real-world projects, applying learned skills to create character animations, walk cycles, and intricate character movements, fostering practical expertise. Software Proficiency: Gain proficiency in 3ds Max, including animation tools, character rigging, and specialized editors, enabling participants to confidently navigate the software. Collaborative Learning: Opportunities for teamwork and collaborative projects, encouraging effective communication and networking within the class. Career Development: Build a diverse and impressive portfolio, receive guidance on industry best practices, and develop problem-solving skills crucial for a successful career in character animation. Post-Course Support: Access to resources, tutorials, and community forums, allowing participants to continue learning and stay updated with industry trends even after the course completion. Certification: Participants receive a certificate of completion, recognizing their proficiency in 3ds Max character animation, enhancing their professional credibility in the job market. By enrolling in this course, you'll enjoy the following advantages: Comprehensive Learning: Master the art of character animation in 3ds Max, covering fundamental concepts and advanced techniques. Certified Tutors and Industry Experts: Learn from experienced professionals with extensive knowledge of character animation, providing valuable insights. Personalized Instruction: Receive one-to-one training tailored to your specific learning needs, ensuring individual attention and effective progress. Flexible Learning Options: Choose between in-person or live online training, offering convenience and accessibility to suit your schedule. Recorded Lessons: Access recorded sessions to review content and reinforce your learning at your own pace and convenience. Lifetime Email Support: Benefit from ongoing assistance and guidance through email, even after completing the course. Free Career Advice: Tap into our industry expertise and receive valuable career guidance to excel in the field of character animation.