Coursera

A quick tour on Big Data and Business Intelligence (Coursera)

Offered by University of Naples Federico II,
A quick tour on Big Data and Business Intelligence (Coursera)

This course is devoted to beginners and practitioners of Big Data and AI fields. It will be a quick overview of some basic concepts that could be further elaborated by professionals. Ranging from CAP theorem to Turing assumption, we will provide a starting guide for diving in these fascinating topics.

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

This course is part of the Autonomous Vehicle Engineering Specialization.

Syllabus

Big data basics
Module 1
Getting familiar with the following key concepts by attending the lessons and answering basic queries

Hadoop
Module 2
Getting familiar with the following paradigms by attending the lessons and writing small pieces of programs

Hadoop Tools
Module 3
Getting familiar with the following tools by attending the lessons and solving small case studies

NoSQL Systems and AI
Module 4
Getting familiar with the No SQL paradigm and AI building blocks by attending the lessons and designing basic solutions

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

Related Courses

Machine Learning for All (Coursera) Coursera
University of London

Machine Learning for All (Coursera)

Data Science Computer Science

Machine Learning, often called Artificial Intelligence or AI, is one of the most exciting areas of technology at the moment. We see daily news stories that herald new breakthroughs in facial recognition technology, self driving cars or computers that can have a conversation just like a real person. Machine Learning technology is set to revolutionise almost any area of human life and work, and so will affect all our lives, and so you are likely to want to find out more about it.

Jun 29th 2026
4 Weeks
Artificial Intelligence Machine Learning AI Technology
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.

Jun 29th 2026
1 Week
Security Big Data Privacy
Details
Guided Tour of Machine Learning in Finance (Coursera) Coursera
New York University

Guided Tour of Machine Learning in Finance (Coursera)

Data Science

This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance.

Jun 29th 2026
4 Weeks
ML Artificial Intelligence Machine Learning
Details
Learn to code with AI (Coursera) Coursera
Scrimba

Learn to code with AI (Coursera)

CS: Software Engineering

Imagine waking up tomorrow as a web developer. What would you want to build? With AI tools like ChatGPT, you're already a developer, regardless of your experience, if you know how to work with them. So in this course, you'll build functional, interactive front-end projects while learning how to write effective prompts and debug and refine your code with the help of AI.

Jul 1st 2026
2 Weeks
Programming Artificial Intelligence HTML
Details
Google Cloud Platform Fundamentals: Core Infrastructure (Coursera) Coursera
Google

Google Cloud Platform Fundamentals: Core Infrastructure (Coursera)

Security & Networking

This course introduces you to important concepts and terminology for working with Google Cloud Platform (GCP). You learn about, and compare, many of the computing and storage services available in Google Cloud Platform, including Google App Engine, Google Compute Engine, Google Kubernetes Engine, Google Cloud Storage, Google Cloud SQL, and BigQuery. You learn about important resource and policy management tools, such as the Google Cloud Resource Manager hierarchy and Google Cloud Identity and Access Management. Hands-on labs give you foundational skills for working with GCP.

Jun 29th 2026
1 Week
Cloud Google App Engine Machine Learning
Details
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

Business

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Jun 29th 2026
5-12 Weeks
Statistics Charts Analytical Tools
Details
Developing AI Applications on Azure (Coursera) Coursera
LearnQuest

Developing AI Applications on Azure (Coursera)

Data Science

This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms. You'll explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning.

Jun 29th 2026
5-12 Weeks
ML Artificial Intelligence Machine Learning
Details
Big Data Emerging Technologies (Coursera) Coursera
Yonsei University

Big Data Emerging Technologies (Coursera)

CS: Information & Technology Computer Science

Every time you use Google to search something, every time you use Facebook, Twitter, Instagram or any other SNS (Social Network Service), and every time you buy from a recommended list of products on Amazon.com you are using a big data system. In addition, big data technology supports your smartphone, smartwatch, Alexa, Siri, and automobile (if it is a newer model) every day. The top companies in the world are currently using big data technology, and every company is in need of advanced big data technology support. Simply put, big data technology is not an option for your company, it is a necessity for survival and growth.

Jun 29th 2026
5-12 Weeks
Big Data Data Management Hadoop
Details
Introduction to Big Data (Coursera) Coursera
University of California, San Diego

Introduction to Big Data (Coursera)

Statistics & Data Analysis Data Science

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!

Jun 29th 2026
3 Weeks
Big Data Data Analysis Hadoop
Details
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera)

Health & Society Science

In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics.

Jun 29th 2026
5-12 Weeks
Network Analysis Big Data
Details