Coursera

Introducción a la Minería de Datos (Coursera)

Offered by Pontificia Universidad Católica de Chile,

En este curso, aprenderás de manera gradual y práctica los conceptos básicos de Minería de Datos, junto a los algoritmos más utilizados hoy en día. Al finalizar el curso, serás capaz de entender la importancia de manejar la información y de explorar por ti mismo distintas bases de datos reales. Este curso es el primer paso para convertirte en un/a profesional con habilidades básicas de un científico de datos o Data Scientist, de manera tal que puedas abrirle la puerta al futuro.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Syllabus

WEEK 1: Reglas de Asociación
WEEK 2: Algoritmos de Clasificación I
WEEK 3: Algoritmos de Clasificación II
WEEK 4: Métricas de Evaluación de Clasificación
WEEK 5: Algoritmos de Clustering

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

Knowledge Accelerators

The ABC's of GDPR: Protecting Privacy in an Online World (Coursera)

Business

This course is aimed at business professionals, web designers, and other interested professionals who collect, process, use, or otherwise encounter personal data subject to the European Union's General Data Protection Regulation. By the end of this course, learners will be familiar with roles involved in assuring compliance with GDPR standards, the rights of GDPR data subjects, responsibilities of organizations regarding GDPR and the consequences for failure to comply.

Nov 2nd 2026

1 Week

Data Management Privacy Data Privacy

Coursera

Princeton University

Computer Science: Algorithms, Theory, and Machines (Coursera)

Computer Science

This course introduces the broader discipline of computer science to people having basic familiarity with Java programming. It covers the second half of our book Computer Science: An Interdisciplinary Approach (the first half is covered in our Coursera course Computer Science: Programming with a Purpose, to be released in the fall of 2018). Our intent is to demystify computation and to build awareness about the substantial intellectual underpinnings and rich history of the field of computer science.

Nov 2nd 2026

5-12 Weeks

Programming Computing Algorithms

Coursera

École normale supérieure

Approximation Algorithms Part II (Coursera)

CS: Software Engineering CS: Programming

This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut. By taking the two parts of this course, you will be exposed to a range of problems at the foundations of theoretical computer science, and to powerful design and analysis techniques.

Oct 26th 2026

4 Weeks

Algorithms Computer Science Linear Programming

Coursera

Universidad Nacional Autónoma de México

Designing data-intensive applications (Coursera)

Statistics & Data Analysis Data Science

Welcome to the specialization course of Designing data-intensive applications. This course will be completed on four weeks, it will be supported with videos and exercises.

Oct 26th 2026

4 Weeks

Data Mining Data Analysis Relational Databases

Coursera

Duke University

Programming Fundamentals (Coursera)

CS: Theory CS: Programming

Programming is an increasingly important skill, whether you aspire to a career in software development, or in other fields. This course is the first in the specialization Introduction to Programming in C, but its lessons extend to any language you might want to learn. This is because programming is fundamentally about figuring out how to solve a class of problems and writing the algorithm, a clear set of steps to solve any problem in its class.

Nov 2nd 2026

4 Weeks

Programming Algorithms C Language

Coursera

Columbia University

Decision Making and Reinforcement Learning (Coursera)

Computer Science

This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms. We touch on the notion of partial observability in real problems, modeled by POMDPs and then solved by online planning methods.

Oct 26th 2026

5-12 Weeks

Algorithms Machine Learning Monte Carlo Method

Coursera

Sungkyunkwan University - SKKU

Machine Learning Algorithms (Coursera)

CS: Software Engineering Data Science

In this course you will: understand the naïve Bayesian algorithm; understand the Support Vector Machine algorithm; understand the Decision Tree algorithm; understand the Clustering. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Oct 26th 2026

4 Weeks

Machine Learning Clustering Support Vector Machines

Coursera

Rice University

Algorithmic Thinking (Part 2) (Coursera)

CS: Theory

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Nov 2nd 2026

4 Weeks

Python Computing Algorithms

Coursera

Northeastern University

Machine Learning in Healthcare: Fundamentals & Applications (Coursera)

Health & Society Data Science

Examines data mining perspectives and methods in a healthcare context. Introduces the theoretical foundations for major data mining methods and studies how to select and use the appropriate data mining method and the major advantages for each. Students are exposed to contemporary data mining software applications and basic programming skills. Focuses on solving real-world problems, which require data cleaning, data transformation, and data modeling.

Oct 26th 2026

4 Weeks

Healthcare Artificial Intelligence Machine Learning

Coursera

University of Edinburgh,Universidad ORT Uruguay

Code Yourself! An Introduction to Programming (Coursera)

CS: Software Engineering CS: Programming

Have you ever wished you knew how to program, but had no idea where to start from? This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer.

Oct 26th 2026

5-12 Weeks

Programming Algorithms Coding

Coursera

Institut Mines-Telecom

Data intelligence for businesses and managers (Coursera)

Statistics & Data Analysis Data Science

With the proliferation of connected objects (computers, tablets, watches, etc.), huge masses of data are generated every second. This Big Data has led to the emergence of a data economy, where data is the main source of competitive advantage for companies. In this sense, data and its processing tools have become a strategic priority for companies, and the main gas pedal of their digital transformation.

Nov 2nd 2026

5-12 Weeks

Artificial Intelligence Data Management Business Strategy

Coursera

EIT Digital

Geometric Algorithms (Coursera)

CS: Theory Computer Science

Course Information: In many areas of computer science such as robotics, computer graphics, virtual reality, and geographic information systems, it is necessary to store, analyze, and create or manipulate spatial data. This course deals with the algorithmic aspects of these tasks: we study techniques and concepts needed for the design and analysis of geometric algorithms and data structures. Each technique and concept will be illustrated on the basis of a problem arising in one of the application areas mentioned above.

Oct 30th 2026

3 Weeks

Algorithms Data Structures Geometric Algorithms