Deep Learning Course in Chennai
825 Ratings
Master advanced Artificial Intelligence technologies with Edubrights' Deep Learning Course in Chennai. Designed for students, freshers, job seekers, and working professionals, this training program helps you develop practical skills in neural networks, deep learning models, computer vision, and intelligent data processing through hands-on learning and real-world projects.
Learn how organizations use Deep Learning to power image recognition, speech processing, recommendation systems, predictive analytics, and intelligent automation solutions. Through practical assignments, industry-focused case studies, and project-based training, you will gain the expertise needed to build and deploy deep learning applications for real-world business challenges.
Key Highlights:
✅ Real-Time Deep Learning Projects & Industry Case Studies
✅ Hands-On Training in Neural Networks & Deep Learning Models
✅ Computer Vision, Image Processing & Pattern Recognition Concepts
✅ Practical Exposure to Predictive Analytics & Intelligent Automation
✅ Industry-Oriented Curriculum Designed by Experienced AI Professionals
✅ Certification Guidance & Career Development Support
✅ Resume Building, Mock Interviews & Placement Assistance
✅ Flexible Online, Classroom & Weekend Training Options
Start your Deep Learning journey with Edubrights and gain the practical skills, project experience, and industry knowledge needed to become a job-ready Deep Learning professional in today's AI-driven world.
Call Course Advisor
₹30000
₹45000
Case Studies and Projects
2+
Hours of Training
20+
Placement Assurance
100%
Expert Support
Yes
Support & Access
Lifetime
Certification
Yes
Skill Level
All
Language
All
Course Objectives
1.What exactly Deep Learning training cover?
Deep Learning training covers neural networks, convolutional and recurrent architectures, natural language processing, computer vision, and AI model deployment.
2. What are the main objectives of the Deep Learning course for your development skills?
To help you master building, training, optimizing, and deploying deep neural networks for solving complex AI problems in vision, language, and sequence data.
3. Process Sequential Data & Text
Build Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks to handle time-series forecasting and natural language processing (NLP).
4. Deploy Production-Ready AI Models
Implement modern MLOps pipelines to scale, monitor, and deploy your deep learning models into real-world cloud environments.
Popular Techniques Covered in This Course
1.Neural network architectures
2.CNN, RNN, LSTM
3.Transfer learning
4.Attention mechanisms and Transformers
5.Data augmentation and preprocessing
6.Model optimization and regularization
7.NLP techniques and embeddings
8.Computer vision fundamentals
9.Deep learning frameworks (TensorFlow, Keras, PyTorch)
10.Cloud deployment and MLOps
Get Hands-on Knowledge about Real-Time Projects
Project 1
1. Image Classification with CNN
Build a CNN to classify images from datasets like CIFAR-10 or MNIST.
Project 2
2. Sentiment Analysis Chatbot
Use RNN/LSTM/transformers to develop a chatbot that understands and responds to sentiment.
Project 3
3. Financial Market Sentiment & Time-Series Predictor
Build a multi-input forecasting system that combines past stock price trends with live financial news feeds. By parsing textual data alongside numerical matrices, your model will learn to predict upcoming market shifts based on public sentiment.
Project 4
4. Generative AI Art Creation Engine
Program dual-network systems where a generator and a discriminator compete to synthesize highly realistic media. You will master the mechanics behind generative modeling by training a system to create entirely original digital artwork from scratch.
Project 5
5. Enterprise Customer Support Intent Classifier
Design and deploy a scalable natural language processing system that reads, interprets, and categorizes incoming corporate service requests. You will train a language transformer model and package it into a live API endpoint ready for real-world business traffic.
Key Features
Edubrights offers Deep Learning Training in virtual mode with expert trainers. Here are the key features.
40 Hours Course Duration
100% Job Oriented Training
Industry Expert Faculties
Free Demo Class Available
Completed 500+ Batches
Certification Guidance
Curriculum
Module 1: Introduction to Neural Networks
- Basics of neurons and perceptrons
- Multilayer perceptron and backpropagation
- Activation functions (ReLU, Sigmoid, Softmax)
Module 2: Building Deep Learning Environment
- Setting up Python and frameworks
- TensorFlow and Keras introduction
Module 3: Convolutional Neural Networks (CNN)
- CNN architecture and components
- Pooling layers, flattening
- Applications in image classification
Module 4: Recurrent Neural Networks (RNN) and LSTM
- Sequence modeling and temporal data
- Architecture and training of RNN and LSTM
- Applications in text and speech
Module 5: Advanced Architectures and Techniques
- Transfer learning, data augmentation
- Generative models and autoencoders
- Optimization techniques and regularization
Module 6: Natural Language Processing (NLP)
- Text preprocessing and embedding layers
- Sequence to sequence models and attention
- Transformer models (BERT, GPT)
Module 7: Computer Vision Applications
- Object detection and segmentation
- Image generation
Module 8: Deployment and MLOps
- Model saving, serving, and deployment on cloud
- Monitoring and maintaining deep learning pipelines
Module 9: Capstone Project
- Real-world problem solved with end-to-end deep learning pipeline
Receive Training From Our Skilled and Effective Trainers
Experience in the Industry Gain knowledge from experts with practical Deep Learning project experience in a variety of sectors.
Backgrounds at the Top Prominent corporations such as HCL, TCS, Accenture, and Cognizant employ trainers.
Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.
Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.
Up-to-Date Knowledge Trainers stay current with the latest tools, techniques, and best practices.
Succeed Our Resourceful Certification
Our certification validates your ability to design, implement, and deploy deep learning models for complex AI tasks. Gain hands-on expertise to work in AI innovation across industries.
Course FAQs
Q1: What is Deep Learning?
A subfield of AI that uses neural networks with many layers to model complex patterns.
Q2: Do I need programming experience?
Basic Python skills are recommended.
Q3: What job options follow this training?
Deep learning engineer, AI researcher, computer vision specialist.
Q4: Is hands-on coding part of the course?
Yes, with Python, TensorFlow, and Keras.
Q5: How long does the course last?
Typically 4–6 months depending on the program.
Q6: What math is required?
Basic linear algebra, calculus, and probability.
Q7: Will I work on real datasets?
Yes, including images, text, and sensor data.
Q8: What hardware is recommended?
A computer with GPU support is ideal for training models.
Q9: Does the course cover the latest models?
Yes, including transformers and GANs.
Q10: How to keep skills current in deep learning?
Follow research papers, participate in challenges, and continuous learning.
Q11: What is the main difference between the Machine Learning and Deep Learning segments?
Machine learning often relies on manual feature engineering where a human must isolate data traits. Deep learning uses multilayered artificial neural networks to automatically discover, isolate, and extract features directly from raw data like pixels or text files.
Q12: Can a complete non-programmer take this course?
If you have zero programming experience, we highly recommend taking our basic Python for Data Science primer class first. Trying to learn complex neural network matrix math and syntax simultaneously can feel overwhelming.
Q13: Do we use PyTorch or TensorFlow in this course?
The core curriculum is built around TensorFlow 2.x and Keras due to its widespread adoption in enterprise production environments. However, we do offer additional bridging modules focused on PyTorch syntax for academic research purposes.
Get Training Quote for Free
Testimonials
Hear What Our Students Say
"Transform your life through Education, hear it from our Alumni"
6 LPA
Fathima
Student
Software Engineer
"Transform your life through Education, hear it from our Alumni"
8 LPA
Siddharth
NIELSON IQ
Data Analyst
"Transform your life through Education, hear it from our Alumni"
8 LPA
Rahul
Student
Data Scientist
