Program Duration
Learn prompt patterns (rewrite, critique, tree-of-thought), build RAG pipelines, leverage function/tool calling & agents, add guardrails & evaluation, and deploy real apps. Earn a QR-verified certificate and a recruiter-proof portfolio.
Includes prompt optimization, embeddings, vector DBs, safety best practices, latency/cost tuning, and CI/CD for LLM apps.
These highlights are extracted from your official brochure (see pages 1, 3 and 6) and presented with live counters for quick scanning.
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Program Duration
Practical : Theory
Doubt Solving
Job Assistance
Mentor Expertise
Global Certification
Market Growth (2020–2030)
Job Vacancies in India
Freshers’ Avg Salary
Learn prompt design for chat, tools, RAG, and workflow automation with LLM evaluation and safety-by-design. Target roles: Prompt Engineer, AI Automations Specialist, Applied AI.
*Outcomes vary by prior experience, pace, and project depth.
Learn to design prompts that perform across models and use-cases. Build automation and content systems with measurable quality, safety, and cost control.
Master system prompts, role prompting, few-shot patterns, and chain-of-thought to boost quality and reliability.
CRISPE, ReAct, CoT, and Planner-Executor frameworks to structure multi-step reasoning and tool use.
Work across ChatGPT, Grok, and open-source LLMs; adapt prompts to different model behaviors and contexts.
Wire prompts into APIs and no-code tools, create reusable templates, and automate content & support workflows.
Mitigate bias, define allowed topics, and implement output validation, red-teaming, and fallbacks.
Build prompt test sets, track win-rates, measure latency/cost, and version prompts like code.
From LLM fundamentals and prompt patterns to evaluation and guardrails, this program emphasizes practical, deployable skills. You’ll ship reusable prompt libraries, integrate with APIs, and publish portfolio-ready demos.
Keywords: prompt engineering course, generative AI prompts, ChatGPT prompting, few-shot CoT, system prompts, evaluation harness, AI content automation, guardrails, LLM safety.
A 10-module, industry-aligned pathway from AI/ML foundations to Generative AI, LLMs, Vision & Speech, Prompt Engineering, Responsible AI, and a hands-on capstone.
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What is AI, its evolution, and importance • Real-world applications • AI vs. Machine Learning vs. Deep Learning • Limitations and ethical considerations.
Subfields of AI (NLP, Computer Vision, Robotics, ML) • Intro to Machine Learning • Learning types (Supervised, Unsupervised) • Basics of Neural Networks • Everyday AI-powered tech.
What Generative AI is and how it creates new content • How it differs from traditional AI • Cross-domain use cases (marketing, healthcare, finance, gaming, etc.).
Foundational model families (LLMs, LIMs, LAMs) • Fine-tuning and transfer learning • Transformer architecture fundamentals.
LLM basics (NLP, prompting, zero-shot & few-shot) • Evolution of LLMs (GPT, Claude, Llama, Gemini/Bard, Pi) • Tokenization, embeddings, context windows • Real-world use cases (chat & voice assistants).
Intro to Computer Vision • Image processing and feature extraction • Large Image Models (Stable Diffusion, Leonardo.ai, DALL-E) • LIM applications.
Video & speech AI tooling (e.g., VEED, PlayHT, Suno.ai) • Text-to-Speech & Speech-to-Text applications • AI-powered video & audio generation.
Prompting foundations • Zero-shot, one-shot, few-shot techniques • Case studies (e.g., brand campaigns) • Hands-on: designing prompts across different AI models.
Ethics and bias in AI models • Governance for responsible deployment • Regulations & compliance • Best practices: Human-in-the-loop, monitoring, AI collaboration.
Real-world AI implementation project • Assessment and certification pathway.
*Module order may vary based on cohort needs and instructor discretion.
Build production-ready prompts and generative workflows across leading LLMs and image models. Learn evaluation, guardrails, and versioning for reliable outcomes.
