Excel for Data Science and Machine Learning

Why machine learning and data science in Excel?Do data scientists and data analysts use Excel at all?The answer is a resounding “Yes, they do!”Few people in an organization can read a Jupyter Notebook, but literally everyone is familiar with Excel. It provides the direct, visual insight that both experts and beginners need to apply the most common machine learning methods. Plus, it is naturally suited to data preparation.In fact, the simplicity of Excel lowers barriers to entry and allows you to undertake your own data analysis right away. Even if you are not a computer science graduate with Python coding skills, this course will teach you how to perform machine learning and advanced statistical analysis on your own.Excel is the perfect environment to grasp the logic of different machine learning techniques in an easy-to-understand way. All you need to do is get started, and in no time, you will be able to fully understand the intuition behind ML algorithms without having to code at all.So, if you are not into programming but you want to break into data science, statistical analysis, and machine learning, and you aspire to become a data analyst or data scientist, you’ve come to the right place.Machine learning methods we will cover in the course:Linear regressionMultiple Linear RegressionLogistic RegressionCluster AnalysisK-Means ClusteringDecision TreesYou will learn fundamental statistical and machine learning concepts, such as:Regression coefficientsVariabilityOLS assumptionsROC curveUnderfittingOverfittingDifference between classification and clusteringHow to choose the number of clustersHow to cluster categorical dataWhen to