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Generative AI Course

Generative AI Course

Our Generative AI Course is designed to help you master the latest AI technologies that create text, images, audio, and more. You’ll learn how modern generative models work, including Large Language Models (LLMs), diffusion models, transformers, and prompt engineering. The course covers practical implementation using tools like OpenAI, Gemini, Stable Diffusion, and other GenAI frameworks. Through real-world projects, you’ll gain hands-on experience in building chatbots, content generators, image creators, automation workflows, and AI-powered applications. This course equips you with the skills needed to innovate using cutting-edge generative AI technologies across industries.

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Generative AI Certification Training Course

Our Generative AI Course is a hands-on program designed to teach learners how to build AI systems that can generate content — from text and images to audio, video, and 3D models. This course covers the fundamentals of generative models, deep learning architectures, natural language generation, computer vision, and practical applications of AI-powered content creation. Whether you are a student, software developer, data scientist, designer, or professional aiming to harness the power of AI for creative or business solutions, this course provides practical skills to work with cutting-edge generative technologies and tools like ChatGPT, DALL·E, Stable Diffusion, GPT models, and other generative AI frameworks.

  • Image Generation with GANs, DALL·E, Stable Diffusion
  • Audio & Speech Generation using AI models
  • Video & 3D content generation fundamentals
  • Fine-tuning generative models for custom tasks
  • Prompt engineering for AI content creation
  • AI ethics, bias, and responsible content generation

Generative AI is revolutionizing industries including content creation, marketing, entertainment, design, gaming, and research. This course teaches you to implement models that can generate realistic images, text, audio, and videos, and integrate them into real-world applications You will gain hands-on experience building AI chatbots, AI art generators, music and speech synthesis, code generation, and automated creative tools. By the end of the course, learners will be capable of designing and deploying generative AI systems that solve practical problems and enhance creativity Enroll now and become a Certified Generative AI Professional, mastering the tools and techniques to create intelligent content with AI!

What will I learn?

  • Master the concepts of Generative AI and deep learning models
  • Ability to create AI-generated content: text, image, audio, and video
  • Hands-on experience with industry-standard tools like GPT, DALL·E, and Stable Diffusion
  • Skills in prompt engineering, fine-tuning, and model deployment
  • Knowledge of ethical considerations and safe AI content generation

Requirements

  • Basic understanding of computers & Python programming
  • Laptop/PC capable of running Python and AI libraries
  • Curiosity to explore AI creativity and innovative solutions
  • No prior AI or ML experience required — beginner-friendly

