Certificate Course on

Computer Vision

Learn to build and deploy Computer Vision and Deep Learning Applications using Convolutional Neural Networks, Keras, TensorFlow 2, and OpenCV

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Self-Paced Online

Format

3 Months

Duration

12+

Projects

CloudxLab

Certificate

8,500+

Learners

About the Course

The certification course on Computer Vision is a self-paced online course. This gives you complete freedom about your schedule and convenience.This course has over 50+ hours of self-paced learning.

Additionally, this course comes with our exclusive lab access to gain the much needed hands-on experience to solve the real-world problems.

Upon successfully completing the course, you will get the certificate from CloudxLab which you can use for progressing in your career and finding better opportunities.

Program Highlights

Certificate of Completion by CloudxLab
50+ Hours of Self-Paced Training
Work on about 12+ projects to get hands-on experience

Timely Doubt Resolution
Best In Class Curriculum
Cloud Lab Access

Start Learning Today

Enroll Now Request a Callback

Our Students Work At

Certificate

What is the certificate like?

CloudxLab Certificate

Why Cloudxlab?

CloudxLab is a team of developers, engineers, and educators passionate about building innovative products to make learning fun, engaging, and for life. We are a highly motivated team who build fresh and lasting learning experiences for our users. Powered by our innovation processes, we provide a gamified environment where learning is fun and constructive. From creative design to intuitive apps we create a seamless learning experience for our users. We upskill engineers in deep tech - make them employable & future-ready.

Programming Languages and Tools

Hands-on Learning

Gamified Learning Platform

Auto-assessment Tests

No Installation Required

Mentors / Faculty

Sandeep Giri

Founder at CloudxLab

Past: Amazon, InMobi, D.E.Shaw

Abhinav Singh

Co-Founder at CloudxLab

Past: Byjus

Praveen Pavithran

Co-Founder at Yatis

Past: YourCabs, Cypress Semiconductor

Curriculum

50+

Hours of Self-Paced Training

Days of Lab Access

12+

Projects

8K+

Learners

Download Curriculum

Foundation: 1. Introduction to Linux

2. Introduction to Python

3. Hands-on using Jupyter on CloudxLab

4. Overview of Linear Algebra

5. Introduction to NumPy & Pandas
1. OpenCV: 1. Introduction to OpenCV

2. OpenCV Basics

3. OpenCV Basic Image Processing

4. OpenCV Histograms

5. Blurring with OpenCV

6. Thresholding with OpenCV

7. Detecting moving objects in Video with OpenCV

8. Edge Detection with OpenCV
2. Introduction to Artificial Neural Networks: 1. From Biological to Artificial Neurons

2. Implementing MLPs using Keras with TensorFlow Backend

3. Fine-Tuning Neural Network Hyperparameters
3. Training Deep Neural Networks: 1. The Vanishing / Exploding Gradients Problems

2. Reusing Pretrained Layers

3. Faster Optimizers

4. Avoiding Overfitting Through Regularization

5. Practical Guidelines to Train Deep Neural Networks
4. Custom Models and Training with Tensorflow: 1. A Quick Tour of TensorFlow

2. Customizing Models and Training Algorithms

3. Tensorflow Functions and Graphs
5. Loading and Preprocessing Data with TensorFlow: 1. Introduction to the Data API

2. TFRecord Format

3. Preprocessing the Input Features

4. TF Transform

5. The TensorFlow Datasets (TDFS) Projects
6. Convolutional Neural Networks: 1. The Architecture of the Visual Cortex

2. Convolutional Layer

3. Pooling Layer

4. CNN Architectures

5. Classification with Keras

6. Transfer Learning with Keras

7. Object Detection

8. YOLO

Projects

Project 1.
Churn Email Inbox with Python

Churn the mail activity from various individuals in an open source project development team.

Project 2.
Build an Image Classifier in Fashion MNIST dataset

Classify images from the Fashion MNIST dataset using Tensorflow 2, Matplotlib, and Python

Project 3.
Training from Scratch vs Transfer Learning

Learn how to train a neural network from scratch to classify data using TensorFlow 2, and how to use the weights of an already trained model to achieve classification to another set of data.

