Coursera

Designing data-intensive applications (Coursera)

Offered by Universidad Nacional Autónoma de México,
Designing data-intensive applications (Coursera)

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.

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

By the end of this specialization, learners will be able to propose, design, justify and develop high reliable information systems according to type of data and volume of information, response time, type of processing and queries in order to support scalability, maintainability, security and reliability considering the last information technologies.
Software to download:
MySQL Workbench
Rapidminer
Hadoop framework Hortonworks
MongoDB
In case you have a Mac / IOS operating system you need to perform an action called VirtualBox.
Course 4 of 4 in the Database systems Specialization.

Syllabus

WEEK 1
Designing a transaccional system
After completing this module, a learner will learn how to distinguish a transactional from an analytical information system according to consistency, concurrency and integrity, and how to propose an architecture that suits user requirements.

WEEK 2
Designing an analytical system
After completing this module, a learner will learn how to distinguish a transactional from an analytical information system according to the queries required on a huge amount of historical structured data that requires fast processing.

WEEK 3
Designing an alternative to relational databases
After completing this module, a learner will learn how to distinguish which database technology to use to suit the user requirements, detect frauds and support ACID properties.

WEEK 4
Designing an analytical system within a data lake
After completing this module, a learner will identify the architecture and technologies required to analyse a huge volume of structured and semistructured data.

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

Related Courses

Data Processing Using Python (Coursera) Coursera
Nanjing University

Data Processing Using Python (Coursera)

CS: Software Engineering Statistics & Data Analysis

This course is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level.

Nov 23rd 2026
5-12 Weeks
Python Data Structures Data Analysis
Details
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Statistics & Data Analysis

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Nov 9th 2026
4 Weeks
Medicine Statistics Data Analysis
Details
Big Data Analysis with Scala and Spark (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Big Data Analysis with Scala and Spark (Coursera)

CS: Theory CS: Programming

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout.

Nov 9th 2026
4 Weeks
Programming Algorithms SQL
Details
Bioinformatic Methods I (Coursera) Coursera
University of Toronto

Bioinformatic Methods I (Coursera)

Health & Society Statistics & Data Analysis

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Nov 16th 2026
5-12 Weeks
Biology Bioinformatics Molecular Biology
Details
Relational Database Implementation and Applications (Coursera) Coursera
Illinois Tech

Relational Database Implementation and Applications (Coursera)

Statistics & Data Analysis Data Science

In today's data-driven world, the ability to work with relational databases is an essential skill for professionals in various fields. This course is designed to equip you with the knowledge and practical skills needed to become proficient in database management and application development. Whether you are pursuing a career as a database administrator, software developer, or data analyst, this course provides you with a strong foundation to excel in your chosen field.

Nov 16th 2026
5-12 Weeks
SQL Transactions Hashing
Details
Data Visualization for Genome Biology (Coursera) Coursera
University of Toronto

Data Visualization for Genome Biology (Coursera)

Statistics & Data Analysis Data Science

The past decade has seen a vast increase in the amount of data available to biologists, driven by the dramatic decrease in cost and concomitant rise in throughput of various next-generation sequencing technologies, such that a project unimaginable 10 years ago was recently proposed, the Earth BioGenomes Project, which aims to sequence the genomes of all eukaryotic species on the planet within the next 10 years. So while data are no longer limiting, accessing and interpreting those data has become a bottleneck. One important aspect of interpreting data is data visualization. This course introduces theoretical topics in data visualization through mini-lectures, and applied aspects in the form of hands-on labs.

Nov 16th 2026
5-12 Weeks
Biology Genome Data Analysis
Details
Principles of fMRI 2 (Coursera) Coursera
Johns Hopkins University,University of Colorado Boulder

Principles of fMRI 2 (Coursera)

Health & Society Medicine & Pharmacology

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data.

Nov 16th 2026
4 Weeks
Brain Mind Behavioral
Details
Data Science for Business Innovation (Coursera) Coursera
Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

Statistics & Data Analysis Data Science

The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Nov 16th 2026
4 Weeks
NoSQL Machine Learning Big Data
Details
Julia Scientific Programming (Coursera) Coursera
University of Cape Town

Julia Scientific Programming (Coursera)

Statistics & Data Analysis Data Science

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more.

Nov 9th 2026
4 Weeks
IPython Data Analysis Computer Programming
Details
Statistics and Data Analysis with Excel, Part 2 (Coursera) Coursera
University of Colorado Boulder

Statistics and Data Analysis with Excel, Part 2 (Coursera)

Statistics & Data Analysis Data Science

This course is meant to be a direct continuation of "Statistics and Data Analysis with Excel, Part 1." Therefore, it is not recommended to take Part 2 unless you've also taken Part 1. Building on the topics learned in Part 1 of the course (probability, probability mass and density functions, the normal and standard normal distributions), this course dives into a more applied side of statistics.

Nov 16th 2026
5-12 Weeks
Statistics Excel Data Analysis
Details