Machine Learning With Big Data (Coursera)

Machine Learning With Big Data (Coursera)

Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.

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

At the end of the course, you will be able to:
• Design an approach to leverage data using the steps in the machine learning process.
• Apply machine learning techniques to explore and prepare data for modeling.
• Identify the type of machine learning problem in order to apply the appropriate set of techniques.
• Construct models that learn from data using widely available open source tools.
• Analyze big data problems using scalable machine learning algorithms on Spark.

Course 4 of 6 in the Big Data Specialization.

Syllabus

WEEK 1: Welcome; Introduction to Machine Learning with Big Data
WEEK 2: Data Exploration
WEEK 3: Classification
WEEK 4: Evaluation of Machine Learning Models
WEEK 5: Regression, Cluster Analysis, and Association Analysis

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

Related Courses

Real-Time Big Data Access using HBase: Boosting Performance (Coursera) Coursera
LearnQuest

Real-Time Big Data Access using HBase: Boosting Performance (Coursera)

In the world of big data, the significant growth in both the sheer volume and variety of data has presented significant challenges. Apache HBase has emerged as a robust and scalable solution. HBase is a powerful, distributed, and scalable NoSQL database designed to handle large amounts of data while maintaining high performance.

Oct 12th 2026
3 Weeks
Information Theory (Coursera) Coursera
The Chinese University of Hong Kong

Information Theory (Coursera)

At the completion of this course, the student should be able to: demonstrate knowledge and understanding of the fundamentals of information theory; appreciate the notion of fundamental limits in communication systems and more generally all systems; develop deeper understanding of communication systems; apply the concepts of information theory to various disciplines in information science.

Oct 5th 2026
13-24 Weeks
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Oct 12th 2026
4 Weeks
Matrix Methods (Coursera) Coursera
University of Minnesota

Matrix Methods (Coursera)

Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction.

Oct 12th 2026
5-12 Weeks
Digital Signal Processing 4: Applications (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Digital Signal Processing 4: Applications (Coursera)

Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices.

Oct 12th 2026
3 Weeks
ML Pipelines on Google Cloud (Coursera) Coursera
Google Cloud

ML Pipelines on Google Cloud (Coursera)

In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. You will learn about pipeline components and pipeline orchestration with TFX. You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata.

Oct 12th 2026
4 Weeks
Technologies and platforms for Artificial Intelligence (Coursera) Coursera
Politecnico di Milano

Technologies and platforms for Artificial Intelligence (Coursera)

This course will address the hardware technologies for machine and deep learning (from the units of an Internet-of-Things system to a large-scale data centers) and will explore the families of machine and deep learning platforms (libraries and frameworks) for the design and development of smart applications and systems.

Oct 12th 2026
4 Weeks
Machine Learning Introduction for Everyone (Coursera) Coursera
IBM

Machine Learning Introduction for Everyone (Coursera)

This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more.

Oct 12th 2026
3 Weeks
Cadeia de Suprimentos na Nuvem (Coursera) Coursera
FIA Business School

Cadeia de Suprimentos na Nuvem (Coursera)

Nossas boas-vindas ao Curso Cadeia de Suprimentos na Nuvem. Neste curso, você aprenderá como o supply chain pode ampliar o valor da empresa explorando as diversas ferramentas disponíveis em cloud para potencializar a visibilidade e a responsividade da cadeia, melhorando o nível de serviço prestado aos clientes.

Oct 12th 2026
5-12 Weeks
Introduction to PySpark (Coursera) Coursera
Edureka

Introduction to PySpark (Coursera)

Welcome to Introduction to PySpark, a short course strategically crafted to empower you with the skills needed to assess the concepts of Big Data Management and efficiently perform data analysis using PySpark. Throughout this short course, you will acquire the expertise to perform data processing with PySpark, enabling you to efficiently handle large-scale datasets, conduct advanced analytics, and derive valuable insights from diverse data sources.

Oct 12th 2026
1 Week