Machine Learning & Data Science: The Complete Visual Guide

Learn data science & machine learning topics with simple, step-by-step demos and user-friendly Excel models (NO code!)

What you’ll learn
Build foundational machine learning & data science skills WITHOUT writing complex code
Play with interactive, user-friendly Excel models to learn how machine learning techniques actually work
Enrich datasets using feature engineering techniques like one-hot encoding, scaling and discretization
Predict categorical outcomes using classification models like K-nearest neighbors, naïve bayes, and decision trees
Build accurate forecasts and projections using linear and non-linear regression models
Apply powerful techniques for clustering, association mining, outlier detection, and dimensionality reduction
Learn how to select and tune models to optimize performance, reduce bias, and minimize drift
Explore unique, hands-on case studies to simulate how machine learning can be applied to real-world cases

Requirements
This is a beginner-friendly course (no prior knowledge or math/stats background required)
Description
Who this course is for
Anyone looking to learn the foundations of machine learning through interactive, beginner-friendly demos
Data Analysts or BI experts looking to transition into data science or build a fundamental understanding of machine learning
R or Python users seeking a deeper understanding of the models and algorithms behind their code
Excel users who want to learn and apply powerful tools for predictive analytics

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Happy Learning!!