Project 4.
Working with Custom Loss Function

Create a custom loss function in Keras with TensorFlow 2 backend.

Project 5.
Image Classification with Pre-trained Keras models

Learn how to access the pre-trained models(here we get pre-trained ResNet model) from Keras of TensorFlow 2 to classify images.

Project 6.
Build cats classifier using transfer learning

In this project, you will build a basic neural network to classify if a given image is of cat or not using transfer learning technique with Python and Keras.

Project 7.
Mask R-CNN with OpenCV for Object Detection

Learn how to read a pre-trained TensorFlow model for object detection using OpenCV.

Project 8.
Art Generation Project

Use TensorFlow 2 to generate an image that is an artistic blend of a content image and style image using Neural Style Transfer.

Project 9.
NYSE Stock Closing Price Prediction using TensorFlow 2 & Keras

Predict stock market closing prices for a firm using GRU, a state-of-art deep learning algorithm for sequential data, with Keras and Python.

Project 10.
Sentiment Analysis using IMDB dataset

Create a sentiment analysis model with the IMDB dataset using TensorFlow 2.

Project 11.
Autoencoders for Fashion MNIST

Learn how to practically implement the autoencoder, stacking an encoder and decoder using TensorFlow 2, and depict reconstructed output images by the autoencoder model using the Fashion MNIST dataset.

Project 12.
Deploy Image Classification Pre-trained Keras model using Flask

Learn how to deploy a deep learning model as a web application using the Flask framework.

Enroll Now

Certification Guideline

Complete 100% of the topics of the course along with mandatory(non optional) projects

Share your achievement

Highlight your skills on your resume, LinkedIn, Facebook and Twitter. Tell your friends and colleagues about it.

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Testimonials

“Sessions were great, pace was also very good. Each of the steps were explained well multiple times to ensure everyone understands the concepts. Thanks Sandeep!”

Nitin Nigam

“Thanks a lot,it was great course! I'm happy that you lead in this path to AI/ML/DL.I hope to continue to collaborate with you in future.”

Domenico Flioravanti

“Thank you so much Sandeep for all your great sessions. It will help in our career a lot. Your session is very much explanatory and understandable. Kudos to you.Thanks for all your hard work and time. Definitely, we will recommend all our friends and colleagues to attend your different course.Thanks a ton”

Hemanta Lenka

“I have been using CloudxLab for a while now, and they are amazing! The best part about using CloudxLab is that you do not need to wait for someone to tell you whether what you did was right or not, it is done automatically on the go. The training materials are of top notch quality. If you get stuck, they have a huge community of trainers and learners to help you out with all your doubts. They have a course structure for everyone, whether you are new to programming or are a seasoned programmer, they have something to offer you. And they are affordable too! I would recommend CloudxLab all the time.”

Rajtilak Bhattacharjee

“This course is suitable for everyone. Me being a product manager had not done hands-on coding since quite some time. Python was completely new to me. However, Sandeep Giri gave us a crash course to Python and then introduced us to Machine Learning. Also, the CloudxLab’s environment was very useful to just log in and start practising coding and playing with things learnt. A good mix of theory and practical exercises and specifically the sequence of starting straight away with a project and then going deeper was a very good way of teaching. I would recommend this course to all.”

Kamal Upadhyay

“It has been a wonderful learning experience with CXL. This is one of the courses that will probably stay with me for a significant amount of time. The platform provides a unique opportunity to try hands-on simultaneously with the coursework in an almost real-life coding example. Besides, learning to use algebra, tech system and Git is a good refresher for anyone planning to start or stay in technology. The course covers the depth and breadth of ML topics. I specifically like the MNIST example and the depth to which it goes in explaining each and every line of code. Would definitely recommend the instructor-led course.”

Pratik Sonthalia

“This is one of the best-designed course, very informative and well paced. The killer feature of machine/deep learning coursed from CloudxLab is the live session with access to labs for hands-on practices! With that, it becomes easy following any discourse, even if one misses the live sessions(Read that as me!). Sandeep(course instructor) has loads of patience and his way of explaining things are just remarkable. I might have better comments to add here, once I learn more! Great Jobs guys!”

