School programs · Degrees · Professional courses

Don't just use AI. 
Build it. 

Live classes, real projects and a mentor by your side — from school programs to full Bachelor's and Master's degrees in AI and Data Science. Online from anywhere in the world, or on campus.

Explore degrees ↓
Approved & recognised by the University of Mysore
Students learning together at FuturAIse Academy
Live cohorts, online & on campus

Why FuturAIse exists

AI is writing essays, drawing art, and running companies. The students who understand how it works will shape what comes next. The ones who only watch will be shaped by it. We built FuturAIse to put your child on the right side of that line. 

How it works

Five steps. One transformation.

01

Take a free class

Meet your mentor. See how we teach. No payment, no pressure.

02

Get your level checked

A short, friendly assessment tells us exactly where to start you.

03

Follow your own path

A personal roadmap — from first steps to advanced AI — built for your age and goals.

04

Build every week

Real projects with a mentor beside you. Not videos. Not theory. Building.

05

Graduate with proof

A portfolio of working AI projects and a certificate to show for it.

Learning paths

A path for every age.

Six levels, one journey — start where you are, grow as far as you want.

Grades 6–7

AI Explorers

Fun AI tools, creative projects, first sparks of curiosity.

Included in the free class
Grades 8–9

AI Foundations

Core concepts, simple machine learning, first mini apps.

Included in the free class
Grades 10–11

AI Builders

Real datasets, model training, apps that actually work.

Included in the free class
Grade 12

AI Portfolio

Portfolio projects, advanced prompting, career direction.

Included in the free class
Degree students

Applied AI

Model building, deployment, internship readiness.

Included in the free class
After degree

AI Professional

Advanced LLMs, deep learning, job-ready specialization.

Included in the free class
Inside the academy

Real classes. Real people.

Learning here is live and human — mentors beside you, cohorts around you, whether you join online from anywhere in the world or sit with us in person.

Approved & recognised by the University of Mysore
Mentor sessions
Mentor sessions

Code reviewed side by side, not marked from a distance.

Live cohorts
Live cohorts

Small groups, cameras on, questions answered in the moment.

Study groups
Study groups

Projects built together — the way real teams work.

On campus & in schools
On campus & in schools

The same curriculum, taught face to face.

Your seat is
waiting.
Find your path
Careers

Where our learners land.

FuturAIse learners and alumni work at companies like these — across global tech, e-commerce, banking and consulting.

GoogleIBMDeloitteFlipkartOnePlusOnePlusSantanderRevolutBlack Arrow
Built by students

Not videos. Working projects.

Every course ends with something running — an app, a model, a dashboard. Hover any project to pause and look closer.

studybuddy.vercel.app
SBStudyBuddy● online
explain photosynthesis like I'm 12
Plants are tiny solar factories 🌱 They take sunlight, water and CO₂, and turn them into sugar (their food) and the oxygen you breathe…
Want a 3-question quiz on this?
Ask anything about your homework…

StudyBuddy — homework chatbot

A tutoring chatbot with memory of what the student got wrong last time.

Built in: Generative AI & Prompt Engineering · capstone

Claude APIReactVercel
localhost:7860 — object detector
person 0.98
person 0.97
laptop 0.91
yolo-v8 · 31 fps · 3 objects

Live object detection

YOLO detector running at 31 fps on a webcam feed, trained on a custom dataset.

Built in: Computer Vision · weeks 6–8

PyTorchYOLOOpenCV
sales-insight.streamlit.app
Store Sales — This Week▲ 18.2%
Revenue
₹1.84L
Orders
1,207
Top item
Masala tea
M
T
W
T
F
S
S

Retail sales dashboard

A real shop’s year of sales, cleaned and turned into decisions.

