329 Linear courses

Throughout this course, you will learn everything you need to know about linear and non-linear regression, regression modeling, and Stata. By the end of this course, you will be able to understand and be confident in interpreting complex types of data using Stata.

Learn complete hands-on Regression analysis for practical Statistical modelling and Machine Learning in R

Go from Beginner to Super Advance Level in Machine Learning Algorithms using Python and Mathematical Insights

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

This video course gives you an insight into applied data science concepts using Python. With the help of interesting activities and hands-on coding exercises, you'll learn about data science, extended data analysis, linear and logistic regression, data visualization, k-means clustering, and decision trees.

Learn to build highly sophisticated deep learning and Computer Vision applications with PyTorch

Overview Statistical Concepts and Application with R Course is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Statistical Concepts and Application with R Course and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 05 Hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Introduction to the course Introduction 00:03:00 Single Linear Regression Install R, RStudio and Basic Functionality 00:08:00 Basics of Linear Regression 00:03:00 Basics of Linear Regression Ctnd 00:03:00 Linear Regression Analysis 00:09:00 Linear Relationships 00:09:00 Line of Best Fit, SSE and MSE 00:05:00 Linear Regression Analysis Ctnd 00:02:00 Regression Results and Interpretation 00:10:00 Predicting Future Profits 00:13:00 Statistical Validity Tests 00:09:00 Statistical Validity Discussion 00:07:00 Single Linear Regression 00:06:00 Multiple Linear Regression Single Linear Regression 00:06:00 Importing the data 00:04:00 Correlation Matrix and MLR 00:08:00 MLR Results and ANOVA 00:07:00 The Best Model? 00:05:00 Interaction Terms and Validity Testing 00:18:00 ANOVA and Predictions 00:18:00 Non-linear Regression Non-linear Regression (and Recap) 00:07:00 Logistic Regression Overview 00:22:00 Logistic Regression: Odds, Logs and Poisson 00:13:00 Logistic Regression: Fitting the Models in R 00:24:00 Optimization Theory and Differential Calculus Differential Calculus - Finding the Maximum and the Minimum 00:15:00 Differential Calculus: One Unknown Input 00:08:00 Analysis in R: One Unknown Input Differential Calculus 00:29:00 Differential Calculus - Two Unknown Inputs 00:07:00 Analysis in R: Two Unknown Inputs Differential Calculus 00:44:00 Downloadable Resources Resource - Statistical Concepts and Application with R 00:00:00

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

This course covers Python for data science and machine learning in detail and is for a beginner in Python. You will also learn about core concepts of data science, exploratory data analysis, statistical methods, role of data, challenges of bias, variance and overfitting, model evaluation techniques, model optimization using hyperparameter tuning, grid search cross-validation techniques, and more.

This is an introductory course on machine learning. The course covers a wide range of topics, from handling a dataset to model delivery. Some prior training in Python programming and basic calculus knowledge will help you get the best out of this course.