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Certification Course on
Deep Learning Specialization (using TensorFlow 2 & Keras)

Learn Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders and Reinforcement Learning From Industry Experts

  90+ hours training

  90 days of Lab

  12+ Projects

  Timely Doubt Resolution

About the Course

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?

Machine 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 Machine 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 Machine 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 machine learning and deep learning. After finishing this specialization, you will find creative ways to apply your learnings to your work. For example

  • You would like to build a robot which can recognize faces or change the path after discovering obstacles on the path.
  • Or maybe you would like to unearth hidden gems (like predicting next year revenue or fraudulent transactions or building a recommendation engine etc) in your company's tons of data(logs, financial records, HR reports or e-commerce transactions reports).

See you in the specialization and happy learning!

Key Features

Learn From Industry Experts

Get Access to 90+ Hours of Training.

Cloud Lab

Apply the skills you learn on a distributed cluster to solve real-world problems.

Certificate

Highlight your new skills on your resume or LinkedIn.

Project

Work on about 12 projects to get hands-on experience

Best-in-class Support

Timely doubt resolution and forum access to answer all your queries throughout your learning journey.
Enrollment
SELF-PACED LEARNING
Course

0 days lab

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90 days lab

349 497
INSTRUCTOR-LED TRAINING
STARTS FROM: 25 Feb
Sat
9:30 a.m. - 1:30 p.m. America/New_York
90 Days Lab
459 699
STARTS FROM: 25 Apr
Sun
10:30 a.m. - 1:30 p.m. America/New_York
90 days lab
349 699
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Learning Path
Download Course Syllabus

Course 1

Python for Machine Learning

1.1 Introduction to Linux
1.2 Introduction to Python
1.3 Hands-on using Jupyter on CloudxLab
1.4 Overview of Linear Algebra
1.5 Introduction to NumPy & Pandas

Course 2

Deep Learning


This course is a part of the Specialization Course in Machine Learning and Deep Learning
1. From Biological to Artificial Neurons
2. Implementing MLPs using Keras with TensorFlow Backend
3. Fine-Tuning Neural Network Hyperparameters
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
1. A Quick Tour of TensorFlow
2. Customizing Models and Training Algorithms
3. Tensorflow Functions and Graphs
1. Introduction to the Data API
2. TFRecord Format
3. Preprocessing the Input Features
4. TF Transform
5. The TensorFlow Datasets (TDFS) Projects
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
1. Recurrent Neurons and Layers
2. Basic RNNs in TensorFlow
3. Training RNNs
4. Deep RNNs
5. Forecasting a Time Series
6. LSTM Cell
7. GRU Cell
1. Introduction to Natural Language Processing
2. Creating a Quiz Using TextBlob
3. Finding Related Posts with scikit-learn
4. Generating Shakespearean Text Using Character RNN
5. Sentiment Analysis
6. Encoder-Decoder Network for Neural Machine Translation
7. Attention Mechanisms
8. Recent Innovations in Language Models
1. Efficient Data Representations
2. Performing PCA with an Under Complete Linear Autoencoder
3. Stacked Autoencoders
4. Unsupervised Pre Training Using Stacked Autoencoders
5. Denoising Autoencoders
6. Sparse Autoencoders
7. Variational Autoencoders
8. Generative Adversarial Networks
1. Learning to Optimize Rewards
2. Policy Search
3. Introduction to OpenAI Gym
4. Neural Network Policies
5. Evaluating Actions: The Credit Assignment Problem
6. Policy Gradients
7. Markov Decision Processes
8. Temporal Difference Learning and Q-Learning
9. Deep Q-Learning Variants
10. The TF-Agents Library
Projects

Projects

1. Analyze Emails

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


2. Build an Image Classifier in Fashion MNIST dataset

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


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.


4. Working with Custom Loss Function

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


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.


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.


7. Mask R-CNN with OpenCV for Object Detection

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


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.


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.


10. Sentiment Analysis using IMDB dataset

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


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.


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.

Certificate

Certificate

Earn your certificate

Our course is exhaustive and the certificate rewarded by us is proof that you have taken a big leap in Machine Learning and Deep Learning.


Differentiate yourself

The knowledge you have gained from working on projects, videos, quizzes, hands-on assessments and case studies gives you a competitive edge.


Share your achievement

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

DL CloudxLab Certificate
Course Creators
Sandeep Giri

Sandeep Giri

Founder at CloudxLab
Past: Amazon, InMobi, D.E.Shaw
Course Developer
Abhinav Singh

Abhinav Singh

Co-Founder at CloudxLab
Past: Byjus
Course Developer
 Jatin Shah

Jatin Shah

Ex-LinkedIn, Yahoo, Yale CS Ph.D.
IIT-B
Course Advisor

Reviews

(4.9 out of 5)
...

I have started learning 3 months ago and I really gained much info and practical experience. I completed the “Big Data with Spark” course and the learning journey really exceeded my expectations.

The course structure and topics were great, well organized and comprehensive, even the basics of Linux were covered in a very simple way. There were always exercises and hands-on that build better understanding, also the lab environment and provided online tools were great help and let you practice everything without having to install anything on your PC except the web browser.

In addition, for the live sessions, it was really a joy attending them each weekend, our instructor “Sandeep Giri”, besides his great experience and knowledge, he was generous, helpful and patient answering all attendees questions in such a way that he could go for more examples and hands-on or even searching the documentation and try new things, I gained much from other attendees’ questions and the way Sandeep responded to them.

This was a great experience having this course and I’m going for more courses in Big Data and Machine Learning with CloudxLab and I recommend it for all my friends and colleagues who look for better learning.

...

Must have for practicing and perfecting hadoop. To setup in PC you need to have a very high end configuration and setup will be pseudo node setup.. For better understanding I recomend CloudxLab

...

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.

...

They are great. They take care of all the Big Data technologies (Hadoop, Spark, Hive, etc.) so you do not have to worry about installing and running them correclty on your pc. Plus, they have a fantastic customer support. Even when I have had problems debugging my own programs, they have answered me with the correct solution in a few hours, and all of this for a more than reasonable price. I personally recommend it to everyone :)

...

Machine learning courses in especially the Artificial Intelligence for the manager course is excellent in CloudxLab. I have attended some of the course and able to understand as Sandeep Giri sir has taught AI course from scratch and related to our data to day life…

He even takes free sessions to helps students and provides career guidance.

His courses are worthy and even just by watching YouTube video anyone can easily crack the AI interview.

FAQ

On completing this course, you will be able to have a complete understanding of how to train a Deep Learning network. Also, as part of the course, you will be working on 4 real-world projects which will give you full expertise on how to build neural networks. The course also enables you to avoid the challenges of overfitting, underfitting, data augmentation etc in real-world scenarios.

You should have the knowledge of about Machine Learning to get the concepts of this course.

You can check https://youtu.be/dXCx4anEcgU for watching the Course Preview.

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.

In this course, you will work on real-time projects. You will receive a problem statement along with a data-set to work on CloudxLab. Once you are done with the projects (it will be reviewed by an expert), you will be awarded a certificate which you can share on LinkedIn.

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

For self-paced course, we provide 100% fees refund if the request is raised within 7 days from enrollment date. Please contact us at reachus@cloudxlab.com to request a refund within the stipulated time. Thereafter, no refund is provided.

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.

Yes, you can renew your subscription anytime. Please choose your desired plan for the lab and make payment to renew your subscription.

We have created a set of Guided Projects on our platform. You may complete these guided projects and earn the certificate for free. Check it out here



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Have more questions? Please contact us at reachus@cloudxlab.com