Dhyan Prem

Senior Software Developer at Decision Resources Group

Frequently Asked Questions

What is the validity of course material?: We understand that you might need course material for a longer duration to make most out of your subscription. You will get lifetime access to the course material so that you can refer to the course material anytime.
Do I need to install any software before starting this course?: No, we will provide you with the access to our online lab and BootML so that you do not have to install anything on your local machine
Can I renew my lab subscription?: Yes, you can renew your subscription anytime. Please choose your desired plan for the lab and make payment to renew your subscription.
What do I need to fulfill to get the CloudxLab certificate for the course?: You should complete 100% of the course along with all the given projects in order to be eligible for the certificate.

Kindly note that there is no deadline for CloudxLab courses.
What are the hardware and software requirements?: Course requires a good internet connection and a browser to watch videos and do hands-on the lab. We've configured all the tools in the lab so that you can focus on learning and practising in a real-world cluster.

Certificate Course on

Computer Vision

Learn to build and deploy Computer Vision and Deep Learning Applications using Convolutional Neural Networks, Keras, TensorFlow 2, and OpenCV

Self-Paced Online

3 Months

12+

CloudxLab

8,500+

About the Course

Program Highlights

Certificate of Completion by CloudxLab

50+ Hours of Self-Paced Training

Work on about 12+ projects to get hands-on experience

Timely Doubt Resolution

Best In Class Curriculum

Cloud Lab Access

Start Learning Today

Our Students Work At

Certificate

What is the certificate like?

Why Cloudxlab?

Programming Languages and Tools

Hands-on Learning

Gamified Learning Platform

Auto-assessment Tests

No Installation Required

Mentors / Faculty

Sandeep Giri

Abhinav Singh

Praveen Pavithran

Curriculum

Hours of Self-Paced Training

Days of Lab Access

Projects

Learners

Course on Computer Vision

Projects

Project 1.Churn Email Inbox with Python

Project 2. Build an Image Classifier in Fashion MNIST dataset

Project 3. Training from Scratch vs Transfer Learning

Project 4. Working with Custom Loss Function

Project 5. Image Classification with Pre-trained Keras models

Project 6. Build cats classifier using transfer learning

Project 7. Mask R-CNN with OpenCV for Object Detection

Project 8. Art Generation Project

Project 9. NYSE Stock Closing Price Prediction using TensorFlow 2 & Keras

Project 10. Sentiment Analysis using IMDB dataset

Project 11. Autoencoders for Fashion MNIST

Project 12. Deploy Image Classification Pre-trained Keras model using Flask

Enroll Now

Certification Guideline

Share your achievement

Start Learning

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29

Computer Vision(lifetime course access)+30 days Cloud Lab

118

59

Computer Vision(lifetime course access)+90 days Cloud Lab

158

79

Computer Vision(lifetime course access)+180 days Cloud Lab

or

Subscribe to CloudxLab Premium

34 /mo

17 /mo

Get Access to ALL Courses with One Single Subscription.

Testimonials

Nitin Nigam

Domenico Flioravanti

Hemanta Lenka

Rajtilak Bhattacharjee

Kamal Upadhyay

Pratik Sonthalia

Dhyan Prem

Related Course

Data Science Certification Program by CloudxLab

Artificial Intelligence Course for Managers

Frequently Asked Questions

Project 1.
Churn Email Inbox with Python

Project 2.
Build an Image Classifier in Fashion MNIST dataset

Project 3.
Training from Scratch vs Transfer Learning

Project 4.
Working with Custom Loss Function

Project 5.
Image Classification with Pre-trained Keras models

Project 6.
Build cats classifier using transfer learning

Project 7.
Mask R-CNN with OpenCV for Object Detection

Project 8.
Art Generation Project

Project 9.
NYSE Stock Closing Price Prediction using TensorFlow 2 & Keras

Project 10.
Sentiment Analysis using IMDB dataset

Project 11.
Autoencoders for Fashion MNIST

Project 12.
Deploy Image Classification Pre-trained Keras model using Flask

Computer Vision
_{(lifetime course access)}
+
30 days Cloud Lab

Computer Vision
_{(lifetime course access)}
+
90 days Cloud Lab

Computer Vision
_{(lifetime course access)}
+
180 days Cloud Lab