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Time
1 Three-Month Term
Study 10-15 hrs/week and complete in 3 months.
Classroom Opens
January 15, 2019
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Why Take This Nanodegree Program?
Over the course of this program, you’ll become an expert in the main components of Natural Language Processing, including speech recognition, sentiment analysis, and machine translation. You’ll learn to code probabilistic and deep learning models, train them on real data, and build a career-ready portfolio as an NLP expert!
Work on the Most Cutting-Edge Applications
Natural Language Processing is at the center of the AI revolution, as it provides a tool for humans to communicate with computers effectively. The industry is hungry for highly-skilled specialists, and you’ll begin making an impact right away.
Focus on Putting Your Skills to Work
Master Natural Language Processing techniques with the goal of applying those techniques immediately to real-world challenges and opportunities. This is efficient learning for the innovative and career-minded professional AI engineer.
Code Your Own Models
You’ll learn how to build and code natural language processing and speech recognition models in Python. You’ll complete three major natural language processing projects, and build a strong portfolio in the process.
Benefit From Personalized Project Reviews
The most effective way to learn is by having your code and solutions analyzed by AI experts who will give you powerful feedback in order to improve your understanding.
What You Will Learn
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Start mastering Natural Language Processing!
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Prerequisite Knowledge
This program requires experience with Python, statistics, machine learning, and deep learning.See detailed requirements.
Introduction to Natural Language Processing
Learn text processing fundamentals, including stemming and lemmatization. Explore machine learning methods in sentiment analysis. Build a speech tagging model.
Part of Speech TaggingComputing with Natural Language
Learn advanced techniques like word embeddings, deep learning attention, and more. Build a machine translation model using recurrent neural network architectures.
Machine TranslationCommunicating with Natural Language
Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.
Speech Recognizer
“This new era of systems is one that is not about programmes. They can talk or ingest natural language, they can understand what they read and they can help us make decisions about areas to explore and finding answers.”— Steve Abrams, VP, Chief Data Scientist, United Technologies
Learn with the best
Luis Serrano
Curriculum Lead
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in Mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Jay Alammar
Instructor
Jay has a degree in computer science, loves visualizing machine learning concepts, and is the Investment Principal at STV, a $500 million venture capital fund focused on high-technology startups.
Arpan Chakraborty
Instructor
Arpan is a computer scientist with a PhD from North Carolina State University. He teaches at Georgia Tech (within the Masters in Computer Science program), and is a coauthor of the book Practical Graph Mining with R.
Dana Sheahen
Instructor
Dana is an electrical engineer with a Masters in Computer Science from Georgia Tech. Her work experience includes software development for embedded systems in the Automotive Group at Motorola, where she was awarded a patent for an onboard operating system.
Student Reviews
Top Reviews
(44)
5 stars
52.3%
4 stars
27.3%
3 stars
11.4%
2 stars
2.3%
1 stars
6.8%
Shukhrat K.
Overall, great course and content. I learned a lot about RNNs, which I was really looking forward to. To make the program even better (at least for me), I would prefer having more mini projects , where one could practice building particular RNN architectures one by one to really get a detailed grasp of how they work and what their advantages and disadvantages are, before actually jumping into the course project.
Nidhin P.
A wonderful overview of NLP techniques. Good overview on state of the art techniques like LSTM, Attention. The last project (voice recognition) was an interesting application of what we learned.
Svetoslav K.
Excellent course!
Hieu M.
awesome
Daniel C.
TL;DR: Enroll in this Program! I enjoyed completing the Udacity Natural Language Processing Nanodegree Program. There are three required projects. Project difficulty ranges from easy to somewhat challenging, depending on your prior experience. Hands-on projects are the most valuable aspect of this Program. When you start the first module, you might wonder why the Program is so expensive. After all, you can find free course materials that covers most of these topics elsewhere on the Web. For me this Program is worth it, and I came up with three reasons that justify the high cost. First, the projects really help you learn the concepts. One caveat is that you should allocate more time than the estimated completion time for all projects. For example, the Automatic Speech Recognition project has a 5 hour estimated completion time. Well, training all the required models takes at least 8 hours on AWS g3.4xlarge EC2 instance, NOT including implementation, testing, and debugging time. Second, the build-in Jupyter workspaces are nice; if you choose, you can submit project within the Udacity workspaces. In addition, the Machine Translation project actually offers the feature to switch between CPU and GPU workspaces. GPU cloud instances can be expensive, and Udacity allocated a generous number of hours for the Machine Translation project. NOTE: The Automatic Speech Recognition project DOESN"T offer any Jupyter workspaces. However, knowing how to setup AWS GPU workspaces from scratch is a valuable skill. I recommend that you budget between 30 to 50 USD to provision your own AWS GPU instances. Finally, the Code Reviews are helpful. The reviewers always pinpoint deficiencies in the submissions. In all cases when I needed to resubmit, it was because I didn't read the instructions carefully. Some reviewers offer more suggestions and recommend more optional improvements than others, so I guess luck has something to do with how much you benefit from Code Reviews. As with all learning, how much you get back is proportional to how much time and effort you invest. I also recommend taking advantage of the optional Extracurricular Modules to maximize value you gain from this Program.
