Udacity is the only place to offer this kind of opportunity. We have collaborated with the best companies in the field to offer world-class curriculum, expert instructors, and exclusive hiring opportunities. While we do offer students a broad introduction to the field of artificial intelligence, you'll have the opportunity to delve into specializations as you refine your interests and follow your passions. Almost any student anywhere in the world with an internet connection can study the field of artificial intelligence with Udacity.
Term one will introduce the basics of artificial intelligence and allow you to build the foundations you’ll need for further exploration. We’ll start by understanding problem-solving and optimization by looking at game playing and search problems. Then we’ll address planning and reasoning, and finish by reviewing probability, and how to use it to build models.
In term two, you’ll have the option to explore a concentration—something you’re really excited about. You’ll dive deep into applications of artificial intelligence as used to solve real-world problems such as computer vision, natural language processing, and more.
Udacity is developing the Artificial Intelligence Nanodegree program in close partnership with leading experts in the field, including IBM Watson.
We believe the applications of artificial intelligence will be a transformative change to all industries. Graduates of this program will be valuable additions to any team working in the domain of AI, and opportunities exist in healthcare, finance, retail, media, advertising, education, and more.
These roles include System Software Engineer, Machine Learning Engineer, Business Analyst, NLP Software Engineer, Computer Vision Engineer, Artificial Intelligence Researcher, and Automation Engineer. For market salary details, please visit the Paysa module on the Artificial Intelligence Nanodegree home page
Given the advanced nature of the artificial intelligence curriculum, we need to ensure that all enrolled students have the necessary background and experience to succeed. In addition, instructor support and peer learning are critical components of the Nanodegree experience. This approach helps establish a community comprised of learners well-equipped to offer guidance, support, and motivation to one another.
A well-prepared student should have a basic knowledge of linear algebra and calculus, the ability to apply basic probability and statistics, experience implementing computer science algorithms, and some familiarity programming in Python. You should be able to answer the following without too much difficulty:
Given a set of N people on a social network how many possible "friend" relationships (i.e. pairs of distinct people) are there?
What will the following python code output?
def mystery(N): s =  while N > 0: s.append(N % 3) N = N / 3 buf = "" while len(s) > 0: buf += str(s.pop()) return buf print mystery(50)
I have a fair coin and a two-headed coin. I choose one of them with equal probability and I flip it. Given that I flipped a heads, what is the probability that I chose the two-headed coin?
- 1+2+3+...+(N-1) = N(N-1)/2
- 1212, which is 50 written in base 3.
We have a number of courses and programs we can recommend that will help prepare you for the next cohort in April, depending on the areas you need to address. For example:
Though every case is different, our expectation is that the most common reason an applicant would not be selected would be due to skills and experience gaps in an applicant’s background. In that case, the best path forward will be to study in those areas to ensure you’re able to meet the requirements during the next application period. Please see the above list of courses.
Regardless of the reason, if you are not accepted for the current round of admissions, you are eligible to apply again for the next round.
Our free courses are an excellent way to refresh your skills on a particular topic, or address a particular arena where you may need to advance your skills in order to pursue the next stage of your learning. But to benefit from the full measure of what Udacity can do to support your career goals, you’ll want to enroll in the Nanodegree program, where you’ll gain access to expert project review, 1:1 mentorship opportunities, personalized career guidance, and more. The Nanodegree program is also the best way to pursue specializations, as you’ll benefit from exclusive access to unique content.
We’ve structured the Artificial Intelligence Nanodegree program in two complementary terms to accomplish our goal of providing students both a broad understanding of the field, and the opportunity to deeply understand one or more of the specific areas of practice. The first term will focus on AI basics that can be applied across the field. The second term allows you to select the specific concentration you’re interested in pursuing. You may take as many concentration terms as you like, though we ask that you do so one at a time.
It is not. This is a unique, two-term program that requires students to keep pace with their peers throughout the duration of the program. If a student does not complete a term within the term deadline, they will be removed from the program and will need to re-enroll for the full term fee in order to continue.
You can choose to only take Term 1 and not continue with Term 2. You must complete Term 1 in order to enroll in Term 2.
Between instructional content, quizzes, projects, and other course-related activity, we estimate that investing 15 hours per week will enable you to proceed through the program at a successful pace.
You will receive a free four-week extension, which is automatically applied to your account. If you do not complete the term within the extension, you will be removed from the program and will no longer be able to access course content. To resume access to the course, you would need to pay the term fee again.
Yes! Once you complete Term 1, you will be able to enroll in the next available session of Term 2 directly from your classroom menu.
We try to accommodate change requests, but also need to maintain consistent enrollment in each term. Before your start date, you are able to change your start date to a future session. After your start date, your request to change classes will be considered on an exception basis. We do not guarantee that your request will be accommodated, but we will do the best we can to make sure the program fits into your schedule.
While some of the video material is available outside of the program, most of the material will only be available to currently enrolled Nanodegree students. Access to project feedback, instructor support and hiring partners are benefits exclusive to the Nanodegree programs. You must complete a term by the term deadline to maintain access to course content; once you have completed a term, you will have access to course material indefinitely.
