Learn Ai
Generative Ai
Use advanced models like GANs, VAEs, and LLMs to learn how to use generative AI to make text, images, audio, and more. Get real-world experience making creative apps that use AI.
5/5(4,890 Reviews)
Level
Advanced
Duration
8 weeks
What is Generative Ai?
This course gives a thorough introduction to Generative AI, going over the main models and how they can be used in different fields. You will learn about GANs, VAEs, Diffusion Models, and LLM-powered generation for text, pictures, and other media. You'll learn how to prompt engineers, fine-tune models, and deploy them through hands-on projects. By the end, you'll be able to come up with and use smart generative AI solutions for real-world problems.
Training Plan
About trainer
Working professional who is carrying more then 10 years of industry experience.
Decks
The candidate will get access to the presentation taken-up during the session.
Notes
Consolidated notes in word document.
Assignments
Assignments for every module will be covered.
MCQs
MCQs for every module covered in the session would be provided.
Video Recording
Daily Session would be recorded and shared to the candidate.
Dumps for Certification
We will provide dumps for the certification exam, which will help you to prepare for the exam.
Updated Content
We provide Generative AI Driven content By experts.
Projects
3 Live Projects will be provided for practice.
Generative Ai Course Curriculum
.
Introduction to Generative AI
Section 1
Understand the fundamentals, history, and importance of Generative AI.
AI vs Generative AI
Evolution of Generative Models
Types of Generative Models
Applications in Industries
Challenges & Risks
.
Foundations of Machine Learning & Deep Learning
Section 2
Learn the essential concepts of ML and DL that power generative AI models. This module covers supervised, unsupervised, and reinforcement learning basics.
Neural Networks
Supervised vs Unsupervised Learning
Backpropagation
Optimization Techniques
.
Generative Models Overview
Section 3
Explore different types of generative models, including probabilistic models, GANs, VAEs, and Diffusion models, and their underlying principles.
Variational Autoencoders (VAEs)
Generative Adversarial Networks (GANs)
Diffusion Models
Probabilistic Models
.
Natural Language Generation (NLG)
Section 4
Focus on text-based generative AI models such as GPT, LLaMA, and other large-scale transformers for conversational AI and content generation.
Transformers & Attention
GPT Family
BERT & LLaMA
Applications in Chatbots & Writing
.
Generative AI for Vision
Section 5
Learn how Generative AI powers computer vision tasks such as image generation, enhancement, and editing through GANs and diffusion models.
Image Synthesis
Style Transfer
Image-to-Image Translation
Diffusion-based Generation
.
Generative AI for Audio & Speech
Section 6
Explore how AI generates audio, speech, and music, including text-to-speech and voice cloning technologies.
Text-to-Speech (TTS)
Voice Cloning
Music Generation
Speech Enhancement
.
Prompt Engineering & Control
Section 7
Learn the art of designing effective prompts and controlling generative outputs for accuracy, creativity, and alignment with requirements.
Prompt Design
Zero-shot & Few-shot Learning
Context Management
Output Constraints
.
Fine-tuning & Customization of Generative Models
Section 8
Understand methods to fine-tune pre-trained models for domain-specific tasks and customize outputs to business needs.
Transfer Learning
Parameter-efficient Fine-tuning
Domain Adaptation
Custom Datasets
.
Evaluation & Metrics for Generative AI
Section 9
This module covers evaluation techniques for generative outputs, focusing on quality, coherence, and relevance of generated content.
BLEU, ROUGE, METEOR
Human Evaluation
Diversity & Creativity Metrics
Hallucination Detection
.
Tools & Frameworks in Generative AI
Section 10
Hands-on practice with popular frameworks and platforms that enable building and deploying generative AI solutions.
TensorFlow & PyTorch
Hugging Face Transformers
LangChain & LlamaIndex
OpenAI API
Key Projects
Generative Ai
AI-Powered Creative Writer
Use LLMs to make a generative text app that can write stories, blogs, or product descriptions. Use prompt engineering and fine-tuning for certain fields.
Text-to-Image Generation Tool
Create a platform that uses diffusion models or GANs to turn text prompts into pictures. Change the styles and try out different creative outputs.
Voice Cloning & Audio Synthesis App
Use diffusion models or GANs to make a platform that makes pictures from text prompts. Change styles and try out different creative outputs.
Generative Ai – Associate Training Program
Category
Associate
Exam Name:
Generative Ai – Associate
Exam Code:
N.A.
Exam Duration:
N.A.
Exam Format:
N.A.
Passing Score:
N.A.
Our Testimonials
Frequently Asked Questions (FAQs)
What skills will I gain from this Generative AI course?
You will learn how to create, train, and use generative AI models for text, images, and audio, as well as how to write good prompts, fine-tune models, and use AI in an ethical way.
What is Generative AI?
Generative AI is a type of artificial intelligence that can create content like text, images, audio, and videos from prompts. It uses deep learning models such as GANs and transformers. TechPratham’s training helps learners understand the principles and practical applications of Generative AI in business, art, and research.
How does Generative AI work?
It works by learning patterns from large datasets and generating new outputs that resemble the original data. This includes language, visuals, or other media types. TechPratham teaches learners to use AI tools efficiently for content creation and problem-solving.
What are the applications of Generative AI?
Generative AI is used for content creation, marketing, design, music, simulations, and coding assistance. TechPratham ensures learners get hands-on experience applying these models in real-world scenarios.
Can Generative AI replace human creativity?
No, Generative AI assists humans by providing ideas, drafts, and inspiration but cannot replicate true human intuition and creativity. TechPratham teaches how to combine AI-generated content with human expertise for better outcomes.
Do I need technical skills to use Generative AI?
Basic computer literacy is sufficient to start using Generative AI tools. TechPratham’s training is beginner-friendly and gradually introduces advanced AI techniques through practical exercises and projects.
How accurate or reliable is Generative AI content?
Outputs can be highly realistic but may occasionally include errors, biases, or inconsistencies. TechPratham emphasizes verification, refinement, and responsible AI use to ensure quality and trustworthiness.
What skills can I gain from Generative AI training?
Learners gain AI content generation, prompt engineering, multimodal AI usage, automation, and creative problem-solving skills. TechPratham provides project-based learning to apply these skills effectively in professional settings.
How is Generative AI used in businesses?
Businesses use Generative AI for marketing campaigns, content automation, design prototyping, simulations, and customer engagement. TechPratham shows practical use cases that prepare learners for AI-driven business environments.
Is Generative AI safe to use?
Generative AI is safe if used ethically, but outputs should be monitored to avoid misinformation or misuse. TechPratham trains learners in ethical AI practices, bias mitigation, and compliance.
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