Gain Knowledge of Computer Vision Theory with this Online Nanodegree Program by Udacity

Govind Savara

02 January 2023

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Course Overview

Computer Vision Udacity Nanodegree Program will help you to improve your Machine Learning (ML) and Deep Learning (DL) skills by teaching advanced computer vision theory and programming techniques. Computer vision supports the following domain models:

applications, including image and video processing
autonomous vehicle navigation.

All those who have intermediate to advanced experience in Python can enroll in this course. This Udacity computer vision Nanodegree program accepts all applicants regardless of experience and specific background. Industries, tech firms, start-ups and government agencies are all fields where one can work. You will be able to perform all the required computer vision tasks with ease.

The instructors, Cezanne Camacho, Alexis Cook, Jay Alammar, and Luis Serrano, explained the concepts very clearly and gave appropriate examples to aid understanding.

"This course helped me in understanding image detection and image processing in detail. I would recommend this course to novices as it teaches popular industry-related skills which you can leverage to your advantage in the workplace."

- Govind Savara

Course Structure

The certification program is a self-paced intermediate-level course taught online. It has a duration of 3 months and requires learners to put in 15 hours per week. Some of the critical areas you develop an interest in are Neural Networks, computer vision with Deep Learning, ML, and more.

In the first month, the concepts of machine learning, model training and prediction are introduced. The course teaches image processing concepts and how to use different methods to detect images and extract important features from image data. All these learnings are implemented in the 1st project of Facial Keypoint Detection, where learners can detect all the key points (mouth, nose, eyes and facial output).

In the following months, the course teaches how to use computer vision Deep Learning concepts and utilize Neural networks to train and predict models. This includes important concepts like backtracking to optimize models and using RNN and CNN networks for image captioning. Also, learners understand how to detect the motion of objects and their movement tracking. These concepts can be utilized in self-driving car systems to follow a proper path to the destination. A computer vision project at the end lets the learner detect the end point of a robot on a farm with tracking and localization. The complete course uses PyTorch for computer vision models.

Technically, you will learn computer vision through the following 3 prime modules, namely:

Module 1: Introduction to Computer Vision
Module 2: Advanced Computer Vision and Deep Learning
Module 3: Object Tracking and Localization

Insider Tips

In order to get the best out of this course, I have included some important tips below that I think you might find useful:

Assessments or Grading Criteria

The assessments involve completing assignments and various projects. There are three projects, and the assessment team reviews the projects and determines whether the goals are achieved.

They provide feedback and suggestions to improve our project accuracy. And, if any project is not up to the mark, we can improve our learning by redoing the assignment.

Prerequisites or Requirements

You should have intermediate to advanced Python experience as well as Object-Oriented Programming.
You should know how to write Nested for loops and how to read and understand code written by others.
You should have an intermediate statistics background.
You should have an intermediate knowledge of ML techniques.
You should be able to describe backpropagation and have seen a few examples of neural network architecture (like a CNN for image classification).
You should have previously seen or worked with a deep learning framework like TensorFlow, Keras, or PyTorch.

Career Assistance

This certification course will help the learners grow their skill set. It is the best computer vision course which will help learners with their resume profiles and will offer a chance to converse with the career guide for resolving their queries. The course will provide an appropriate career path to individuals on how to become a computer expert.

The course includes a mentor who guides us in the right direction for our project goals. The learners get assistance with job related queries.

Final Take

Currently, I am working as a software developer in Marktine Technology Solution Pvt. Ltd.. This course helped me in understanding image detection and image processing in detail. I would recommend this course to novices as it teaches popular industry-related skills that will give you an advantage in this domain.

Key Takeaways

Gain knowledge of computer vision which can be used in many applications, including image and video processing and autonomous vehicle navigation

Develop skills in Neural Networks, Deep Learning, ML, Computer Vision, and more

Use Deep Learning techniques like RNN and CNN in Image captioning projects

Get assistance in finding jobs

Course Instructors

Govind Savara

Senior Software Developer

Experienced Programmer Analyst with a demonstrated history of working in the US health care industry. Strong working experience in Python, Database and Angular with a keen interest in Artificial Intelligence and Deep Learning.