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Computer Vision Nanodegree Program

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Course Report - Computer Vision 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

3 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

Advanced

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Effort

15 hours per week

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Teaching Type

Self Paced

Course Description

This program will help you to improve your machine learning and deep learning skills by adding computer vision theory and programming techniques. This computer vision knowledge can be used in many applications, including image and video processing and autonomous vehicle navigation. Medical diagnostics and smartphone apps are just a few examples. The program does not prepare you to work in a particular career. Instead, it will help you to increase your computer vision skills and deepen your learning. This term consists of three courses and three projects. Each course is described below. A project is a great way to show your skills. Each project will add to your impressive portfolio, which will demonstrate to potential employers that you are an expert in computer vision and 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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Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Intermediate knowledge of machine learning techniques

Intermediate statistics background

Intermediate to advanced Python experience You are familiar with object-oriented programming

You are familiar with probability

You can describe backpropagation, and have seen a few examples of neural network architecture (like a CNN for image classification)

You can write nested for loops and can read and understand code written by others

You have seen or worked with a deep learning framework like TensorFlow, Keras, or PyTorch before

What You Will Learn

Discover how to combine CNN and RNN networks to build an automatic image captioning application

Learn how to locate an object and track it over time

Learn to apply deep learning architectures to computer vision tasks

Learn to extract important features from image data

Master computer vision

apply deep learning techniques to classification tasks

image processing essentials

Target Students

This Nanodegree program accepts all applicants regardless of experience and specific background

Course Instructors

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Alexis Cook

Curriculum Lead

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.
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Cezanne Camacho

Curriculum Lead

Cezanne is an expert in computer vision with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she’s applied computer vision a...
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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.
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Juan Delgado

Content Developer

Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large a...
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