To prepare the next generation of product managers to compete in the AI-driven workforce of tomorrow, lifelong learning pioneer Udacity is announcing a new learning partnership with San Francisco-based machine learning and artificial intelligence company Figure Eight, an Appen company. Today, the two companies are announcing their collaboration on the AI Product Manager Nanodegree program, a course designed to teach students how to build AI-powered products and how to bring value to their business using AI.
“When product managers adopt and embrace AI to develop products with AI at their core, they can create an impressive impact on their bottom line and on the real world as a whole,” said Alyssa Simpson Rochwerger, Vice President of Product, Figure Eight. “We built this course with Udacity to empower professionals to help build amazing products using AI, but aren’t coming to the table with a deep technical background.”
Companies are amassing huge amounts of data and hiring small armies of data scientists and engineers to store and analyze it. However, there’s often a disconnect between technical data professionals and business decision makers. More and more, companies are looking for people who can bridge the gap and unlock the real value of big data by crafting impactful narratives supported by data visualizations. Recent Linkedin research even pointed to data presented as one of the top 10 most in-demand skills. To help people develop these important skills, Udacity is excited to announce the Data Visualization Nanodegree program.
“The ability to communicate effectively with data sets you apart professionally. Plenty of people can do the technical work or put together a fancy presentation. Creating clear data visualizations to support your viewpoints, and using your analyses to tell a narrative or make a recommendation, is a crucial 21st-century data skill” – Sam Nelson, Head of Content Strategy at Udacity.
Real-world projects are integral to every Udacity Nanodegree program. They become the foundation for a job-ready portfolio to help learners advance their careers in their chosen field. The projects in the Data Engineer Nanodegree program were designed in collaboration with a group of highly talented industry professionals to ensure learners develop the most in-demand skills. Every project in a Nanodegree program is human-graded by a member of Udacity’s mentor and reviewer network. These project reviews include detailed, personalized feedback on how learners can improve their work. Graduates consistently rate projects and project reviews as one of the best parts of their experience with Udacity.
The Project Journey
The projects will take you on a journey where you’ll assume the role of a Data Engineer at a fabricated data streaming company called “Sparkify” as it scales its data engineering in both size and sophistication. You’ll work with simulated data of listening behavior, as well as a wealth of metadata related to songs and artists. You’ll start-, working with a small amount of data, with low complexity, processed and stored on a single machine. By the end, you’ll develop a sophisticated set of data pipelines to work with massive amounts of data processed and stored on the cloud.
Udacity has Programming for Data Science nanodegeree programs in both Python and R.Start Learning Python
Start Learning R
Udacity is excited to announce the release of a new R Programming track within the popular Programming for Data Science Nanodegree program. Now students can choose to learn either Python or R as they begin their journey into data science. Both the Python and R tracks also include courses on SQL, Command Line, and GitHub.
Udacity’s Data Science track begins with programming as it’s an essential skill for most data science and analytics work. In terms of popularity in the data science field, R and Python dwarf most other programming languages, and much has been written comparing the two. In fact, if you Google “r vs. python” you’ll get over 55,000 results! So rather than give just one more opinion, we’ve pulled together some of the key takeaways on the topic to help you make a decision on which language to learn.
For both R and Python, I’ll begin by introducing the programming language then describing some of the most significant advantages to using it.
What is R?
The programming language R was first released by a group of statisticians in 1994 and has since become widely used by statisticians, researchers, and data analysts around the world. It was created “for statisticians, by statisticians,” and has a wide array of built-in functions and third-party libraries enabling data scientists to accomplish tasks at every step of the data science process.
The numbers paint a pretty compelling picture, and all the press articles certainly add to the sense of excitement. Everywhere you look, there’s another story about the incredible demand for skilled data scientists. Just two weeks ago, a story from Bloomberg noted that job listings for data scientists on Indeed.com have increased 75% in just three years. Glassdoor has named Data Scientist the best job in the U.S. three years in a row. IBM is predicting a demand increase of nearly 30% in the next two years.
In short, it is an incredible time to become a Data Scientist.
That’s easier said than done, of course. But that’s where Udacity comes in. No matter where your skills and experience are today, we offer a point-of-entry into the world of data, and at Udacity, every data learning path ends with you being ready for success in the field.
Whether you want to master data science programming with Python and SQL, launch a Data Analyst career, or explore business and predictive analytics, Udacity offers world-class programs, expert instructors, and the opportunity to start building relevant skills right away. We’ve partnered with industry leaders like Tableau, Kaggle, and IBM Watson, to ensure you’re learning the in-demand skills recruiters and hiring managers are looking for.
In this post, I’ll walk you through all the Nanodegree programs in our School of Data Science. I’ll show you what each covers, make clear how they connect, and help you choose the program that’s right for you. In the process, I’ll describe the projects you’ll build, and the skills you’ll learn.
Let’s get started!
According to a recent report by DOMO, the world produces 2.5 million terabytes of data per day. Data is quickly becoming the lifeblood of digital transformation, and companies are scrambling to re-invent themselves as data-driven organizations. That’s why, according to Indeed and Glassdoor, the ratio of data engineer to data scientist job openings is roughly four-to-one.
Companies can’t find enough data engineers to store, organize, and manage their ever-increasing amount of data.
Data engineers are responsible for making data accessible to all the people who use it across an organization. That could mean creating a data warehouse for the analytics team, building a data pipeline for a frontend application, or summarizing massive datasets to be more user-friendly.
Today, we are excited to announce the Data Engineer Nanodegree Program. Students who take this program will learn the technical skills required to become a data engineer. With the launch of this program, anyone with an Internet connection (and the relevant background and skills) will be able to enroll. Companies all over the world are looking for data engineers and our goal is to help anyone who wishes to land a job in the field can do so.
What IS Data Science?
Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science. This can be daunting if you’re new to data science, but keep in mind that different roles and companies will emphasize some skills over others, so you don’t have to be an expert at everything. There are potential data science jobs for lots of different experience levels.