Beginner
AI Explorers
Foundations, logic and first models
₹5,999 / program
3 months
- Intro to AI
- Block-based coding
- Build first AI models
- Logic & problem-solving games
Your child won't just learn AI.They'll build with it.
Structured AI education. Real Python, real mentors, and a personal AI companion.
Three levels. One path to mastery.
Each track builds on the last, from first AI concepts to real-world projects and capstones.
See full pricing and refund details →Intermediate
AI Builders
Real Python, data and ML projects
₹9,999 / program
6 months
- Python basics
- Build chatbots with LLMs
- Computer vision projects
- Ethics in AI
Advanced
AI Innovators
Deep learning, GenAI and capstones
₹15,999 / program
9 months
- Advanced Python & data science
- Neural networks & deep learning
- Generative AI (text & image)
- Capstone AI project
2
Expert AI mentors
3
AI programs
Free demo class
Tools and technologies used in our curriculum
Python·
TensorFlow·
OpenAI·
Scratch·
PyTorch·
Jupyter·
NumPy·
Pandas·
Keras·
VS Code·
Hugging Face·
Matplotlib·
Python·
TensorFlow·
OpenAI·
Scratch·
PyTorch·
Jupyter·
NumPy·
Pandas·
Keras·
VS Code·
Hugging Face·
Matplotlib·
HOW IT WORKS
Start the AI journey here
From booking a free demo to building real AI projects in just a few simple steps
01
Share Your Details
Share who is joining — name and which program interests them most.
02
Register Free
Register in under a minute. We instantly email your free demo link so you can jump into a session with a qualified AI mentor.
03
Start Learning
Dive into hands-on AI projects with expert mentor guidance and gamified challenges every session.
04
Get Certified
Complete the program and receive an AKMind certificate. Build a portfolio of real AI projects.
The AKMind Method
Learning that actually sticks
Not just videos. A complete AI learning experience engineered around how the brain actually learns. Every lesson. Every time.
01
Watch. Learn. Get Inspired.
Every lesson starts with an engaging 11-minute concept video. Real demos, animations and examples that make complex AI concepts feel simple and exciting.
11 min videoReal demosAI concepts simplified
Introduction to Neural Networks4:23 / 11:00
MISSION: Neural Network Challenge
> Training data loaded successfully...
> Accuracy: 94.2% ✓
> Mission complete! +150 XP
XP EARNED
02Our biggest differentiator
Play. Build. Remember.
After every lesson, an interactive story-based game reinforces what you just learned. You are not just watching AI — you are living it. This is what makes AKMind unforgettable.
Story-based gameInteractive challengesXP rewards
03
Recap. Reinforce. Master.
A focused 5-minute recap locks in everything you learned. Key takeaways, a mini-challenge, and a preview of what is coming next. Short. Sharp. Effective.
5 min recapKey takeawaysMini challenge
LESSON RECAP
Neural networks mimic the human brain
Layers process information step by step
Training improves accuracy over time
MINI CHALLENGE
Build a 2-layer network in the simulator →
Mentor Online
Why does the loss increase sometimes during training?
Great question! This is called overfitting. Let me show you...
Mentor is typing...
04
Ask. Clarify. Go Deeper.
Live Q&A sessions with your mentor after key modules. Got stuck? Confused? Your dedicated mentor is there to answer every question and push you further.
Live Q&AExpert mentorModule reviews
NEW05
Meet your AI Learning Companion
NOVA is with you throughout your entire learning journey. It takes notes during your lessons, answers your questions instantly, tracks your progress, and nudges you when you need a push. Think of it as a brilliant study buddy that never sleeps.
- Takes smart notes during every lesson
- Answers questions 24/7 between sessions
- Tracks your progress across all modules
- Sends personalised tips and reminders
- Celebrates your wins and milestones
AI
NOVA
Always online
Hi! I noticed you just finished Lesson 7. Great work on the neural network challenge!
Thanks! I'm confused about backpropagation though
No worries! Think of it like this: imagine the network is trying to find its way through a maze, and backprop is how it learns from wrong turns. Want me to show you a quick visual explanation?
Ask anything...
10
Modules per program
60
Bite-sized lessons
11
Min video per lesson
1
NOVA per learner
Gamified learning
Learning feels like a game.
Every lesson earns XP, unlocks badges and climbs the leaderboard — keep going, because the momentum is hard to resist.
Your Progress
AK
Aarav K.
