• views: 220
• date: 6 June 2026
• posted by: AD-TEAM

Learn foundational machine learning and data science concepts through simple visual examples and interactive models. This beginner-friendly course breaks down complex techniques into intuitive steps without requiring coding or advanced math, helping you understand how machine learning works in practice.

What you'll learn:

Build foundational machine learning and data science skills without coding
Explore data profiling and visualization techniques
Apply classification models like K-nearest neighbors, naïve Bayes, and decision trees
Understand regression and forecasting methods
Learn unsupervised learning techniques like clustering and dimensionality reduction
Practice model selection and tuning for better performance

Course content:

Introduction to machine learning and the ML landscape
Data quality assurance and profiling
Univariate and multivariate data analysis
Classification modeling and evaluation
Regression and forecasting techniques
Unsupervised learning and clustering methods

Requirements:

No prior machine learning or coding experience needed
Optional use of Excel for visual demonstrations

Description:
This course offers a complete visual introduction to machine learning and data science. You will learn how key models and techniques work through interactive, beginner-friendly demos and intuitive examples. The focus is on understanding concepts like classification, regression, clustering, and model tuning without writing code, making it ideal for learners who want practical insight into machine learning fundamentals.

Who this course is for:

Beginners seeking an intuitive introduction to machine learning
Analysts and professionals transitioning into data science
Excel users interested in predictive analytics
Anyone wanting to understand machine learning concepts clearly

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