Coursera

Applied Data Science Capstone (Coursera)

Offered by IBM,
Applied Data Science Capstone (Coursera)

This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data. Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings.

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

If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course.
This course is part of multiple programs
This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

Syllabus

WEEK 1
Introduction
In this module, you will learn about the scope of this capstone course and the context of the project that you will be working on. You will learn about different location data providers and what location data is normally composed of. Finally, you will be required to submit a link to a new repository on your Github account dedicated to this course.

WEEK 2
Foursquare API
In this module, you will learn in details about Foursquare, which is the location data provider we will be using in this course, and its API. Essentially, you will learn how to create a Foursquare developer account, and use your credentials to search for nearby venues of a specific type, explore a particular venue, and search for trending venues around a location.

WEEK 3
Neighborhood Segmentation and Clustering
In this module, you will learn about k-means clustering, which is a form of unsupervised learning. Then you will use clustering and the Foursquare API to segment and cluster the neighborhoods in the city of New York. Furthermore, you will learn how to scrape website and parse HTML code using the Python package Beautifulsoup, and convert data into a pandas dataframe.

WEEK 4
The Battle of Neighborhoods
In this module, you will start working on the capstone project. You will clearly define a problem and discuss the data that you will be using to solve the problem.

WEEK 5
The Battle of Neighborhoods (Cont'd)
In this module, you will carry out all the remaining work to complete your capstone project. You will submit a report of your project for peer evaluation.

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

Related Courses

Foundations: Data, Data, Everywhere (Coursera) Coursera
Google

Foundations: Data, Data, Everywhere (Coursera)

Statistics & Data Analysis Data Science

This is the first course in the Google Data Analytics Certificate. These courses will equip you with the skills you need to apply to introductory-level data analyst jobs. Organizations of all kinds need data analysts to help them improve their processes, identify opportunities and trends, launch new products, and make thoughtful decisions. In this course, you’ll be introduced to the world of data analytics through hands-on curriculum developed by Google. The material shared covers plenty of key data analytics topics, and it’s designed to give you an overview of what’s to come in the Google Data Analytics Certificate. Current Google data analysts will instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 16th 2026
5-12 Weeks
Data SQL Spreadsheets
Details
Introduction to HTML5 (Coursera) Coursera
University of Michigan

Introduction to HTML5 (Coursera)

CS: Programming

Thanks to a growing number of software programs, it seems as if anyone can make a webpage. But what if you actually want to understand how the page was created? There are great textbooks and online resources for learning web design, but most of those resources require some background knowledge. This course is designed to help the novice who wants to gain confidence and knowledge. We will explore the theory (what actually happens when you click on a link on a webpage?), the practical (what do I need to know to make my own page?), and the overlooked (I have a page, what do I do now?).

Jun 15th 2026
3 Weeks
Programming HTML HTML5
Details
Data Science Companion (Coursera) Coursera
MathWorks

Data Science Companion (Coursera)

Statistics & Data Analysis Data Science

The Data Science Companion provides an introduction to data science. You will gain a quick background in data science and core machine learning concepts, such as regression and classification. You’ll be introduced to the practical knowledge of data processing and visualization using low-code solutions, as well as an overview of the ways to integrate multiple tools effectively to solve data science problems.

Jun 19th 2026
4 Weeks
MATLAB Machine Learning Regression
Details
The Structured Query Language (SQL) (Coursera) Coursera
University of Colorado Boulder

The Structured Query Language (SQL) (Coursera)

Data Science

In this course you will learn all about the Structured Query Language ("SQL".) We will review the origins of the language and its conceptual foundations. But primarily, we will focus on learning all the standard SQL commands, their syntax, and how to use these commands to conduct analysis of the data within a relational database. Our scope includes not only the SELECT statement for retrieving data and creating analytical reports, but also includes the DDL ("Data Definition Language") and DML ("Data Manipulation Language") commands necessary to create and maintain database objects.

Jun 16th 2026
5-12 Weeks
Databases SQL Data Science
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 15th 2026
3 Weeks
Big Data Data Analysis Hadoop
Details
Practical Machine Learning (Coursera) Coursera
Johns Hopkins University

Practical Machine Learning (Coursera)

Statistics & Data Analysis Data Science

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates.

Jun 15th 2026
4 Weeks
Algorithms Machine Learning Regression
Details
The Data Scientist's Toolbox (Coursera) Coursera
Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

Statistics & Data Analysis Data Science

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 15th 2026
4 Weeks
Data Github Data Analysis
Details
An Introduction to Interactive Programming in Python (Part 1) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 1) (Coursera)

CS: Programming

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Jun 15th 2026
5-12 Weeks
Programming Python Interactive Applications
Details
Hadoop Platform and Application Framework (Coursera) Coursera
University of California, San Diego

Hadoop Platform and Application Framework (Coursera)

Statistics & Data Analysis Data Science

This course is for novice programmers or business people who'd like to understand the core tools used to wrangle and analyze big data. With no prior experience, you'll have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment.

Jun 15th 2026
5-12 Weeks
Big Data Data Analysis Hadoop
Details
Ask Questions to Make Data-Driven Decisions (Coursera) Coursera
Google

Ask Questions to Make Data-Driven Decisions (Coursera)

Statistics & Data Analysis Data Science

This is the second course in the Google Data Analytics Certificate. These courses will equip you with the skills needed to apply to introductory-level data analyst jobs. You’ll build on your understanding of the topics that were introduced in the first Google Data Analytics Certificate course. The material will help you learn how to ask effective questions to make data-driven decisions, while connecting with stakeholders’ needs. Current Google data analysts will continue to instruct and provide you with hands-on ways to accomplish common data analyst tasks with the best tools and resources.

Jun 16th 2026
4 Weeks
Spreadsheets Data Analysis Decision Making
Details