At 10-15 hrs/week
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This program requires experience with Python, statistics, machine learning, and deep learning.See detailed requirements.
Learn text processing fundamentals, including stemming and lemmatization. Explore machine learning methods in sentiment analysis. Build a speech tagging model.Part of Speech Tagging
Learn advanced techniques like word embeddings, deep learning attention, and more. Build a machine translation model using recurrent neural network architectures.Machine Translation
Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.Speech Recognizer
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Personal career coach and
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 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 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 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.
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.
This program is the best and well coordinated i have seen so far. The program is very concise, gives equal weightage to theoretical concepts and their practical applications. I am a data scientist who recently got the opportunity to work in NLP and was looking for a program who can help and guide me moving into this unknown domain. The program duration was apt for me to plan my workload and concentrate on this program. Thanks to this program and udacity team that i am able to understand the concepts and adding value to my work.
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.
I finally understand neural nets and the fundamentals of NLP. I have tried many resources and even though some of the classes here were simply notebooks but the fact that they have gathered those resources in this order and provided readings and other resources has a great impact on the learning curve.
The Natural Language Processing Nanodegree is definitely challenging and goes through some of the intricate problems one might encounter as an NLP engineer. Provides easy to understand videos at a high level, but provides literature and extra reading material to understand the fundamentals.
I have experience in NLP, so I can easily notice the clarity in which you guys explain relatively complex concepts from HMM and Viterbi (especially when someone is getting started). I think the quality of the program is good, and I'm excited to see the rest of the material.
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.
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.
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!
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
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:
Basic shell scripting:
Basic statistical knowledge, including:
Intermediate differential calculus and linear algebra, including:
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:
The Natural Language Processing Nanodegree program is comprised of content and curriculum to support three (3) projects. We estimate that students can complete the program in three (3) months, working 10 hours per week.
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.
Please see the Udacity Program FAQs for policies on enrollment in our programs.
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.
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.