Want to Master Computer Vision? Leverage Udacity's Nanodegree Program for Your Career Growth

Aditya Jyoti Paul

08 June 2023

Add To Wishlist

Course Overview

Computer Vision Nanodegree Program offered by Udacity is an online certification course that aims to provide students with the skills and knowledge needed to build and develop computer vision applications. This program is designed for students who want to enter the field of computer vision or for those who want to enhance their skills and knowledge in this area.

The program consists of courses designed to teach students the fundamentals of computer vision and more advanced topics such as deep learning, convolutional neural networks (CNNs), and object detection. Industry experts with extensive experience in the field of computer vision teach the courses.

The names of the instructors in this program are given below:

Sebastian Thrun
Cezanne Camacho
Alexis Cook
Juan Delgado
Jay Alammar
Ortal Arel
Luis Serrano

I found Luis Serrano and Jay Alammar's teaching styles extremely easy to grasp. Cezanne Camacho could explain complicated topics in a simple, lucid language, and Sebastian Thrun's experience with self-driving cars and other visual projects inspired me to pursue the course with unparalleled dedication.

"Overall, the Computer Vision Nanodegree Program offered by Udacity is an excellent choice for students who want to develop their skills and knowledge in computer vision."

- Aditya Jyoti Paul

Course Structure

The courses in this program cover the following topics:

Introduction to Computer Vision

This course introduces computer vision, including image processing, feature extraction, and image segmentation.
Convolutional Neural Networks

This course teaches students how to build and train CNNs for image classification tasks.
Advanced CNNs and Object Detection

This course covers more advanced CNN architectures, such as YOLO and SSD, and the instructors teach students how to use these architectures for object detection.
Deep Learning for Computer Vision

This course covers deep learning techniques for computer vision, including CNNs, recurrent neural networks, and generative adversarial networks.
Applications of Computer Vision

This course covers various applications of computer vision, including facial recognition, image retrieval, and autonomous vehicles.

The program includes hands-on projects and assignments that allow students to apply the concepts they learn in each course. Students also have access to a community of peers and mentors who can provide guidance and support throughout the program.

Overall, the Computer Vision Nanodegree Program offered by Udacity is an excellent choice for students who want to develop their skills and knowledge in computer vision. The program covers various topics, from the fundamentals of computer vision to advanced deep learning techniques and provides hands-on experience with real-world projects.

Insider Tips

To get the best out of this course, I have included some important tips that you might find useful.

Practice Consistently

Consistent practice enhances learning. When you practice something regularly, you reinforce the neural pathways in your brain responsible for that skill. The course includes hands-on exercises and case studies to practice applying the concepts and techniques covered. Take advantage of these opportunities to reinforce learning and build practical skills.
Engage Actively with the Course Material

Take notes, highlight key concepts and techniques, and ask questions to reinforce your understanding of the material. Engaging with the course material can help you retain information better and apply it more effectively
Capstone Project

The capstone project, “Landmark Detection and Tracking,” included the below topics:
- Facial Keypoint Detection: Face Expression detection from a position of the key points.
- Automatic Image Captioning: Using a combination of Convolutional and Recurrent Neural Nets.
- Object Tracking and Localization: Locating an object and tracking it over time. These techniques are used in various moving systems, such as self-driving car navigation and drone flight.
Assessment/Grading Assignment

To the best of my knowledge, there is no limit on how many times you can take an assessment. The assessments were thorough and had amazing real-world projects and a capstone project. You can complete the projects at your own pace; if you fail to do so in the period, then you most probably need to reach out to your course admin requesting an extension and might have to pay extra. I am unsure as I never faced this issue, and enough content was provided through the lectures and content to support a student appearing for the assessment.

Final Take

I am currently a Sr Tech Architect at Reflective AI. This course has given me real-world skills and actionable experience for this role. This course will benefit anyone seeking a detailed hands-on, and realistic learning program to get into Computer Vision either as an Engineer or as a Research Scientist. I was selected as the recipient of the Facebook-Udacity scholarship program, which enabled me to pursue this course for free. Previously, I had completed all of the Deep Learning specializations that existed till 2020 from deeplearning.ai and wanted a more challenging and pragmatic course; hence, I opted for this course, which was a great fit.

You can do Andre Ng's Deep Learning course, Udacity Deep Learning, or anything else available. I started with Andrew Ng's Deep Learning Specialization. The course is still relevant in 2023, and after the course, you can pursue both engineering and research careers, though more training would be necessary for both. If you are an absolute beginner with no Machine Learning (ML) knowledge, this course is no magic bullet to give you your dream job but certainly a step in the right direction. If you are an Engineer with some experience in Python/Data Science, this could be an excellent way to segue into your CV role. This course is good enough as it provides more structure. Looking at the prices today, I suggest considering other free alternatives or seeking a scholarship. Except for the fee, I have no inhibitions recommending the course.