Recurrent Neural Networks (RNN) Training in Gurgaon, Delhi

Recurrent Neural Networks (RNN)

The Ultimate Training for Recurrent Neural Networks (RNN)

Duration : 1 year Classes : 72 Days : Weekdays / Weekends

Overview
Curriculum
Pre-requisite
Review

RNN is a class of neural architectures designed to process sequential data. Learners will explore how RNNs maintain memory across time steps, making them ideal for tasks involving temporal or ordered inputs such as speech, text, and sensor data.

RNNs works on the principle of saving the output of a particular layer and feeding this back to the input in order to predict the output of the layer. Generally they are the queen of algorithms for Speech Recognition, Voice Recognition, Time Series Prediction, Natural Language Processing and Machine Translation (i.e. Google Translate).

In this training, we shall use Keras with TensorFlow as its backend to create a RNN model. You shall learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages. Exploring how information flows through a RNN, you`ll use a Keras RNN model to perform sentiment classification.

During the course you will learn how to prepare data for the multi-class classification task, as well as the differences between multi-class classification and binary classification (sentiment analysis).

This course provides an in-depth look at RNNs in machine learning, giving you the knowledge to build your skills in this area. This is an enlightening course. Why Wait? Register today.

Target Audience:-
:- People pursuing a career in Data Science
:- Anyone curious to master CNN from Beginner level in short span of time
:- Data Analysts and Engineers
:- University Students
:- Scientists and Researchers

Learning Outcomes:-
:- Design and train RNN-based models for various sequential tasks
:- Apply LSTM and GRU architectures to improve performance and stability
:- Integrate attention and transformer layers for enhanced context modeling
:- Building and Train an Recurrent Neural Networks (RNN) in Python
:- Evaluate and deploy RNN models in production environments

Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training

Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas

:- You are hands-on with Machine Learning using Python.
:- You have theoretical knowledge of Artificial Neural Networks (ANN)
:- You have a genuine interest in RNN.

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NB: All our trainings are always tailored to adopt to the Individual's Pace and Learning Depth.

NB: As a stepping stone, providing foundational knowledge, Bridge Courses are conducted periodically, to help students transition between different levels by closing knowledge gaps. These classes can be attended ad hoc, and are 'complimentary' for our bonafide students.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre and complete your registration.

This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.

Module 1: Foundations of Sequential Data and Simple RNNs
✔ Sequence Data and Dependencies
✔ The Vanilla RNN Architecture
✔ Sequence Mapping Configurations
✔ Mathematical Derivations
✔ Data Preparation for Sequences

Module 2: RNN Training Dynamics and Challenges
✔ Backpropagation Through Time (BPTT)
✔ The Vanishing Gradient Problem
✔ The Exploding Gradient Problem
✔ Sequence Loss Functions
✔ Advanced Initialization

Module 3: Long-Term Dependency Architectures
✔ Long Short-Term Memory (LSTM)
✔ The LSTM Gates
✔ Gated Recurrent Units (GRU)
✔ Bidirectional RNNs (Bi-RNN/Bi-LSTM)
✔ Deep/Stacked RNNs

Module 4: Sequence-to-Sequence (Seq2Seq) Models and Attention
✔ Encoder-Decoder Architecture
✔ The Bottleneck Problem
✔ Introduction to Attention
✔ Softmax and Beam Search Decoding

Module 5: Natural Language Processing (NLP) Applications
✔ Text Generation/Language Modeling
✔ Sentiment Analysis
✔ Neural Machine Translation (NMT)
✔ Word Embeddings

Module 6: Time Series, Advanced Topics, and Practice
✔ Time Series Forecasting
✔ Multivariate Time Series
✔ Convolutional RNNs (CRNNs)
✔ Introduction to Transformers and comparison with RNNs
✔ Practical Implementation and Debugging

Module 7: Capstone Project
✔ Choose a domain: NLP, finance, healthcare, or IoT
✔ Build and evaluate an RNN-based solution
✔ Present findings and deploy model

NB:The curriculum is regularly subjected to updates, reflecting the latest industry trends & current technological advancements.

At Vyom Data Sciences, we aspire to provide the latest curriculum and most recent technology, as a standard component of all our trainings. Experts, with 25+ years of experience from USA, Europe and Australia, bring the best industry practices while designing and executing these trainings. All our trainers are Highly Qualified and Certified in their respective subject areas.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre.

Bhawana

Fabulous NLP + ML course

I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.

Harish

Excellent ML course!

The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.