Udemy – Machine Learning & Data Science: The Complete Visual Guide 2025-6

Machine Learning & Data Science: The Complete Visual Guide, 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. In Part 1 we’ll introduce the machine learning workflow and common techniques for cleaning and preparing raw data for analysis. We’ll explore univariate analysis with frequency tables, histograms, kernel densities, and profiling metrics, then dive into multivariate profiling tools like heat maps, violin & box plots, scatter plots Throughout the course, we’ll introduce real-world scenarios to solidify key concepts and simulate actual data science and business intelligence cases. You’ll use profiling metrics to clean up product inventory data for a local grocery, explore Olympic athlete demographics with histograms and kernel densities, visualize traffic accident frequency with heat maps, and more.

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

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

Specificatoin of Machine Learning & Data Science: The Complete Visual Guide

• Publisher : Udemy
• Teacher : Maven Analytics • 1,500,000 Learners , Chris Dutton , Joshua MacCarty
• Language: English
• Level : All Levels
• Lectures : 182
• Duration : 8 hours and 51 minutes

Content of Machine Learning & Data Science: The Complete Visual Guide

Requirements

• This is a beginner-friendly course (no prior knowledge or math/stats background required)
• We’ll use Microsoft Excel (Office 365) for some course demos, but participation is optional

Pictures

Sample Clip

Installation Guide

Extract the files and watch with your favorite player

Subtitle : English

Quality: 720

The 2025/6 version has not changed in terms of the number of lessons and time compared to 2024/11, but it has been updated after 1 year.

Download Links

Download Part 1 – 1 GB

Download Part 2 – 617 MB

File size

1.6 GB