Coursera

Software Architecture Patterns for Big Data (Coursera)

Offered by University of Colorado Boulder,
Software Architecture Patterns for Big Data (Coursera)

The course is intended for individuals looking to understand the architecture patterns necessary to take large software systems that make use of big data to production. You will transform big data prototypes into high quality tested production software. After measuring the performance characteristics of distributed systems, you will identify trouble areas and implement scalable solutions to improve performance. Upon completion of the course you will know how to scale production data stores to perform under load, designing load tests to ensure applications meet performance requirements.

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

Software Architecture Patterns for Big Data can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics.
Course 2 of 3 in the Software Architecture for Big Data Specialization.

What You Will Learn

  • Compare, measure, and test big data models for production use.
  • Write custom performance tests to measure the characteristics of a distributed system.
  • Use queues to horizontally distribute large workloads.

Syllabus

WEEK 1
Predictive Models
In this module, you will learn how to write tests that allow you to iterate on predictive models.

WEEK 2
Performance of Distributed Systems
In this module, you will learn how to write performance tests to ensure your distributed system operates as expected in production.

WEEK 3
Horizontal Distribution of Large Workloads
In this module, you will learn how to use queues to horizontally distribute large workloads.

WEEK 4
Highly Available Distributed Systems
In this module, you will learn the advantages and disadvantages of high availability distributed systems.

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

Related Courses

Graph Analytics for Big Data (Coursera) Coursera
University of California, San Diego

Graph Analytics for Big Data (Coursera)

Statistics & Data Analysis Data Science

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data.

Sep 14th 2026
5-12 Weeks
Big Data Data Analysis Graphs
Details
Getting Started with CyberGIS (Coursera) Coursera
University of Illinois at Urbana-Champaign

Getting Started with CyberGIS (Coursera)

Statistics & Data Analysis Data Science

This course is intended to introduce students to CyberGIS—Geospatial Information Science and Systems (GIS)—based on advanced cyberinfrastructure as well as the state of the art in high-performance computing, big data, and cloud computing in the context of geospatial data science. Emphasis is placed on learning the cutting-edge advances of cyberGIS and its underlying geospatial data science principles.

Sep 28th 2026
4 Weeks
Big Data Geospatial Hadoop
Details
Big Data Analysis Deep Dive (Coursera) Coursera
Alibaba Cloud Academy

Big Data Analysis Deep Dive (Coursera)

CS: Information & Technology

The job market for architects, engineers, and analytics professionals with Big Data expertise continues to increase. The Academy’s Big Data Career path focuses on the fundamental tools and techniques needed to pursue a career in Big Data. This course includes: data processing with python, writing and reading SQL queries, transmitting data with MaxCompute, analyzing data with Quick BI, using Hive, Hadoop, and spark on E-MapReduce, and how to visualize data with data dashboards. Work through our course material, learn different aspects of the Big Data field, and get certified as a Big Data Professional!

Sep 28th 2026
5-12 Weeks
Python SQL Big Data
Details
Laboratório de Programação Orientada a Objetos - Parte 2 (Coursera) Coursera
Universidade de São Paulo, Brasil

Laboratório de Programação Orientada a Objetos - Parte 2 (Coursera)

CS: Software Engineering CS: Programming

Esta é a segunda parte do curso avançado de Programação Orientada a Objetos oferecido pelo Departamento de Ciência da Computação do IME-USP. O curso é voltado para profissionais ou estudantes interessados em Desenvolvimento de Software Avançado e que já dominam uma linguagem de programação e já conhecem os fundamentos básicos da orientação a objetos.

Sep 14th 2026
5-12 Weeks
Programming Object-Oriented Programming OOP
Details
Infonomics I: Business Information Economics and Data Monetization (Coursera) Coursera
University of Illinois at Urbana-Champaign

Infonomics I: Business Information Economics and Data Monetization (Coursera)

Business

Thriving in the Information Age compels organizations to deploy information as an actual business asset, not as an IT asset or merely as a business byproduct. This demands creativity in conceiving and implementing new ways to generate economic benefits from the wide array of information assets available to an organization. Unfortunately, information too frequently is underappreciated and therefore underutilized.

Sep 14th 2026
4 Weeks
Business Economics Big Data
Details
Media ethics & governance (Coursera) Coursera
University of Amsterdam

Media ethics & governance (Coursera)

Social Sciences

This course explores some of the basic theories, models and concepts in the field of media ethics. We will introduce influential ethical theories and perspectives, explore changing societal demands and expectations of media creation and media use, and we will elaborate on existing ethical norms for media professionals. After following this course, you will be able to reflect on ethical dilemmas and develop a well-substantiated argumentation for ethical decision making in a variety of media-related contexts.

Sep 21st 2026
4 Weeks
Ethics Big Data Research
Details
Predictive Modeling and Analytics (Coursera) Coursera
University of Colorado Boulder

Predictive Modeling and Analytics (Coursera)

Statistics & Data Analysis Data Science

Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.

Sep 14th 2026
4 Weeks
Data Analysis Analytics Data Cleaning
Details
Data Processing with Azure (Coursera) Coursera
LearnQuest

Data Processing with Azure (Coursera)

CS: Information & Technology

This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.

Sep 21st 2026
3 Weeks
Big Data Data Analysis Microsoft Azure
Details
Deploying Machine Learning Models (Coursera) Coursera
University of California, San Diego

Deploying Machine Learning Models (Coursera)

Statistics & Data Analysis Data Science

In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets.

Sep 14th 2026
4 Weeks
Python Machine Learning Big Data
Details
Security and Privacy for Big Data - Part 2 (Coursera) Coursera
EIT Digital

Security and Privacy for Big Data - Part 2 (Coursera)

CS: Information & Technology

This course sensitizes regarding privacy and data protection in Big Data environments. You will discover privacy preserving methodologies, as well as data protection regulations and concepts in your Big Data system. By the end of the course, you will be ready to plan your next Big Data project successfully, ensuring that all privacy and data protection related issues are under control.

Sep 21st 2026
1 Week
Security Big Data Privacy
Details