AI Specialist Certification Program: AI‑Driven Business Growth & Automation
Outcome: Students learn to turn AI into revenue — for themselves or any business
LEADERSHIP TEAM
Experienced Leaders in AI Education & Technology
Mr. Gautam Prakashchandra Jain
Founder - Umirai.ai | Director - CLAIM
- 20+ years in business, AI, and training
- UN & UNESCO speaker on AI and education
- Bestselling author and thought leader
- Expert in curriculum design and educational transformation
Mr. Darsh Singh
Founder & CEO - Optume.ai | Director - CLAIM
- AI scientist and marketing technologist
- 15+ years industry experience (Oracle & Bell)
- Product architect and behavioral AI expert
- Specialization in AI application development
Mr. Deepak Prakashchandra Jain
Co-Founder - UMIRAI.ai
- AI expert with 12+ years experience
- Technology and business consulting leader
- Focus on simplifying AI for non-technical users
- Platform development and innovation strategist
Advisory & Support Team:
- Academic curriculum designers
- Industry subject matter experts
- Technology development team
- Research and innovation consultants
Executive Summary
A hands‑on undergraduate course designed to make students job‑ready and business‑ready in 30 hours.
What students learn (simple + practical):
- Pick a profitable niche using AI market intelligence
- Build an offer that sells
- Design funnels (lead gen, sales, webinar, service)
- Write ads, emails, and landing pages with AI co‑creation
- Rank in the AI search era (AEO) while others still play only SEO
- Build no‑code AI apps and chatbots (even without coding)
- Map workflows and automate business operations end‑to‑end
What students produce:
A portfolio-grade AI‑Enabled Growth System + capstone presentation.
Why AI, Why Now
Finance evolved fast; education must too
AI is changing work the way technology changed finance.
Finance evolved step‑by‑step:
- Barter → commodity money → metal coins → paper notes
- Banking instruments → cards → electronic transfers/ATMs
- Internet banking → mobile payments
- Cryptocurrency/blockchain → DeFi (still evolving)
The impact on careers:
- Companies are actively hiring people who can use AI to move faster and produce better outcomes
- Businesses that integrate AI deeply gain a competitive edge in speed, cost, and decision-making
- Students who don't build AI capability are competing at a disadvantage from day one
What This Course Solves
Reality of business work
In real business, results come from systems, not isolated skills.
Business outcomes require:
- Understanding customers + competition
- A clear offer + pricing logic
- A funnel that generates leads and converts
- Content and campaigns that scale
Systems that work:
- Visibility in search + AI search
- Follow-ups that don't depend on humans remembering
- Automation for lead gen, onboarding, and fulfillment
- Metrics that tell you what to fix and what to scale
This course teaches students to build that system — with AI as the accelerator.
Course Promise
Student outcomes
By the end of 30 hours, students can:
01
Contribute to marketing and growth teams (agency or in-house)
02
Support founders and business owners with real deliverables
03
Start a service business with a repeatable offer + delivery workflow
04
Build a portfolio that shows capability (not just certificates)
Course Snapshot
Course type:
Credit-linked add‑on / micro‑certification
Credits:
2
Hours:
30 (15 hours per credit)
Format:
10 sessions × 3 hours
Level:
Undergraduate (beginner-friendly, no coding required)
Teaching style:
- Short concept → live demo → guided lab → output every session
- Teams of 2–5 students build one business system from scratch
The Business System Map
What we cover in 30 hours
This course combines growth + visibility + tools + automation across business functions.
