Welcome to the Nanodegree program

Introduction to Software Engineering

In this lesson, you’ll write production-level code and practice object-oriented programming, which you can integrate into machine learning projects.

Software Engineering Practices Pt I

Software Engineering Practices Pt II


Portfolio Exercise: Upload a Package to PyPi

Part 15-Module 01-Lesson 06_Web Development

Portfolio Exercise: Deploy a Data Dashboard

Introduction to Data Engineering

ETL Pipelines

Introduction to NLP

Learn Natural Language Processing one of the fields with the most real applications of Deep Learning

Machine Learning Pipelines

Disaster Response Pipeline

Project1: Disaster Response Pipeline

Part 17-Module 02-Lesson 01_Concepts in Experiment Design

Part 17-Module 02-Lesson 02_Statistical Considerations in Testing

Statistical Considerations in Testing

Part 17-Module 02-Lesson 03_AB Testing Case Study

A/B Testing Case Study

Part 17-Module 02-Lesson 04_Portfolio Exercise Starbucks

Part 17-Module 03-Lesson 01_Introduction to Recommendation Engines

Part 17-Module 03-Lesson 02_Matrix Factorization for Recommendations

Part 17-Module 04-Lesson 01_Recommendation Engines

Part 17-Module 05-Lesson 01_Upcoming Lesson

Sentiment Prediction RNN

Convolutional Neural Networks

Transfer Learning

Weight Initialization


Job Search

Find your dream job with continuous learning and constant effort

Refine Your Entry-Level Resume

Craft Your Cover Letter

Optimize Your GitHub Profile

Develop Your Personal Brand

01. Introduction

Why should a data scientist learn web development?

In this course, you are going to use Flask to build a data dashboard. You might be thinking that you already have good tools for visualizing data such as matplotlib, seaborn, or Tableau.

However, the web development skills you’ll learn in this lesson will prepare you for building other types of data science applications. Data scientists are increasingly being asked to deploy their work as an application in the cloud.

For example, consider a project where you build a model that classifies disaster relief messages into categories. With your web development skills, you could turn that model into a web app where you would input a message and display the resulting message category.

As another example, consider a system that recommends movies based on a user’s preferences. Part of the recommendation engine could include a web application that displays recommended products based on a userid. What you learn in this course will set you up for building the web app portion of the recommendation engine.