Design system prompts, few-shot examples, and structured outputs for robust assistants.
Craft visual prompts, control styles, and iterate compositions for brand-ready imagery.
Stylize prompts with descriptors, aspect ratios, and seeds for consistent art direction.
Master negative prompts, CFG, and ControlNet for controllable generative outputs.
Use templates, evaluators, and versioning to A/B test prompts and track win-rates.
Explore search-grounded prompting and factuality checks for knowledge tasks.
Structure long-form prompts, safety rails, and analysis workflows with extended context.
Optimize prompts for latency/cost tradeoffs and high-throughput generation.
Master ChatGPT, DALL·E, Midjourney, Stable Diffusion, prompt testing tools, Google Bard, Claude AI, and Groq for professional prompt engineering and generative AI workflows.
Follow these four proven steps to go from beginner to job-ready Prompt/GenAI professional with portfolio projects recruiters trust.
Foundations of LLMs, prompt patterns, context windows, safety/guardrails, and rapid prototyping to build confidence fast.
Ship an AI content assistant, a RAG knowledge bot, and an automation/agent workflow with docs, demos, and clean READMEs.
Resume & LinkedIn optimization, ATS keywords, product thinking, system design for LLM apps, and scenario-based interviews.
Target roles like Prompt Engineer, LLM App Engineer, RAG/Knowledge Engineer, or AI Product Specialist (₹8–15 LPA).
Learn from anywhere. Your GenAI journey starts here.
Create AI-powered applications the right way: robust prompt patterns, guardrails, structured outputs, and LLM evaluation.
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Generate long-form articles with sectioning, tone control, and fact-checking cues.
Multi-turn coding helper that plans, explains, and writes tests from specs.
Prompt a text-to-image model with style presets, seeds, and safety filters.
Retrieval-augmented assistant that cites sources and follows policy reliably.
Batch create on-brand ad variants with A/B hooks and readability checks.
Summarize PDFs/spreadsheets with structured outputs and QA follow-ups.
These industry-aligned projects emphasize prompt reliability, safety, and evaluation-exactly what hiring managers want for Prompt Engineer, AI Automations, and Applied AI roles.
*Scope may vary by dataset, model, and pace.
Real feedback from graduates of our Prompt Engineering with Gen AI program-covering prompt frameworks, evaluation, guardrails, and automation. Portfolio-first and job-focused outcomes.
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Read independent reviews of our Prompt Engineering course. Alumni highlight frameworks, evaluation methods, guardrails, automation, and job placements.
High-growth careers across AI content, automation, copilots, RAG platforms, and LLM product engineering.
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*Logos are illustrative of hiring potential. Openings vary by location, skills, and experience.
Master Prompt Engineering to produce reliable, on-spec outputs for content, code, and automation use-cases with guardrails and LLM evaluation.
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Start from the fundamentals of LLMs, prompt patterns, and safe usage—no prior experience required.
Automate briefs, drafts, and repurposing with on-brand voice, tone control, and approval-ready outputs.
Enhance coding workflows with tool-use prompts, structured outputs, and evaluation for reliability.
Build a recruiter-ready portfolio with real projects in chat, RAG, and automation—plus job assistance.
Launch AI-powered agencies or products. Learn to build MVPs, automate operations, and scale with GenAI.
Ideal for beginners, content & marketing pros, developers, and career switchers targeting roles like Prompt Engineer, AI Automations Specialist, and Applied AI.
*Learning paths adapt by background and pace.
Everything about our Prompt Engineering with Gen AI program-curriculum, tools, projects, timelines, certification, and career support.
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Still have questions? for a personalized walkthrough of the curriculum and outcomes.
Join a project-first program with global certification, 20+ guided hours, and 100% job assistance-covering frameworks, evaluation, guardrails, and automation with leading LLMs.
Flexible schedules • Mentor support • Seats are limited-secure yours today.