Built in: Data Analytics with Python & SQL · capstone

pandasSQLStreamlit
wa.me — order assistant
SK
Sharma Kirana Store
AI assistant · replies instantly
2 kg atta, 1L milk, bread bhejna
Order summary 🛒
Aashirvaad Atta 2kg₹142
Amul Taaza 1L₹74
Brown bread₹45
Total₹261
✓ ConfirmEdit order

WhatsApp order assistant

Takes grocery orders in Hinglish, builds the bill, confirms in one tap.

Built in: AI Agents & Automation · weeks 3–4

LLMWhatsApp APIFastAPI
colab — train.py
$ python train.py --model resnet18 --epochs 20
Loading dataset… 12,480 images · 10 classes
Using device: cuda (Tesla T4)
epoch 17/20 ━━━━━━━━━━━━━━━━ 390/390
loss: 0.2141 · acc: 92.7% · val_acc: 90.1%
epoch 18/20 ━━━━━━━━━━━━━━━━ 390/390
loss: 0.1987 · acc: 93.4% · val_acc: 90.8%
✓ best model saved → checkpoints/best.pt

Training an image classifier

ResNet fine-tuned on GPU: 93% accuracy, with the runs and graphs to prove it.

Built in: Deep Learning & Neural Networks · weeks 4–6

PyTorchColab GPUW&B
studybuddy.vercel.app
SBStudyBuddy● online
explain photosynthesis like I'm 12
Plants are tiny solar factories 🌱 They take sunlight, water and CO₂, and turn them into sugar (their food) and the oxygen you breathe…
Want a 3-question quiz on this?
Ask anything about your homework…

StudyBuddy — homework chatbot

A tutoring chatbot with memory of what the student got wrong last time.

Built in: Generative AI & Prompt Engineering · capstone

Claude APIReactVercel
localhost:7860 — object detector
person 0.98
person 0.97
laptop 0.91
yolo-v8 · 31 fps · 3 objects

Live object detection

YOLO detector running at 31 fps on a webcam feed, trained on a custom dataset.

Built in: Computer Vision · weeks 6–8

PyTorchYOLOOpenCV
sales-insight.streamlit.app
Store Sales — This Week▲ 18.2%
Revenue
₹1.84L
Orders
1,207
Top item
Masala tea
M
T
W
T
F
S
S

Retail sales dashboard

A real shop’s year of sales, cleaned and turned into decisions.

Built in: Data Analytics with Python & SQL · capstone

pandasSQLStreamlit
wa.me — order assistant
SK
Sharma Kirana Store
AI assistant · replies instantly
2 kg atta, 1L milk, bread bhejna
Order summary 🛒
Aashirvaad Atta 2kg₹142
Amul Taaza 1L₹74
Brown bread₹45
Total₹261
✓ ConfirmEdit order

WhatsApp order assistant

Takes grocery orders in Hinglish, builds the bill, confirms in one tap.

Built in: AI Agents & Automation · weeks 3–4

LLMWhatsApp APIFastAPI
colab — train.py
$ python train.py --model resnet18 --epochs 20
Loading dataset… 12,480 images · 10 classes
Using device: cuda (Tesla T4)
epoch 17/20 ━━━━━━━━━━━━━━━━ 390/390
loss: 0.2141 · acc: 92.7% · val_acc: 90.1%
epoch 18/20 ━━━━━━━━━━━━━━━━ 390/390
loss: 0.1987 · acc: 93.4% · val_acc: 90.8%
✓ best model saved → checkpoints/best.pt

Training an image classifier

ResNet fine-tuned on GPU: 93% accuracy, with the runs and graphs to prove it.

Built in: Deep Learning & Neural Networks · weeks 4–6

PyTorchColab GPUW&B
notequery.app
what did the professor say about overfitting?
Overfitting = the model memorises training data instead of learning the pattern. Fixes covered in class: more data, dropout, early stopping, and cross-validation.
📄 lecture-07-notes.pdf · p.3📄 ml-textbook-ch4.pdf · p.112
Indexed: 34 documents · 1,208 chunks · ChromaDB

NoteQuery — ask your notes

RAG over lecture PDFs: answers with page-level citations, no hallucinated sources.