Level 7 · AI BuilderXP Progress2,450 / 3,000 XP
12 Day Streak!
Keep it up!
+50 XPCompleted Lesson 7
+100 XPWon Neural Network Challenge
+25 XP7-day streak bonus
Achievements
Unlock badges as you learn
First Lesson
Coder
Speed Run
ML Master
Champion
On Fire
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???
???
Latest: AI Explorer badge unlocked!
This Week's Top Learners
1
RS
Rohan S.
3,240 XP2
PN
Priya N.
3,180 XP3
KI
Karthik I.
2,950 XP4
AR
Ananya R.
2,780 XP5
AK
Aarav K.You
2,450 XPWeekly Challenge
Complete 5 lessons this week
Progress3 / 5 complete
200+
Badges available to unlock
POWERED BY AI
Meet your personal NOVA — Your AI Learning Companion
Not a chatbot. Not a FAQ page. A genuine AI companion that knows your learning journey, understands where you are stuck, and guides you forward — 24 hours a day, 7 days a week.
Auto Note-Taking
24/7 Available
Progress Tracking
Smart Reminders
AI
NOVA
Watching your progress in real-time
LIVE
AI
Hey Aarav! I noticed you just finished Module 3. Your accuracy on the quiz was 87% — really impressive for your first attempt at classification algorithms!
Thanks! But I'm still confused about why we need to normalise data before training.
AI
Great question — this is actually one of the most important concepts in ML. Here is a simple way to think about it:
Imagine you are comparing the height of people (150–190cm) with their salary (₹30,000–₹5,00,000). Without normalisation, salary dominates everything just because the numbers are bigger.
Normalisation puts everything on the same scale so the model can learn fairly. Does that help? Want me to show you a hands-on example?
Imagine you are comparing the height of people (150–190cm) with their salary (₹30,000–₹5,00,000). Without normalisation, salary dominates everything just because the numbers are bigger.
Normalisation puts everything on the same scale so the model can learn fairly. Does that help? Want me to show you a hands-on example?
Yes please! Can you give me a coding example?
AI
Of course! Here is a simple example in Python:
from sklearn.preprocessing import MinMaxScaler scaler = MinMaxScaler() X_normalized = scaler.fit_transform(X_train) # Now all values are between 0 and 1 ✓
Try this in your next lesson! I have added it to your notes automatically.
AI
Ask NOVA anything...
Smart Notes
Automatically captures key concepts from every lesson
Always Available
Ask questions anytime between your sessions
Progress Insights
Knows exactly where you are in your journey
Personalised Tips
Tailored guidance based on your learning patterns
Why AKMind
Everything that makes AKMind different
Pre-recorded micro-lessons. Story-based games. Live mentor sessions. NOVA never sleeps. This is not just another online course.
Micro-Learning Format
11-minute concept videos designed for how the brain actually learns. Short, sharp and packed with real demos and animations.
Story-Based Games
After every lesson, an interactive story game puts you inside the concept. You are not watching AI — you are living it.
NOVA — Your AI Learning Companion
Your personal AI companion available 24/7. Takes notes, answers questions, tracks progress and keeps you motivated throughout.
XP, Badges & Leaderboards
Earn XP for every lesson completed, unlock achievement badges and compete on leaderboards. Learning has never felt this good.
Live Mentor Sessions
2 live sessions per module with expert AI mentors — for doubt clearing, project reviews and interactive group activities.
Verifiable Certificate
Complete a program phase and earn a digitally verifiable AKMind certificate — recognised in school portfolios and beyond.
Skills you will gain
Skills that prepare you for tomorrow's world
Python Programming
Machine Learning
Computer Vision
Natural Language Processing
Data Analysis
Deep Learning
AI Ethics
Problem Solving
Project Building
Critical Thinking
Neural Networks
Prompt Engineering
Meet Your AI Mentors
Learn from industry leaders building real-world AI systems.
Nagaraj Ethirajulu
Doctorate Researcher | Generative AI & Emerging Technologies
Nagaraj Ethirajulu is a Doctorate Researcher in Emerging Technologies with Generative AI as concentration. Nagaraj has over 20+ years of experience in IT Product and Services Industry. Nagaraj's core expertise spans Python, Machine Learning, Deep Learning, Neural Networks, Generative AI, Large Language Models, and Applied AI Research.
Jaibin Jose
AI Mentor & Industry Expert
A creative AI practitioner who makes deep learning accessible and thrilling. Known for turning abstract AI ideas into tangible projects.
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