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Deep Learning Nanodegree Program

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Course Report - Deep Learning Nanodegree Program

Course Report

Find detailed report of this course which helps you make an informed decision on its relevance to your learning needs. Find out the course's popularity among Careervira users and the job roles that would find the course relevant for their upskilling here. You can also find how this course compares against similar courses and much more in the course report.

Course Features

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Duration

4 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

10 hours per week

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Teaching Type

Self Paced

Course Description

Learn how to use PyTorch, a deep learning framework that teaches you how to create and implement neural networks. Learn how to make convolutional networks that recognize images, recurrent networks that generate sequences, and generative adversarial network for image generation accessible via a website.

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Highlights

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Rating & Reviews

Top 30 Percentile

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Pedagogy

Top 1 Percentile

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Career Impact

Top 5 Percentile

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Course Credibility

Top 1 Percentile

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Parameters

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Course Credibility

Delivered through Udacity a renowned institution in the field, this course offers a comprehensive learning experience.

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Pedagogy

Designed for newcomers to Deep Learning, this course provides a tailored and comprehensive overview, facilitating effective learning and understanding of the subject. It caters to beginners' needs, ensuring a smooth and engaging introduction to the Deep Learning field. An exceptional course in Deep Learning, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

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Career Impact

This course is exceptional, ranking among the top 5 percentile in Deep Learning for its significant career impact and excellent job assistance. Learners benefit from valuable career opportunities and support, enabling them to secure relevant positions and excel in the industry. The course's dual focus on career impact and job assistance enhances its value, making it an ideal choice for individuals seeking to advance their careers and succeed in the Deep Learning field.

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Rating & Reviews

This highly acclaimed course is among the top-rated in Deep Learning, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Deep Learning.

Course Overview

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Job Assistance

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Personlized Teaching

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International Faculty

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Post Course Interactions

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Hands-On Training

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

This program has been created specifically for students who are interested in machine learning, AI, and/or deep learning, and who have a basic working knowledge of Python programming Outside of that Python expectation, it's a very beginner-friendly progra

What You Will Learn

Learn to build the deep learning models that are revolutionizing artificial intelligence

Neural Networks

Convolutional Neural Networks

Recurrent Neural Networks

Deploying a Sentiment Analysis Model

Target Students

This Nanodegree program accepts everyone, regardless of experience and specific background

Course Instructors

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Mat Leonard

Instructor

Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.
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Luis Serrano

Instructor

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.
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Cezanne Camacho

Curriculum Lead

Cezanne is a computer vision expert with a Masters in Electrical Engineering from Stanford University. As a former genomics and biomedical imaging researcher, she’s applied computer vision and deep learning to medical diagnostics.
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Alexis Cook

Instructor

Alexis is an applied mathematician with a Masters in computer science from Brown University and a Masters in applied mathematics from the University of Michigan. She was formerly a National Science Foundation Graduate Research Fellow.

Corporate Sponsors

Course Reviews

Average Rating Based on 6 reviews

5.0

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