Veda IT

Who Should Join Masters Program in Generative AI Course?

Working Professionals
Engineering Graduates
University Students
Entry-Level Candidates
Job Switchers

Keyskills of Masters Program in Generative AI Developer

A Master's Program in Generative AI equips students with advanced skills in deep learning, neural networks, and natural language processing (NLP). Key competencies include expertise in models like GPT, transformers, and diffusion models for generating text, images, and other media. The program covers AI ethics, prompt engineering, deployment techniques, and practical applications in content generation, automation, and creative industries, preparing graduates for cutting-edge AI innovation.

Key Features

Covers core principles of generative AI, neural networks, and advanced deep learning.
Real-world projects focused on AI applications such as text, image, and music generation.
Learn from AI experts with real-world industry experience.
Develop skills in demand in AI-driven industries, including entertainment, tech, and creative sectors.
Offline classes with optional online support.
Participate in live sessions, collaborative projects, and peer reviews.
Job placement support, resume optimization, and interview prep.
Earn a recognized certification from Veda IT upon successful completion.

What you'll learn

The Masters in Generative AI at Veda IT is an advanced program designed to equip learners with the skills to create AI models that generate new content, ideas, and solutions. This course covers key areas of artificial intelligence, deep learning, and neural networks, focusing on state-of-the-art techniques in generative modeling, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and large language models like GPT and BERT.

With an emphasis on hands-on projects, the program enables students to work on real-world applications such as text generation, image synthesis, music composition, and more. By the end of the course, students will be prepared to apply generative AI techniques across industries such as entertainment, healthcare, finance, and tech, enhancing their creativity, innovation, and analytical problem-solving abilities.

Supported by Veda IT’s career services, graduates will gain access to a range of opportunities in AI, equipped to take on roles that focus on next-generation AI applications and innovation.

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Modules Covered

Overview of Generative AI and Its Applications
Basics of Machine Learning and Deep Learning
Neural Network Architectures
Activation Functions and Optimizers
Loss Functions in Generative AI
Training Neural Networks
Introduction to AI Tools and Frameworks (TensorFlow, PyTorch)

CNN Architecture and Applications
Image Feature Extraction and Classification
Transfer Learning with CNNs
RNN Architecture and Sequence Modeling
Applications of RNNs in Language and Time Series Data
Long Short-Term Memory (LSTM) Networks
Practical Projects with CNNs and RNNs

Introduction to GANs and Adversarial Training
Generator and Discriminator Networks
Types of GANs (DCGAN, CycleGAN, StyleGAN)
Image Generation and Style Transfer
Applications in Image Synthesis and Art
Training Techniques and Challenges
Evaluating GAN Models

Introduction to Variational Autoencoders
Latent Space Representation
Applications of VAEs in Image and Data Generation
Diffusion Models and Applications
Implementing VAEs for Image Generation
Combining VAEs with GANs

Practical Use Cases for VAEs and Diffusion Models

Overview of Transformer Architecture
Pretrained Models (GPT, BERT, T5)
Text Generation and Summarization
Chatbots and Conversational AI
Sentiment Analysis and Text Classification
Fine-Tuning and Transfer Learning in NLP
Advanced NLP Applications with LLMs

AI for Image Synthesis and Manipulation
Generative AI in Music and Art Creation
Text-to-Image and Text-to-Video Models
Generative AI for Game Design and Storytelling
Ethical Considerations in Creative AI
Exploring AI-Generated Content and Ownership
Project-Based Application in Art and Design

Optimizing Model Performance
Model Compression and Quantization
Deployment on Cloud Platforms (AWS, Google Cloud, Azure)
Creating API Endpoints for Generative Models
Ethical Considerations in Generative AI
Bias Mitigation and Responsible AI Practices
Monitoring and Maintaining Deployed Models

Project Planning and Data Collection
Model Selection and Training for Generative Applications
Experimenting with GANs, VAEs, or NLP Models
Evaluating Model Performance and Output Quality
Final Project Presentation and Peer Review
Feedback and Final Enhancements
Real-World Deployment of Capstone Project

Learning Path

Introduction to Generative AI and Deep Learning

Explore the foundations of generative AI and key deep learning concepts.

Fundamentals of CNNs and RNNs

Understand Convolutional Neural Networks and Recurrent Neural Networks for image and sequence processing.

GANs and Adversarial Learning Techniques

Master Generative Adversarial Networks and adversarial techniques for realistic content generation.

Variational Autoencoders (VAEs) and Diffusion Models

Learn to generate high-quality data using VAEs and the latest diffusion models.

Large Language Models (GPT, BERT) and NLP Applications

Dive into large language models and their applications in Natural Language Processing.

Creative AI: Applications in Art, Music, and Design

Explore AI-driven creativity across visual arts, music composition, and design tools.

Model Deployment, Optimization, and Ethics

Deploy AI models, optimize performance, and address ethical considerations in AI applications.

Capstone Project: AI-Driven Application Development

Build and showcase a practical AI project that highlights your generative AI expertise.

Resume Building and Portfolio Development

Develop a professional resume and portfolio to present your AI projects and skills effectively.

Interview Preparation and Career Services

Prepare for AI-related roles with interview practice, career guidance, and job placement support.

Potential Roles

AI Research Scientist
Machine Learning Engineer
Data Scientist (AI Specialization)
NLP Engineer
Computer Vision Engineer
Generative AI Specialist
AI Product Manager
Creative AI Developer
AI Innovation Specialist
Deep Learning Engineer
Research Engineer (AI/ML)
Data Engineer (AI Pipeline)
Applied AI Developer
Ethics Analyst in AI
AI Consultant

Start Date20/05/2025
Enrolled100
Lectures50
Skill LevelBasic
LanguageEnglish,Telugu
Quizzes10
CertificateYes
Pass Percentage100%

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Masters Program in Generative AI

Learn Masters in Generative AI Course Certification Course

The Masters in Generative AI at Veda IT is an advanced program designed to equip learners with the skills to create AI models that generate new content, ideas, and solutions. This course covers key areas of artificial intelligence, deep learning, and neural networks

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