Learn now, pay later
To make it even easier to learn, you can finance your Nanodegree through Affirm.
Flexible Payments
Pay your monthly bill using a bank transfer, check, or debit card.
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Term
Natural Language Processing
$999
OR
as low as
$84
Learn the essentials of natural language processing, including part-of-speech tagging, sentiment analysis, machine translation, and speech recognition.
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Program Details
Why should I enroll in this program?
This program offers a deep dive into modern Natural Language Process techniques. Mastering these skills will prepare you to build applications involving written and spoken language. We’ve collaborated with leading innovators such as IBM and Amazon to create our world-class curriculum, and you’ll learn from an instructor team comprised of experts from both Udacity and industry professionals. Massive growth is being predicted for the Natural Language Processing software market, making now the perfect time to enter this field.
What jobs will this program prepare me for?
In this program, you’ll develop and refine specialized skills in natural language processing and voice user interfaces. The curriculum is not designed to prepare you for a specific job; instead, the goal is that you’ll expand your skills in the natural language processing domain. Growth predictions are extremely high for this market, and having these in-demand skills will significantly enhance your ability to advance your AI career.
How do I know if this program is right for me?
If your goal is to become an expert in Natural Language Processing (NLP), this program is ideal for you. Over the course of this program, you’ll become an expert in the main components of NLP, including speech recognition, sentiment analysis, and machine translation. You’ll learn cutting edge probabilistic and deep learning models, code them and train them on real data, and build a career-ready portfolio as an NLP expert!
PROGRAM OVERVIEW - WHY SHOULD I TAKE THIS PROGRAM?
Do I need to apply? What are the admission criteria?
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
What are the prerequisites for enrollment?
To succeed in this Nanodegree program, we recommend you first take any course in Deep Learning equivalent to our Deep Learning Nanodegree program. You also need to be able to communicate fluently and professionally in written and spoken English.
Additionally, you should have the following knowledge:
Intermediate Python programming knowledge, including:
- Strings, numbers, and variables
- Statements, operators, and expressions
- Lists, tuples, and dictionaries
- Conditions & loops
- Generators & comprehensions
- Procedures, objects, modules, and libraries
- Troubleshooting and debugging
- Research & documentation
- Problem solving
- Algorithms and data structures
Basic shell scripting:
- Run programs from a command line
- Debug error messages and feedback
- Set environment variables
- Establish remote connections
Basic statistical knowledge, including:
- Populations, samples
- Mean, median, mode
- Standard error
- Variation, standard deviations
- Normal distribution
Intermediate differential calculus and linear algebra, including:
- Derivatives & Integrals
- Series expansions
- Matrix operations through eigenvectors and eigenvalues
If I do not meet the requirements to enroll, what should I do?
We have a number of courses and programs we can recommend that will help prepare you for the program, depending on the areas you need to address. For example:
ENROLLMENT AND ADMISSION
How is this Nanodegree program structured?
The Natural Language Processing Nanodegree program is composed of one (1) Term of three (3) months. A Term has fixed start and end dates.
To graduate, students must successfully complete four (4) projects, each of which affords you the opportunity to apply and demonstrate new skills that you learn in the lessons. Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
How long is this Nanodegree program?
Access to this Nanodegree program runs for the period noted in the Term length section above.
See the Terms of Services and FAQs for other policies around the terms of access to our Nanodegree programs.
Can I switch my start date? Can I get a refund?
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
How much does the program cost?
The full program consists of one 3-month long term at a cost of USD 799, for a total program cost of USD 999.
Payment is due before the term begins.
I have graduated from the Natural language Processing Nanodegree program but I want to keep learning. Where should I go from here?
If you would like to explore other applications for convolutional and recurrent neural networks, and have an interest in computer vision, then consider enrolling in the Computer Vision Nanodegree program. If you are looking for additional advanced topics in AI, the Robotics Engineer and Self-Driving Car Engineer Nanodegree programs could be ideal for you. And regardless of your future career destination, you’ll find that the Artificial Intelligence Nanodegree program is full of valuable content that will serve you well in almost any AI role.
TUITION AND TERM OF PROGRAM
What software and versions will I need in this program?
You will need a computer running a 64-bit operating system (most modern Windows, OS X, and Linux versions will work) with at least 8GB of RAM, along with administrator account permissions sufficient to install programs including Anaconda with Python 3.5 and supporting packages. Your network should allow secure connections to remote hosts (like SSH). We will provide you with instructions to install the required software packages. Udacity does not provide any hardware or software.