EdX

Machine Learning for Data Science and Analytics (edX)

Machine Learning for Data Science and Analytics (edX)

Learn the principles of machine learning and the importance of algorithms. Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.

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

This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.
This course is part of the Data Science for Executives Professional Certificate.

What you'll learn:

  • What machine learning is and how it is related to statistics and data analysis
  • How machine learning uses computer algorithms to search for patterns in data
  • How to use data patterns to make decisions and predictions with real-world examples from healthcare involving genomics and preterm birth
  • How to uncover hidden themes in large collections of documents using topic modeling
  • How to prepare data, deal with missing data and create custom data analysis solutions for different industries
  • Basic and frequently used algorithmic techniques including sorting, searching, greedy algorithms and dynamic programming
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Introduction to Data Science (edX) EdX
IBM

Introduction to Data Science (edX)

Learn about the world of data science first-hand from real data scientists. The art of uncovering the insights and trends in data has been around for centuries. The ancient Egyptians applied census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year.

Self Paced
Self-Paced
Estadística Aplicada a los Negocios (edX) EdX
Galileo University,GalileoX

Estadística Aplicada a los Negocios (edX)

Aprende las principales herramientas y técnicas de la estadística descriptiva y la estadística inferencial para analizar e interpretar datos desde la perspectiva de negocios facilitando la toma de decisiones. Este curso proporciona una introducción al análisis de datos en base a las principales herramientas estadísticas, enfocándose en la estadística descriptiva y la estadística inferencial.

Self Paced
Self-Paced
Introduction to Linear Models and Matrix Algebra (edX) EdX
HarvardX,Harvard University

Introduction to Linear Models and Matrix Algebra (edX)

Learn to use R programming to apply linear models to analyze data in life sciences. Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory data analysis course, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will use the R programming language.

Self Paced
Self-Paced
Big Data Capstone Project (edX) EdX
University of Adelaide,AdelaideX

Big Data Capstone Project (edX)

Further develop your knowledge of big data by applying the skills you have learned to a real-world data science project. This project will give you the opportunity to deepen your learning by giving you valuable experience in evaluating, selecting and applying relevant data science techniques, principles and theory to a data science problem. This project will see you plan and execute a reasonably substantial project and demonstrate autonomy, initiative and accountability.

Self Paced
Self-Paced
Data Science: Inference and Modeling (edX) EdX
HarvardX,Harvard University

Data Science: Inference and Modeling (edX)

Learn inference and modeling, two of the most widely used statistical tools in data analysis. Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting.

Self Paced
Self-Paced
Observation Theory: Estimating the Unknown (edX) EdX
Delft University of Technology,DelftX

Observation Theory: Estimating the Unknown (edX)

Learn how to estimate parameters from observational data for real-world engineering applications and assess the quality of the results. Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.

Self Paced
Self-Paced
Data Science: Wrangling (edX) EdX
HarvardX,Harvard University

Data Science: Wrangling (edX)

Learn to process and convert raw data into formats needed for analysis. In this course, we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.

Self Paced
Self-Paced
Data Science Ethics (edX) EdX
University of Michigan,MichiganX

Data Science Ethics (edX)

Learn how to think through the ethics surrounding privacy, data sharing, and algorithmic decision-making. As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias.

Self Paced
Self-Paced