- About Us
- Introduction
- Srishyla Educational Trust
- G M University
- GMU- Campus
- GMU Logo, Flag and Mascot
- GMU- Anthem
- Vision, Mission, Values, and Objectives
- Leadership
- Statutory Committees
- University Documents
- Organisation Structure
- University Best Practices
- Information and Communication Technology (ICT)
- Learning Management System (LMS)
- Human Resources (HR)
- Collaboration and Cooperation
- Programs
- Admissions
- Academics
- Research
- Introduction
- Research Advisor Message
- Dean's Message
- Research Co-ordinators
- PhD Programs offered &
PhD Regulations - Notifications &
Circulars - Galary
- Curriculum
- PhD Admissions
- PhD Supervisors
- PhD Research Scholar List
- Journal Publications
- Conference Publications
- Conferences/Symposium Organized
- Patents
- Research Bulletin
- Sponsored/Grant Research
- Prestigious Lecture Series
- Centres of Excellence
- Skill Development
- Home About Us
- Introduction
- Srishyla Educational Trust
- G M University
- GMU- Campus
- GMU Logo, Flag and Mascot
- GMU- Anthem
- Vision, Mission, Values, and Objectives
- Leadership
- Statutory Committees
- University Documents
- Organisation Structure
- University Best Practices
- Information and Communication Technology (ICT)
- Learning Management System (LMS)
- Human Resources (HR)
- Collaboration and Cooperation
- Programs
- Admissions
- Academics
- Campus life
- Promotions
- Student Placements
- Contact Us
- Careers
Advanced Project Development using AI based technologies
GMUSD67
Credits: 2.00
Prerequisites : Intermediate understanding of machine learning concepts and proficiency in Python programming
Course Duration : 30 Hours / 12 Weeks
Start Date : 2024-04-05
End Date : 2024-03-15
Seats Remaining : 60
Aim & Summary
The course covers a wide range of advanced AI technologies, including deep learning, natural language processing (NLP), computer vision, reinforcement learning, and generative models. Participants will learn how to leverage these technologies to solve complex problems and create AI-driven applications. Through hands-on projects and practical exercises, participants will gain experience in designing, implementing, and deploying advanced AI-based projects. By the end of the course, participants will have the skills and confidence to tackle challenging projects using state-of-the-art AI technologies.| Week 1 | Introduction to Advanced AI-Based Project Development |
| Week 2 | Deep Learning Fundamentals: Neural Networks and Optimization Techniques |
| Week 3 | Advanced Deep Learning Architectures: CNNs, RNNs, and Transformers |
| Week 4 | Natural Language Processing (NLP) Techniques: Word Embeddings, Sequence Models |
QUIZ 1 |
|
| Week 5 | Computer Vision Applications: Image Classification, Object Detection, Image Segmentation |
| Week 6 | Reinforcement Learning: Q-Learning, Policy Gradient Methods |
| Week 7 | Generative Models: GANs, VAEs, and Applications in Creative AI |
| Week 8 | Advanced Topics in AI: Transfer Learning, Meta-Learning, and Self-Supervised Learning |
QUIZ 2 |
|
| Week 9 | Model Interpretability and Explainable AI Techniques |
| Week 10 | Deployment Strategies for AI Models: Cloud Services, Containers, Edge Devices |
| Week 11 | Ethical Considerations and Bias in AI Project Development |
| Week 12 | Capstone Project Development: Designing and Implementing Advanced AI-Based Projects |
PROJECT REPORT |
|