Build Your AI Project [1-on-1]

Start any time | 4 weeks | ₹ 48,000 | Grade 9-12

What you'll learn

One-on-one mentorship to design, build and publish a working AI project of your own, from idea to finished product.

Outcomes

Design and build a working AI project from scratch, based on a real problem you choose
Ship it live: finish with a working link anyone can open and use, not just a prototype on your laptop
Record a short demo video showing what your project does and how it works
Write a technical writeup on GitHub or Notion explaining what you built, why, and how
Learn how agentic AI systems perceive, plan, and act, and how to design one yourself
Build with no-code and low-code AI tools, or choose the optional Python track (Grade 11-12) for more technical depth
Work one to one with a mentor who builds AI systems professionally
Submit your project to global competitions
Get published on Futurowise. See projects published by past students
Earn a certificate with unique credential id
Build a project and a way of thinking about AI that stands out on college applications

Details

When: Rolling admissions. Start any time.

Duration: 4 weeks of mentorship per project

Timings: One-on-one sessions. Timings will be mutually decided based on the student’s availability.

Commitment: 12 hours: 6 hours of live one to one sessions and feedback, 6 hours of foundation videos and self paced work

Where: Online (on Zoom, plus asynchronous mentor support)

Recommended For: Grade 9-12

For students interested in:

AI, Coding, Business, STEM, Critical Thinking

Overview

Week 1 | Idea and design Narrowing a broad interest into a specific, buildable AI project idea. Understanding what makes a good agent task: a clear goal, the information it needs, and the actions it should take. Mapping the project on a structured design template with one to one mentor feedback. Week 2 | Building the base Setting up the chosen no-code or low-code tools. Building the first working version of the agent or AI tool. Mentor sessions focus on unblocking students and reviewing early builds. Week 3 | Testing and refining Running the project against real scenarios and inputs. Finding where it breaks, fixing it, and improving how it performs. Mentor sessions dig into specific problems in the student's build. Week 4 | Demo and deploy Finishing touches on the project. Preparing a short demo and a project writeup that explains what was built, why, and how it works. Deploying and completing the writeup.

Instructor(s)

	Surekha Ananthapalli Data Science Associate Manager at Accenture Strategy and 5Consulting, Applied Intelligence Hub. Has mentored three Futurowise cohorts to date.
	Saara Anand Software Engineer at a Fortune 500 company and an experienced AI and Data Science trainer. Expertise in developing real-world machine learning, natural language processing, and data-driven solutions.

I enjoyed researching for the project given to us, which were then very well evaluated and we were given valuable feedback about the real-world applicability.

Anwita

Jamnabai Narsee School, Mumbai