🎯 Promise
“No tech background required — become job-ready for AI-enabled corporate roles with real projects and portfolio.”
✔ No coding required
✔ Real workplace scenarios
✔ Live training
✔ Career guidance
✔ Practical workflows
🧭 LEARNING PATH (Designed for Beginners)
We follow a confidence ladder:
1️⃣ Understand AI
2️⃣ Use AI daily
3️⃣ Work with data
4️⃣ Build simple solutions
5️⃣ Automate workflows
6️⃣ Apply in business scenarios
7️⃣ Prepare for corporate roles
“Learn AI like a working professional — not like a student.”
Highlight outcomes:
- Use AI tools daily at work
- Automate tasks
- Corporate productivity skills
- AI portfolio
- Career clarity
- Confidence in interviews
Remember — this is career acceleration, not coding.
🔵 PHASE 1 — AI Basics & Confidence Building (Weeks 1–4)
Goal: Remove fear of AI.
Teach slowly:
- What AI is (simple mental models)
- How generative AI works
- Prompt basics → advanced prompting
- Everyday productivity workflows
- Writing emails, summaries, research with AI
- Professional communication
- LinkedIn setup from scratch
- Career mindset training
Beginner Exercise:
“Use AI to plan a weekly work schedule.”
Outcome:
Students feel capable.
🟢 PHASE 2 — Data Literacy Without Coding Fear (Weeks 5–8)
Goal: Make data approachable.
Teach:
- Excel basics → AI automation
- Understanding datasets
- Simple analysis
- Power BI dashboards (step-by-step)
- Data storytelling basics
- Resume building
No jargon overload.
Outcome:
Students can interpret business data.
🟡 PHASE 3 — Build Simple AI Tools (Weeks 9–12)
Goal: Show creation is possible.
Teach:
- No-code tools
- Simple AI assistants
- Building small workflows
- Basic website project
- Testing outputs
Outcome:
Students feel “I can build”.
🔴 PHASE 4 — Automation Thinking (Weeks 13–16)
Goal: Teach efficiency mindset.
Teach:
- Workflow basics
- Automation logic
- Make platform step-by-step
- n8n introduction
- Process mapping
Exercise:
Automate a simple reporting task.
Outcome:
Students think like operators.
🟣 PHASE 5 — AI in Corporate Functions (Weeks 17–20)
Goal: Connect learning to real jobs.
Teach with scenarios:
- AI in marketing teams
- AI in operations
- AI in HR workflows
- AI in sales
- Presentations with AI
- Business communication
- Ethics basics
Outcome:
Students see career relevance.
⚫ PHASE 6 — Capstone + Placement Bootcamp (Weeks 21–24)
Students:
✔ Solve a real business problem
✔ Build AI workflow or tool
✔ Present solution
Placement Training:
- Resume polishing
- Mock interviews
- Confidence training
- Case discussions
- Corporate etiquette
Outcome:
Interview ready.
🧠 Beginner Support System (Critical)
To ensure success:
✔ Weekly doubt sessions
✔ Recorded replays
✔ Step-by-step guides
✔ Slack/WhatsApp community
✔ Beginner office hours
This reduces dropout.
💼 Roles Students Can Apply For
Realistic entry roles:
- AI Operations Associate
- Junior Business Analyst
- Digital Transformation Trainee
- Data Support Executive
- AI Productivity Specialist
This keeps placement honest.
📊 Difficulty Design Principle
👉 “No prior experience assumed”
👉 “We build from fundamentals”
👉 “Hands-on from Week 1”