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Certification Course on
Natural Language Processing

Learn Python, Artificial Neural Networks,TensorFlow 2, Convolutional & Recurrent Neural Networks, Natural Language Processing and More

2,665 Ratings        6,500+ learners

  70+ Hours of Online Self-Paced Training

  90 Days of Lab

  Timely Doubt Resolution

  5+ Projects

About the Course

Natural Language Processing Specialization Program is a self-paced online course. This gives you complete freedom about your schedule and convenience.This course has over 70 hours of video content.

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.



Learn From Industry Experts

Get Access to 70+ Hours of Training.

Cloud Lab

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

Project

Work on about 5+ 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.

Certificate

Highlight your new skills on your resume or LinkedIn.
Enrollment
SELF-PACED LEARNING
( Course+ Lab+ Certificate)

90 Days Lab

159 349
Get a callback from a Course Counselor - Click Here
Learning Path
Download Course Syllabus

Course 1

Python

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

Natural Language Processing Specialization


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. The Architecture of the Visual Cortex
2. Convolutional Layer
3. Pooling Layer
4. CNN Architectures
5. Classification with Keras
5. Transfer Learning with Keras
5. Object Detection
5. 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
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. 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.


5. Sentiment Analysis using IMDB dataset

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

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 Python.


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

 Course Certificate Sample
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
Praveen Pavithran

Praveen Pavithran

Co-Founder at Yatis

Past: YourCabs, Cypress Semiconductor

Course Developer

Reviews

(4.7 out of 5)
...

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.

...

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.

...

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!

...

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.

...

I took both the machine learning and deep learning course at CloudXLab. I came into the first part of the course with some knowledge of machine learning but the class really helped me understand some of the topics a lot clearer. I think the best part of the class is the instructor Sandeep. He is very knowledgeable and does a really good job explaining topics that can be nebulous at times. Another favorite part of the course are the online labs. I would watch the 3hr lecture the next day, and then work on the labs. The labs reinforces the lectures with questions and coding assignments. There is also a message board and a slack channel. I preferred using slack, but I think you get a quicker response if you use the message board. As far as the deep learning portion of the course, it was all new to me but I was building CNN and RNN models using TensorFlow after each 3hr lecture. Overall, I was very pleased with the course. I am hoping that CloudxLab will put together an advanced class focusing more on deploying models to the clouds, working with pipelines, DevOps etc…

...

I found the ML&DL course very well structured with ample examples and hands on exercises. Sandeep was very patient in answering questions and he made the training sessions very interactive. I would recommend this training to all who plan to take a dive into the world of machine and deep learning.

...

I have thoroughly enjoyed both the ML and DL courses from CloudXLab and will look forward to reviewing the videos/material at a later time. I’ve been to many meetups and paid sessions on ML /DL and this course beats most of them on the depth of topics and certainly breadth of topics. I’ve not taken any online courses (Andrew Ng, for example) to their conclusion, so I won’t draw a conclusion there. For an instructor-led, interactive course, I would expect to pay many times more for a class (ML and DL) such as this in the US. The instructor is easy to understand, has extensive experience, and truly cares about the student knowing the material.

...

A very well structured instructor-led course. The instructor was very thorough, and always willing to answer questions and clarify coursework, no matter how minor. The course described the theory of machine/deep learning well, but also followed through with very thorough examples to demonstrate the practical implementations of the theory. This leads nicely into the student exercises, which served to solidify the instructor's teachings and encourage experimentation. The resources provided for students was exceptional and presented in a very user-friendly format.

My only complaint is that the course went quite overtime, but I also appreciate Sandeeps dedication to quality and ensuring that he finished teaching us everything adequately.

...

I have been using CloudxLab for Machine Learning and based on experience I can say that they have done a fabulous job in training and certification process which makes the user so interactive with faculty and software intuitive.

FAQ

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.

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

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.



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