The Complete Visual Guide to Machine Learning & Data Science
The Complete Visual Guide to Machine Learning & Data Science Course
Explore Data Science & Machine Learning topics with simple, step-by-step demos and user-friendly Excel models (NO code!)
This course is for everyday people looking for an intuitive, beginner-friendly introduction to the world of machine learning and data science. Build confidence with guided, step-by-step demos, and learn foundational skills from the ground up. Instead of memorizing complex math or learning a new coding language, we’ll break down and explore machine learning techniques to help you understand exactly how and why they work.
Follow along with simple, visual examples and interact with user-friendly, Excel-based models to learn topics like linear and logistic regression, decision trees, KNN, naïve bayes, hierarchical clustering, sentiment analysis, and more – without writing a SINGLE LINE of code.
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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
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