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Learn Regression Analysis, earn certificates with free online courses from Stanford, MIT, University of Pennsylvania, University of Michigan and other top universities around the world. Read reviews to decide if a class is right for you.
Equip yourself with data analysis tools and techniques for informed business decision-making. Learn to extract insights, enhance processes, and drive strategic initiatives through hands-on applications.
Unlock Excel's Potential: Data Analysis, Charting, and Advanced Techniques for Science & Engineering Professionals
Learn advanced statistical analyses in R: correlations, t-tests, ANOVA, regression, and reliability indicators. Step-by-step guidance for parametric and non-parametric tests, with assumption checks and result interpretation.
Microsoft Excel - The Complete Excel Data Analysis. Learn Basic to Advanced Excel Data Analysis & Visualization.
Mastering advanced statistical analyses in R: from ANCOVA to logistic regression, multidimensional scaling, factor analysis, cluster analysis, and discriminant analysis. Gain expertise in sophisticated data scrutiny techniques.
Machine Learning: A comprehensive guide to machine learning. Learn machine learning algorithms & machine learning tools
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.
Fundamentals of Data Science : Exploratory Data Analysis (EDA), Regression (Linear & logistic), Visualization, Basic ML
Discover econometrics, analyze data, and master regression models. Learn to interpret results, build models, and apply skills to real-world scenarios like estimating the Capital Asset Pricing Model using R.
Learn Data Analysis: Descriptive & Inferential Statistics, Regression Analysis, Time Series and much more!
Deep dive into Machine Learning with Python Programming. Implement practical scenarios & a project on Recommender System
Master advanced regression techniques for data-driven industries. Learn logistic, Poisson, and robust regression, generalized linear models, and model validation using R for practical applications.
Thoroughly understand statistical concepts, apply them in R and interpret the results correctly with maximum validity
Explore machine learning, visual recognition, and NLP in AI workflows. Learn evaluation metrics, model selection, and best practices for linear models, tree-based algorithms, and neural networks using IBM Watson.
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