Data Science & AI
Generative AI Fundamentals Course
Understand how large language models and diffusion models actually work, explained for practitioners
- Duration
- Live batches
- Format
- Live online
- Modules
- 9 modules
- Certificate
- On completion
- ✓Live online instructor-led training in scheduled batches
- ✓Transformers, tokens, embeddings and attention explained step by step
- ✓How LLMs are pretrained, aligned and evaluated
- ✓Diffusion models for images and multimodal systems
- ✓Hands-on notebooks with open models and hosted APIs
- ✓Assure Success course-completion certificate
About the course
What this course covers
Generative AI Fundamentals explains what is going on inside the models behind modern AI tools. It is written for practitioners such as analysts, developers and technical managers who use or evaluate generative AI and want a solid mental model rather than a collection of prompts.
The course covers how text becomes tokens and embeddings, how the transformer's attention mechanism works, how a model is pretrained on large text corpora, and how instruction tuning and preference training make it behave like an assistant. It then looks at what influences outputs, such as temperature and context length, why models hallucinate, and how to evaluate them. A section on diffusion models explains how images and video are generated, and a closing section surveys retrieval-augmented generation, fine-tuning and agents so you can see how the pieces fit together.
There is no external exam. You complete hands-on notebooks and a short project, and receive an Assure Success course-completion certificate.
Who should attend
- ● Data analysts, developers and engineers who use generative AI at work
- ● Technical managers and architects who must judge AI proposals
- ● Students of computer science or data science wanting a clear conceptual base
- ● Professionals who plan to take LLM, fine-tuning or agent courses next
- ● Product and business analysts working with AI teams
Prerequisites
- Basic Python is helpful for the notebooks; non-coders can follow the concepts
Key skills
Skills you will walk away with
Tokens and embeddings
Explain how text is split, represented as vectors and compared.
Attention and transformers
Describe self-attention and how stacked blocks produce next-token predictions.
LLM training pipeline
Distinguish pretraining, instruction tuning and preference-based alignment.
Controlling outputs
Use temperature, top-p, system instructions and context to influence results.
Failure modes
Recognise hallucination, bias, prompt injection and context limits.
Diffusion and multimodal models
Understand how image generation and vision-language models work.
Curriculum
Module-by-module syllabus
9 modules · 36 topics
1Module 1: The Generative AI Landscape4 topics ▾
Learning objective: Place generative AI in context.
- ▸ Discriminative vs generative models
- ▸ Timeline from n-grams to LLMs
- ▸ Model families and modalities
- ▸ What changed in recent years
2Module 2: Text, Tokens and Embeddings4 topics ▾
Learning objective: Understand model inputs.
- ▸ Tokenisation and vocabulary
- ▸ Embeddings and vector spaces
Schedules
Upcoming live batches
Enroll now and choose your batch dates
Send an enquiry and we'll reserve your seat in the next batch.
Certification
How you get certified
- 1Enrol in a scheduled live batch and receive the notebook setup guide
- 2Attend the live sessions and run the demonstration notebooks
- 3Complete the short project or concept review task
- 4Meet the attendance and assessment criteria for your batch
- 5Receive your Assure Success course-completion certificate
Career outcomes
Roles this opens up
Generative AI Analyst / Associate
₹5–12 LPA (approx.)Evaluates and applies generative AI tools within business teams.
Data Scientist / Analyst (AI-aware)
₹5–14 LPA (approx.)Adds generative AI techniques to analytics and ML work.
Technical Product Owner (AI)
₹10–25 LPA (approx.)Works with engineers to define AI features.
Junior GenAI Developer (after follow-on courses)
₹6–15 LPA (approx.)Builds applications once coding and LLM engineering skills are added.
Salary ranges are approximate figures for India and vary by city, company and experience.
Why this certification is worth it
Clear mental models
Understanding how models work helps you ask better questions and spot unrealistic claims.
Why Assure Success
Learn it once, pass it once
Trainers from the field
Every session is led by a practitioner who uses this material at work.
Batches that fit your week
Weekday and weekend batches in IST, scheduled for working professionals.
Exam-style practice
Practice questions and, where available, a full simulator free with the course.
Exam voucher help
Discounted vouchers and step-by-step help booking your exam.
Human support
WhatsApp support Mon–Sat, 9 AM–8 PM IST — a person answers.
Pay your way
UPI, cards, netbanking and EMI in India; international cards accepted.
FAQs
Questions learners ask us
Q.Is this a prompt-engineering course?
No. Prompting is touched on, but the focus is how the models work. For everyday prompting skills see Generative AI & Prompt Engineering.
Q.How much maths will there be?
Concepts are explained visually first. We show the key equations but do not require you to derive them.
Q.Do I need to code?
Basic Python helps with the notebooks. Non-coders can follow along with prepared outputs, though you will gain more by trying the code.
Q.Is there an exam?
No. You receive an Assure Success course-completion certificate.
Q.Will I be able to build an LLM application after this?
You will understand the building blocks. To build and deploy applications, continue with the Large Language Model, Agentic AI or AI Engineer courses.
Q.Do you cover Indian-language models?
We discuss multilingual support and the challenges for Indian languages at a conceptual level.
Q.Which models will we use?
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₹31,999
Generative AI Fundamentals Course