Generative AI Course Content

Introduction to Generative AI
  • Generative AI: definition and scope
  • Why generative models are required
  • Understanding generative models and their significance
  • Generative AI vs Discriminative models
  • Recent advancements and research in generative AI
  • Gen-AI end-to-end project lifecycle
  • Key applications of generative models (text, image, audio, code, agents)
Text Preprocessing & Classical NLP Features
  • Segmentation and tokenization
  • Case normalization, spell correction
  • Stop word removal, punctuation removal, whitespace cleaning
  • Stemming and lemmatization
  • Parts of Speech (POS) tagging
  • Text normalization and rephrasing
Text Encoding Techniques
  • One-hot encoding
  • Index-based encoding
  • Bag of Words (BoW)
  • TF-IDF
  • N-grams and feature extraction (Elimo mention → instructor can map to n-gram engine)
  • Word2Vec & FastText fundamentals
  • BERT-based encodings (intro)
Transformer & Attention Fundamentals
  • Intuition of Transformer and Attention (paper guided)
  • Transformer architecture deep dive (encoder/decoder, selfattention)
  • Masked language modeling & transfer learning in NLP
Large Language Models (LLMs) & Evaluations
  • Overview: BERT (Google), GPT (OpenAI), T5 (Google)
  • GPT-3, GPT-3.5 Turbo use cases and GPT-4 intro
  • How ChatGPT is trained (training pipeline overview)
  • Evaluation metrics for LLMs (perplexity, ROUGE, BLEU, human evals, safety metrics)
Hugging Face Ecosystem
  • Hugging Face Transformers library overview
  • HF API key generation and usage
  • Pre-trained transformer models and transfer learning
  • Datasets, tokenizers, pipelining & standardization
  • Training loops, callbacks, and evaluation metrics
  • Language translation with HF models
Generative Tasks with LLMs (Applications)
  • Text summarization (with Hugging Face)
  • Language translation (Hugging Face flows)
  • Text → Image generation using LLM-backed pipelines
  • Text → Speech generation using LLM tools
OpenAI: APIs and Practical Implementation
  • What is OpenAI API; generate API key & setup environment
  • OpenAI packages: installation and playground experiments
  • Chat completion API, embeddings, moderation, and image/speech models (DALL·E, Whisper)
  • Functional calling and completion API patterns
  • Token management, throttling, error codes, rate limits
  • OpenAI plugins overview and third-party connections
Fine-tuning & Projects with OpenAI
  • When & how to fine-tune models with custom data
  • Best practices for dataset prep and evaluation for fine-tuning
  • Optimization tactics for better outputs
Prompt Engineering (Masterclass)
  • Introduction: What & Why of Prompt Engineering
  • Templates & core elements of good prompts
  • Context selection: zero/one/few-shot prompting
  • Output templates, cues & hints, separating instructions from content
  • Advanced patterns: ask-before-answer, perspective & emotional prompting, laddering, role reversal
  • Self-evaluative prompting & problem splitting
  • Super prompts and ethical considerations (CAN & DAN examples — discuss risks)
Vector Databases & Semantic Search
  • Vector data basics & storing vectors (SQLite approach)
  • ChromaDB local setup: insertion, querying, fetch by id, CRUD for vectors
  • Semantic search workflows & use cases
  • Pinecone, Weaviate overview & comparisons
Building LLM Apps: LangChain & LlamaIndex
  • Hands-on with LangChain: chains, agents, retrieval augmented generation (RAG)
  • LlamaIndex practical guide and integrations with LLMs
  • Building an AI chat agent combining LangChain + OpenAI + Vector DB
Productivity & Auxiliary Tools (Bonus Module)
  • Chainlit (async Python framework)
  • LIDA (auto visualizations), Slidesgo AI slide maker
  • Content tools: Jasper, Copy.ai, Anyword
  • Grammar & rewording: Grammarly, Wordtune, ProWritingAid
  • Video creation: Descript, Runway, Filmora
  • Image generation: DALL·E 2, Midjourney
  • Research assistants: Genei, Aomni

Start Your Enrollment

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Why Choose Us ?

At TCIIT, our Generative AI Course is designed to prepare students for the future of AI by training them in LLMs, prompt engineering, AI agents, embeddings, vector databases, multimodal AI, and real-world AI automation. You learn how modern AI systems like ChatGPT, Claude, Gemini, and Llama work — and how to build your own AI apps, chatbots, content generators, and automation tools using Python and no-code/low-code platforms. With complete hands-on practice, this course is perfect for students, professionals, entrepreneurs, and developers who want to build real AI solutions for business, industry, and research.

Diverse Career Opportunities in Generative AI: Exploring Cutting-Edge Roles in India’s AI Innovation Ecosystem

In India, expertise in Generative AI opens doors to some of the most advanced and transformative career opportunities in technology, media, entertainment, healthcare, finance, and e-commerce sectors. Leading global organizations like OpenAI, Google, Microsoft, Meta, Adobe, and NVIDIA actively hire Generative AI specialists to develop creative AI solutions, automated content generation, intelligent assistants, and next-generation AI products. Generative AI professionals are highly valued for their ability to design, train, and deploy AI models that generate high-quality text, images, audio, video, and synthetic data. Their work powers applications such as AI-powered chatbots, content creation tools, virtual environments, recommendation engines, and generative design for industries like gaming, marketing, and healthcare. Salary packages vary based on expertise and experience. In India, the average annual salary for a Generative AI Engineer ranges from 1,200,000 to 1,800,000 INR, while in the USA it is approximately $150,000 per year, reflecting strong global demand and exceptional earning potential in this rapidly growing field.

Get Generative AI Certification

Three easy steps will unlock your Generative AI Certification

  • Complete the online/offline Generative AI Course along with all required assignments.
  • Successfully work on multiple industry-based Generative AI projects, including LLMs, prompt engineering, and AI automation tasks.
  • Pass the Generative AI Certification Exam to earn your verified, industry-recognized certificate.

The certificate for this Generative AI course will be provided through our learning management system (LMS). You can download it anytime and attach the certificate link to your CV, resume, or LinkedIn profile to highlight your expertise in cutting-edge AI technologies.

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