7 gears of business students will touch:
Strategy
niche, customer, positioning
Marketing
content, social, campaigns
AEO/SEO
AI search visibility
Sales
lead handling, scripts, follow‑ups
Operations
SOPs, fulfillment workflow
Automation
tool integration, agent workflows
Analytics
KPIs, weekly review
What Students Will Master
Four Tracks inside one course
Track 1: AI Marketing (Turn AI into revenue)
- Find profitable niches using AI market intelligence
- Create "Godfather" offers customers find hard to refuse
- Build winning funnels (lead gen, sales, webinar, service)
- Write converting ads, emails, and pages with AI co‑creation
- Understand the psychology behind funnels that scale
- Set up automation flows that capture & close clients 24/7
- Execute WhatsApp, SMS & email campaigns that convert quietly
Track 2: AEO (AI Engine Optimization)
- Compete with bigger brands using AI‑first content strategy
- Use llms.txt to guide AI engines on what to read and recommend
- Apply schema markup to improve visibility without technical confusion
- Optimize Instagram, LinkedIn, Facebook for AI discoverability
- Turn existing posts, reels & blogs into AI‑ranked assets
- Understand where AI engines are going next — and move early
- Build first‑mover advantage in your niche
Track 3: AI Software (No‑Code)
- Learn the thinking patterns of expert prompt engineers
- Build custom AI apps from scratch using no‑code platforms
- Create niche AI tools businesses actually need (and pay for)
- Deploy personal AI agents to automate everyday tasks
- Install AI chatbots on websites and funnels in minutes
- Turn knowledge → working products, ready for clients
Track 4: AI Agents & Automation
- Map workflows and automate them end‑to‑end
- Connect software tools into one seamless business machine
- Eliminate repetitive human tasks using smart automations
- Build automation stacks for lead gen, onboarding & fulfillment
- Deliver done‑for‑you automation services businesses pay premium for
Certification Requirements
How students earn it
Students earn the certificate by completing:
Minimum attendance as per university policy
Session lab outputs (practical deliverables)
Final capstone project submission
Capstone presentation + viva (Q&A)
Assessment Plan
Simple and fair
Suggested evaluation split:
20%
Concept check
(quiz)
40%
Lab outputs
(session deliverables)
40%
Capstone
(system quality + presentation)
Evaluation focus:
- Practical usefulness
- Clarity and correctness
- Ethical AI use
- Completeness of the business system
- Execution quality (not fancy theory)
30‑Hour Module Plan
10 Sessions × 3 Hours
01
AI Basics + Prompting that Works
02
AI Market Intelligence (Find Profitable Niches)
03
Offer Design + Pricing + Unit Economics (UG‑simple)
04
Funnel Design (Lead gen, Sales, Webinar, Service) + Psychology
05
Conversion Copy (Ads, Emails, Landing Pages)
06
AEO Fundamentals + AI‑First Content Strategy + Schema
07
AI Discoverability on Social + Repurposing into Ranked Assets
08
No‑Code AI App Building (Niche Tool)
09
Chatbots + Personal Agents (Deployable Assets)
10
Automation Stacks + WhatsApp/SMS/Email Flows + Capstone Defense
Session 1
AI Basics + Prompt Engineering Patterns
3 Hours
Topics:
- What AI can do vs what it cannot do (business reality)
- Prompting framework: context → task → constraints → format → examples
- Output quality control: facts, math, claims, tone, compliance
- "Human-in-the-loop" rule for customer-facing work
Lab output:
Personal prompt library
(10 reusable prompts for business work)
AI quality checklist
(what to verify every time)
Session 2
Find Profitable Niches using AI Market Intelligence
3 Hours
Topics:
- What makes a niche profitable (pain + urgency + ability to pay)
- Competitor scan and differentiation
- Simple market sizing logic (UG‑simple)
- Selecting a niche for the capstone
Lab output:
Niche selection sheet
(3 niche options → final pick)
Competitor map + differentiation statement
Session 3
Create "Godfather" Offers
Offer Design + Pricing
3 Hours
Topics:
- Offer design: outcome, scope, timeline, proof, risk reversal
- Pricing basics: cost, margin, value logic (simple)
- Packaging: good/better/best structure
- What makes customers say "yes" faster
Lab output:
Final offer page (1‑pager)
offer, inclusions, exclusions, pricing
Unit economics snapshot
(simple numbers: cost → margin → breakeven)
Session 4
Build Winning Funnels + Psychology Behind Scale
3 Hours
Topics:
- Funnel types: lead gen, sales call, webinar, service delivery
- Funnel stages: attention → interest → trust → conversion → retention
- Psychology basics: clarity, trust, proof, social proof, urgency, risk reversal
- Mapping a funnel for the capstone business
Lab output:
Funnel map (visual)
Lead capture plan + lead qualification questions
Session 5
Write Converting Ads, Emails, and Pages with AI Co‑Creation
3 Hours
Topics:
- Message-market fit: the core promise and pain
- Copy structures: hook → problem → proof → offer → CTA
- Ad angles and creative testing matrix
- Email sequences: welcome, nurture, follow-up, reactivation
- Landing page structure for conversion
Lab output:
3 ad copies + 3 creative concepts
(text-based)
5‑email sequence
