Course Overview
This program introduces the core concepts of deep learning, focusing on neural network architectures, optimization techniques, and common applications. Participants will learn to implement and train models using TensorFlow and PyTorch with hands-on exercises.
Aim
To provide PhD scholars, researchers, and professionals with foundational knowledge and practical skills to build deep learning solutions across various domains.
Program Objectives
- Understand deep learning principles and architectures
- Build and train CNNs, RNNs, and other models
- Use optimization techniques like dropout and regularization
- Apply frameworks like TensorFlow and PyTorch
- Execute real-world AI projects and deployments
Program Structure
- Module 1: Introduction to Deep Learning
- Module 2: Neural Networks Basics
- Module 3: Training Deep Neural Networks
- Module 4: Convolutional Neural Networks (CNNs)
- Module 5: Recurrent Neural Networks (RNNs)
- Module 6: Deep Learning Frameworks
- Module 7: Autoencoders and Generative Models
- Module 8: Advanced Deep Learning Concepts
- Module 9: Model Deployment and Production
- Module 10: Deep Learning Ethics and Fairness
- Final Project: Real-world DL project implementation and deployment
Participant Eligibility
Suitable for AI researchers, data scientists, PhD scholars, ML engineers, and academicians seeking to gain practical deep learning skills.
Program Outcomes
- Build, train, and evaluate deep learning models
- Use TensorFlow and PyTorch for implementation
- Develop solutions for NLP, computer vision, and time series
- Deploy models on real-world platforms and applications
Program Deliverables
- Full e-LMS access
- Real-time project guidance
- Publication support
- Assignments and self-assessment tools
- Final exam and e-certification
- e-Marksheet
Future Career Prospects
- Deep Learning Engineer
- AI Research Scientist
- Computer Vision Specialist
- Data Scientist
- NLP Engineer
Job Opportunities
- AI Labs and Research Centers
- Tech Startups and Product Companies
- Healthcare, Finance, and E-Commerce AI Teams
