Have you ever wondered how self-driving cars are running on roads or how Netflix recommends the movies which you may like or how Amazon recommends you products or how Google search gives you such an accurate results or how speech recognition in your smartphone works or how the world champion was beaten at the game of Go?
Deep learning is behind these innovations. In the recent times, it has been proven that machine learning and deep learning approach to solving a problem gives far better accuracy than other approaches. This has led to a Tsunami in the area of Machine Learning.
Most of the domains that were considered specializations are now being merged into Deep learning. This has happened because of the following:
Better research and algorithms
Better computing resources
Distributed computing infrastructures
Availablity of Big Data
Every domain of computing such as data analysis, software engineering, and artificial intelligence is going to be impacted by Deep learning. Therefore, every engineer, researcher, manager or scientist would be expected to know Machine Learning.
So naturally, you are excited about Machine learning and would love to dive into it. This specialization is designed for those who want to gain hands-on experience in solving real-life problems using deep learning. After finishing this specialization, you will find creative ways to apply your learnings to your work.
Program Highlights
Certificate by IIT Roorkee
80+ Hours of Online Training
Work on about 12+ projects to get hands-on experience
IIT Roorkee is ranked first among all the IITs AND 20th position globally in citations per faculty. Established in 1847, it's one of the oldest technical institutions in Asia.
IIT Roorkee fosters a very strong entrepreneurial culture. Some of their alumni are highly successful as entrepreneurs in the new age digital economy.
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.
In this topic, we will cover concepts like different types of Machine Learning algorithms (Supervised, Unsupervised, Reinforcement) and challenges in Machine Learning. We will see examples of solving the problems using the traditional approach and why Machine Learning algorithms give far better accuracy than the traditional approach. This topic will give you a brief introduction to both Machine Learning and Deep Learning world.
We will start the course by learning concepts in Machine Learning. In this topic, we will build a machine learning model to predict housing pricing in California. By the end of this project, you will understand how to build machine learning pipelines to build a model. We will also cover concepts like data cleaning, preparing data for machine learning algorithms, exploring many different models, short-list the best one and fine-tuning the selected model
In this topic, we will train a model on the MNIST dataset to recognize handwritten digits. We will also learn various performance measures in classification like Confusion Matrix, Precision and Recall, and ROC Curve.
In this topic, we will learn various Machine Learning algorithms and concepts like Unsupervised Learning, Ensemble Learning, and Dimensionality Reduction
We will start the Deep Learning course with Artificial Neural Networks. We will learn about biological neurons, multilayer perceptrons, and back-propagation. We will implement a multilayer perceptron using Keras and visualize the runs and graphs using Tensorboard
In this topic, we will learn various challenges deep neural networks face while training like vanishing and exploding gradients. We will learn various techniques to solve these problems like reusing pre-trained layers, using faster optimizers and avoiding overfitting by regularization.
In this topic, we will dive deeper into TensorFlow and its lower level Python API. These lower-level Python APIs are useful when we need extra control like writing custom loss function, layers and many more.
Deep Learning systems are usually trained on very large datasets that may not fit in the RAM. In this topic, we will learn TensorFlow's Data API which helps in ingesting dataset and preprocessing it efficiently.
In this topic, we will learn how Convolutional Neural Networks - CNNs achieve superhuman performance on complex visual tasks. Today CNNs power image search services, self-driving cars, automatic video classification systems and more. We will learn CNNs basic building blocks and how to implement them using TensorFlow and Keras
Predicting the future is something we do all the time like predicting stock prices. In this topic, we will learn how Recurrent Neural Networks - RNN predict the future, the problem they face like limited short-term memory and solutions to these problems - LSTM (Long Short-Term Memory) and GRU cells
Using Natural Language Processing we build systems that can read and write natural language. In this topic, we will learn different NLP techniques and generate Shakespearean text using a Character RNN.
Autoencoders are artificial neural networks capable of learning dense representations of input data without any supervision. For example, we could train an autoencoder on pictures of faces and it can then generate new faces. In this topic, we will learn different types of autoencoders and generative models.
Reinforcement Learning is one of the most exciting fields of Machine Learning. Using Reinforcement Learning AlphaGo(system) defeated the world champion at the game of Go. Reinforcement Learning is an area of Machine Learning aimed at creating agents capable of taking actions in an environment in a way that maximizes rewards over time. In this topic, we will learn various concepts in Reinforcement Learning and experiment with OpenAI Gym.
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.
Apply Now
Application Process
Step 1. Submit the application form and SOP(Statement of Purpose)
Register by filling the application form
Step 2. Reviewing the application
The admission team will review the application and respond with the application status in 24 hours
Step 3. Join The Program
Confirmation of seat is subject to the payment
Note: The Registration deadline is 17 November 2024
Certification Guideline
Complete at least 75% of the topics of the course along with any 3 mandatory(non optional) projects. All the above requirements need to be met within 180 days from the course enrollment date to be eligible for the certificate.
Scholarships
15% Scholarships are available for students, unemployed, women from STEM background, IIT Alumni and CloudxLab Alumni
10% Scholarship available for those clearing the scholarship test
PS: Details to avail the scholarship will be sent post application-submission and only one scholarship applicable per learner
Please note that there is an additional 5% off for one-time payment
Placement Assistance
Placement Eligibility Test
We have around 300+ recruitment partners who will be interviewing you based on your performances in PET
Profile Building Sessions
Sessions will be conducted to guide you on creating the perfect resume and professional profile to get noticed by recruiters
Career Guidance Webinars
Career Guidance Webinars from seasoned industry experts
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
Yes, we do offer placement assistance that includes career guidance, resume building tips and mock interviews. Each participant will receive staunch support from the industry mentors, who also direct you through various placement opportunities within the industry. Above all, we are partnered with leading MNC’s that offer placement opportunities to our participants.
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.
If you are unhappy with the product for any reason, let us know within 7 days of purchasing or upgrading your account, and we'll cancel your account and issue a full refund. Please contact us at reachus@cloudxlab.com to request a refund within the stipulated time. We will be sorry to see you go though!