No, there is no Nanodegree Plus version of AIND. This Nanodegree program is launching with hiring partners Didi Chuxing & IBM Watson. So while Nanodegree Plus is not an option in this case, hiring partners like these mean our students will have direct and preferential exposure at these companies. Plus, we expect to add more hiring partners over time.
We will not be supporting Connect sessions for the Artificial Intelligence Nanodegree program at this time. While students of this program are of course welcome to attend Connect sessions, we will not be able to provide curriculum support at the sessions, nor will there be session leads on-site who are equipped to provide specific program guidance and input.
You will receive a certificate after you’ve completed both terms of the Nanodegree program.
There is no option to pause your enrollment in AIND, due to the fixed term nature of the program and the need to maintain a consistent and stable student body. If you have a special circumstance that requires more time, please contact Udacity Support.
We do not recommend doing so, though there is no specific prohibition against it. Our main reason for recommending against simultaneous enrollments is the time commitment. These are both intensive, fixed-term programs. They are not self-paced, and it is accordingly critical that students proceed throughout the programs at the necessary rate of progress. In addition, while the programs cover certain shared fundamentals, they do so at different times, and in different ways. To make the most of each program, you’re definitely best served by focusing solely on one program at a time, and fully immersing in the unique structure and pacing of each. You can always take one after the other!
To begin, there are definitely overlaps between the three programs, and this is by design. We want you to be really prepared for the fields in question, and to achieve this requires both mastering shared fundamentals, as well as going deep into each program’s unique curriculum to understand specific applications of each technology.
Our approach to machine learning focuses largely on algorithmic methods of determining patterns and equations from large data sets in order to “teach” machines to act without being pre-programmed to do so, and to then improve their own performances through repetition/experience, with an end goal of building and implementing more efficient systems. As an example of machine learning in action, a movie might be recommended to you because you liked similar ones, and those were deemed similar because a big data base has those patterns in it based on what other people liked.
Our Artificial Intelligence program approaches data more from the standpoint of using the technology to “reason” over data—for example, by comparison to the movie example above, a more cognitive AI solution might be one that could analyze a new movie and then "reason"—based on its components— as to whether or not you would like it given other movies you liked. When this program delves into specializations in the second term, you begin to explore applications of artificial intelligence as used to solve real-world problems such as computer vision, natural language processing, and more.
Our Self-Driving Car Nanodegree program incorporates elements of both machine learning and artificial intelligence, in the service of a specific application: autonomous vehicles. For example, Term 1’s curriculum includes segments focused on both deep learning, and computer vision.
When it comes to deciding which program to enroll in, it can be helpful to “begin at the ending”; that is to say, think about where you’d like to be after you graduate, and how you see yourself implementing what you’ve learned. Do you want to help build systems that grow progressively more efficient through the use of machine learning algorithms? Do you want to help build “smart machines” of all different kinds? Do you want to specifically build autonomous vehicles? How you answer these questions will help you choose which program to pursue.
When we use the term "deadline" with regards to Nanodegree program projects, we use it in one of two ways:
It is very important to understand the distinctions between the two, as your progress in the program is measured against the deadlines we've established. Please see below for an explanation of what each usage means.
In order to graduate a term, you must submit all projects by the last day of the term and pass all projects once they are reviewed by a Udacity Reviewer (the review may take place after the last day of the term). Passing a project means a Udacity Reviewer has marked a project as "Meets Specifications."
If you do not submit all projects by the end of the term and also pass all projects once they are reviewed:
You will receive a 4-week extension to complete any outstanding projects. You will receive this extension once per term. Once you submit and pass all projects, you can enroll in the next term, which will potentially be with a later class. If you do not submit and pass all projects within the 4-week extension, you will be removed from the program and will need to pay for future access to course content.
The deadlines you see in your classroom are suggestions for when you should ideally pass each project. They are meant to help keep you on track so that you maintain an appropriate pace throughout the program–one that will see you graduate on time!
Please note that you can re-submit any projects that receive a grade of Needs Revisions. There are no penalties if you miss these deadlines. However, you will be at risk of not passing all projects on time if you miss these deadlines, and fall behind, so it is a recommended best practice to try and meet each suggested deadline.
This Nanodegree program consists of two terms of three months each. Students must complete the full six months to earn their credential and graduate. Each term costs $800, paid at the beginning of each term.
Given the extended curriculum and the student-selected specialization, it is critical that we know exactly how many students we’ll be supporting and teaching. It’s important that this student body remains consistent and stable throughout the duration of the program as they work together as a group.
There is no free trial period for this program.
Artificial Intelligence Nanodegree program graduates are not eligible to receive this tuition refund upon completion of their studies.
We do not have any scholarships or financial aid currently available.
Our team is actively working with a wide range of organizations to secure additional scholarships for upcoming terms.
Please complete this application form if you'd like to be considered for future scholarships. When answering the questions, please provide details and be specific so we have sufficient information when reviewing your application.
We look forward to considering your application as new scholarship opportunities emerge.
Since enrollment in future terms depends on completion of prior terms, you will not be automatically enrolled in the following term. Once you complete a prior term, you will unlock the next term for purchase directly in your classroom menu.
You can enroll in Term 2 directly from your classroom menu. Once you complete Term 1, you will be eligible to enroll in all future Term 2 sessions.
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