Built in: NLP & Large Language Models · capstone

RAGChromaDBLangChain
demand-ai.streamlit.app
Demand forecast — next 7 daysProphet + XGBoost
today+21%
MAPE 6.8% on holdout— actual   ┄ forecast   ▒ 90% interval

Demand forecaster

Predicts next week’s sales with confidence intervals a shop owner can act on.

Built in: Machine Learning with Python · weeks 10–12

ProphetXGBoostpandas
agent-runner — trace viewer
Task
Compare pricing of 3 competitor gyms & draft a report
Planned: 4 steps0.8s
web_search("gym membership price bangalore")2.1s
read_page × 3 — extracted plans & prices5.4s
write_report(format="markdown")…
3 tools7 steps$0.04 run cost

Research agent with tools

An agent that plans, searches, reads and writes a report — every step visible.

Built in: AI Agents & Automation · capstone

AgentsTool useClaude API
cvcoach.app — review
Priya_Resume_v3.pdf
“worked on data analysis”
⚠ Add a number: analysed how many records? What changed?
“built a churn model (AUC 0.87)”
✓ Strong — specific and measurable
76
ATS score+18 this draft

CV Coach — resume reviewer

Reads a CV line by line, scores it against the job description, suggests fixes.

Built in: Machine Learning with Python · project week

NLPFastAPIscikit-learn
notequery.app
what did the professor say about overfitting?
Overfitting = the model memorises training data instead of learning the pattern. Fixes covered in class: more data, dropout, early stopping, and cross-validation.
📄 lecture-07-notes.pdf · p.3📄 ml-textbook-ch4.pdf · p.112
Indexed: 34 documents · 1,208 chunks · ChromaDB

NoteQuery — ask your notes

RAG over lecture PDFs: answers with page-level citations, no hallucinated sources.

Built in: NLP & Large Language Models · capstone

RAGChromaDBLangChain
demand-ai.streamlit.app
Demand forecast — next 7 daysProphet + XGBoost
today+21%
MAPE 6.8% on holdout— actual   ┄ forecast   ▒ 90% interval

Demand forecaster

Predicts next week’s sales with confidence intervals a shop owner can act on.

Built in: Machine Learning with Python · weeks 10–12

ProphetXGBoostpandas
agent-runner — trace viewer
Task
Compare pricing of 3 competitor gyms & draft a report
Planned: 4 steps0.8s
web_search("gym membership price bangalore")2.1s
read_page × 3 — extracted plans & prices5.4s
write_report(format="markdown")…
3 tools7 steps$0.04 run cost

Research agent with tools

An agent that plans, searches, reads and writes a report — every step visible.

Built in: AI Agents & Automation · capstone

AgentsTool useClaude API
cvcoach.app — review
Priya_Resume_v3.pdf
“worked on data analysis”
⚠ Add a number: analysed how many records? What changed?
“built a churn model (AUC 0.87)”
✓ Strong — specific and measurable
76
ATS score+18 this draft

CV Coach — resume reviewer

Reads a CV line by line, scores it against the job description, suggests fixes.

Built in: Machine Learning with Python · project week

NLPFastAPIscikit-learn
0

Learning paths, school to career

0+

Real AI projects in the curriculum

0%

Project-based — no passive videos

0:1

Mentorship in every path

Our promise

Why parents trust us.

A mentor, not a playlist

Every student gets a real person who knows their name, their level, and their goals.

Build from week one

The first project starts in the first week. Confidence comes from shipping, not watching.

Proof you can show

Students graduate with a portfolio of working AI projects and a certificate — evidence, not just claims.

Questions

Asked by every parent.

Your first class
is free.

One hour. A real mentor. A real project. See exactly how your child learns to build AI — then decide.

No payment details. We call you back within 24 hours.