Master Generative AI: Build, Train, and Deploy Cutting-Edge AI Models

Generative AI Training at TechnoPaat

Learn how to build with Generative AI through hands-on courses that cover core ideas and real tools. Create text, images, and audio with systems like GPT, GANs, and VAEs, and turn concepts into working demos and applications. Whether starting out or advancing skills, training focuses on practical workflows that boost creativity and career growth in AI-driven roles.

What is Generative AI? It is a set of techniques that produce new content by learning patterns from data. At TechnoPaat, explore projects and guided labs using modern model families and toolchains. Build capabilities for content creation, design, automation, and product features that benefit from synthetic data and smart generation.

Mastering Generative AI: From Fundamentals to Advanced Applications

Go from foundations to deployment with a curriculum that explains key architectures, tuning methods, evaluation, and safety. Learn how to pick the right approach for the job and prove value with measurable results.

What You Will Learn

1. Introduction to Generative AI

• Core concepts, use cases, and common pitfalls
• Generative vs discriminative modeling and when to use each

2. Core Models and Techniques

• GANs: architecture, training dynamics, stabilization, and applications
• VAEs: latent variables, reconstruction, and practical implementation
• Transformers: text and image generation with models like GPT and diffusion-backed systems

3. Hands-On Projects

• Image generation pipelines with configuration and evaluation
• Text generation apps using prompt design and basic retrieval
• Audio synthesis or augmentation for creative and product use cases

4. Advanced Topics

• Responsible AI: safety, bias, privacy, and governance
• Fine-tuning and lightweight adaptation (LoRA, adapters)
• Serving and scaling: APIs, caching, and cost control

5. Real-World Applications

• Creative tools for design and media
• Marketing and content production workflows
• Synthetic data for training and testing

Who Is This Course For?

• Engineers, data scientists, and applied researchers
• Developers building creative or productivity apps
• Professionals exploring AI features for products and teams
• Learners interested in modern ML with practical outcomes

Prerequisites

• Basic Python and machine learning familiarity
• Helpful: experience with a deep learning framework

Course Format

• Short lectures paired with live demos
• Hands-on coding labs and projects
• Quizzes and reviews to reinforce learning
• Community discussion and peer feedback

Key Features

• End-to-end curriculum from fundamentals to deployment
• Project-driven learning with practical evaluation
• Guidance from experienced practitioners
• Certificate of completion