(subject lines + bodies)
Landing page wireframe
(sections + copy bullets)
Session 6
AEO Fundamentals + AI‑First Content Strategy + Schema
3 Hours
Topics:
- SEO basics vs AEO (AI search era)
- AI-first content: intent + entities + structured answers
- Schema markup basics (what it is and how it helps)
- llms.txt concept: guiding AI engines on what to read and recommend
- Turning your offer into searchable answer assets
Lab output:
AEO content plan
10 "answer pages" + FAQ map
Draft llms.txt structure
for the capstone site
Basic schema plan
(what schema types you would use and where)
Session 7
Social Discoverability + Repurposing into AI‑Ranked Assets
3 Hours
Topics:
- Optimize Instagram/LinkedIn/Facebook profiles for discoverability
- Content formats that travel: posts → carousels → reels → shorts → blogs
- Turning existing posts, reels, and blogs into higher-performing assets
- Publishing consistency: cadence, content bank, and quality control
Lab output:
1
Profile optimization checklist
(for one platform)
2
Repurposing kit
1 blog → 1 carousel → 1 reel script → 1 short caption set
3
2‑week content calendar
aligned to funnel stage
Session 8
AI Software Academy (No‑Code App Build)
3 Hours
Topics:
- Thinking patterns of expert prompt engineers (systems approach)
- What "no‑code AI app" means (inputs → prompt logic → outputs → storage)
- How to choose a niche tool businesses actually need
- Building a simple AI tool prototype (no coding)
Lab output:
One working tool prototype
(examples: offer generator, audit tool, content repurposer, lead qualifier)
Tool positioning
who it's for, what it solves, why it's valuable
Session 9
Chatbots + Personal Agents (Deployable Assets)
3 Hours
Topics:
- Chatbots for funnels: FAQs, qualification, booking, objections
- Personal AI agents: automate daily tasks (briefs, reporting, follow-ups, planning)
- Turning knowledge into working products ready for clients
- Packaging your chatbot/tool as a service deliverable
Lab output:
1
Chatbot knowledge base + conversation flow
2
Personal agent workflow map
(what tasks it runs and how outputs are checked)
3
Productized delivery checklist
(what a client receives)
Session 10
Automation Stacks + WhatsApp/SMS/Email + Capstone Defense
3 Hours
Topics:
- Map workflows and automate end‑to‑end
- Connect tools into one business machine (lead → follow-up → booking → onboarding → fulfillment → reporting)
- Eliminate repetitive tasks with smart automations
- Build automation stacks for lead gen, onboarding, and fulfillment
- WhatsApp, SMS & email campaigns that convert quietly (follow-up systems)
- Ethical guardrails and approvals
Lab output:
Automation blueprint
(flow diagram + steps)
Follow-up sequence plan
(WhatsApp + email + SMS touchpoints)
Capstone presentation + Q&A
Capstone Project
Portfolio-Grade Output
Capstone title: AI‑Enabled Growth & Automation System (for one niche business)
Each team submits:
1
Niche + competitor map + positioning statement
2
"Godfather" offer (1‑pager) + simple unit economics
3
Funnel map (lead gen / sales / webinar / service)
4
Conversion assets: ads + landing page structure + email sequence
5
AEO kit: answer pages plan + FAQ map + schema plan + llms.txt draft
6
Social discoverability kit + repurposing kit + 2‑week calendar
7
One no‑code AI tool prototype (usable)
8
One chatbot (FAQ + qualification + booking flow)
9
One automation stack blueprint (lead → onboarding → fulfillment)
10
Responsible AI checklist (how they prevent wrong claims and protect data)
What Students Can Do After This Course
Jobs + Business
Job readiness (entry-level practical roles):
- Marketing / Growth / Content / Social Media
- SEO + AEO assistant roles
- CRM + automation assistant roles
- Business development support with follow-up systems
- Operations support with SOP + automation mindset
Entrepreneurship readiness:
Students can start a micro‑agency/service:
niche selection → offer → funnel → content → follow-ups → delivery workflow
Implementation & Collaboration Model
CHARUSAT × CLAIM
Delivery modes (choose one):
1
CLAIM-led delivery + faculty shadowing
2
Co-taught delivery (CLAIM + CHARUSAT faculty)
3
Faculty-led delivery after CLAIM training
CLAIM provides:
- Course curriculum, slide deck, lab sheets, assignments, rubrics
- Faculty enablement workshop and delivery handbook
- Capstone evaluation rubrics and sample outputs
CHARUSAT provides:
- Faculty coordinator + classroom/lab infrastructure
- Student enrollment and academic evaluation process
- Time-table integration and attendance tracking
Resource Requirements
Minimal, practical
Students need:
- Laptop (preferred) or lab access
- Internet access
- Basic document + spreadsheet tools
Faculty needs:
- Teaching kit + rubrics
- Lab access for hands-on sessions
- Simple evaluation workflow
Pricing & Investment
Proposal
Exceptional Value
Standard market pricing for equivalent training + 3-month tool access:
₹29,441
per student
This partnership pricing represents significant savings while delivering the same comprehensive experience.
Partnership Pricing Tiers
Up to 50 Students
₹14,999
per student
51–100 Students
₹11,999
per student
100+ Students
₹9,999
per student
*Taxes not included
CHARUSAT × CLAIM