AI Summer Camp 2026 for the High School Students
Hands-on AI Summercamp for Students in High School. Today's AI enthusiasts in school are tomorrow's AI developers, leaders & entrepreneurs in industry. Build meaningful AI applications, master deep-learning fundamentals, and become an innovator in just 6 weeks. Gain mentorship from researchers at Top Universities & Industry Experts from Microsoft.
Limited Spots Available - Only 10 Students
Taught by world class mentors from universities like NYU & industries like Microsoft
Duration
6 weeks - 3 hour sessions/week
Class Size
Limited to 10 Learners on Each of the Project
Certificate
Included after Course & Project Completion
Cost
$600 after 25% discount on Early Registration
Why AI Skills Are Necessary
for High School Students?
AI is not the future, it's the present. High School Students with AI literacy have a massive advantage in college admissions, scholarships, and future careers.
College Advantage
AI projects in your portfolio make you stand out in competitive college applications. Show admissions officers you're ahead of the curve.
Future-Proof Skills
Every industry is being transformed by AI. From healthcare to entertainment, AI skills open doors to unlimited career opportunities.
Make Real Impact
Build AI solutions that solve real-world problems and help people. Create technology that makes a meaningful difference in society.
Your 6-Week Journey
Our 6-week intensive program focuses on one project. Not sure about where to begin? Contact us directly or choose any level!
Week 1 (3 hours)
AI Foundations & Python Mastery
Build solid conceptual and coding foundation - from zero to functional Python
Session 1: The AI Universe (1.5 hours)
Core Topics:
- What is Intelligence? Artificial vs. Human - defining intelligence beyond technicalities
- The AI Family: Machine Learning & Deep Learning with real-world analogies
- Three Flavors of Learning: Supervised, Unsupervised, Reinforcement
- AI Ethics & Responsible Innovation - bias prevention and fairness principles
Hands-on Activities:
- Interactive poll: 'Where have you seen AI today?' with pattern recognition discussion
- Visual mapping: Drag-and-drop real examples into AI/ML/DL categories
- 'Be the AI' game: Experience different learning types hands-on
Session 2: Python Power-Up (1.5 hours)
Core Topics:
- First Steps: Setting up your AI development environment
- Intro to Google Colab: Cloud-based Python notebooks
- Python fundamentals: Variables, loops, functions, and data structures
- Data manipulation with NumPy and Pandas
Hands-on Activities:
- 'Mad Libs' in Python: Creative variable and print() practice
- Number guessing game: Interactive conditionals and loops
- First data visualization: NumPy arrays plotted with Matplotlib
📚 Homework & Practice:
Complete curated Python challenges on HackerRank • Set up GitHub account
Week 2 (3 hours)
Project-Specific Foundations
Master the core concepts and tools needed for your chosen project
Session 3: Project-Specific Tools (1.5 hours)
Core Topics:
- Introduction to project-specific libraries and frameworks
- Setting up development environment for your project
- Understanding project requirements and success metrics
- Data collection and preprocessing techniques
Hands-on Activities:
- Set up project environment and required dependencies
- Explore and understand project dataset
- Create initial project structure and documentation
Session 4: Project Implementation - Part 1 (1.5 hours)
Core Topics:
- Core algorithm implementation
- Data processing pipeline development
- Initial model training and testing
- Performance metrics and evaluation
Hands-on Activities:
- Implement core project functionality
- Build basic data processing pipeline
- Train and test initial model version
📚 Homework & Practice:
Polish initial implementation • Document progress and challenges
Week 3 (3 hours)
Advanced Implementation
Enhance your project with advanced features and optimizations
Session 5: Advanced Features (1.5 hours)
Core Topics:
- Implementing advanced project features
- Performance optimization techniques
- Error handling and edge cases
- User interface development
Hands-on Activities:
- Add advanced features to your project
- Optimize performance and resource usage
- Implement robust error handling
Session 6: Project Implementation - Part 2 (1.5 hours)
Core Topics:
- Final model training and tuning
- User interface refinement
- Integration testing
- Documentation and code review
Hands-on Activities:
- Complete project implementation
- Refine user interface and experience
- Conduct thorough testing and debugging
📚 Homework & Practice:
Finalize project implementation • Prepare comprehensive documentation
Week 4 (3 hours)
Project Polish & Professional Showcase
Perfect your project and present to industry professionals
Session 7: Professional Development (1.5 hours)
Core Topics:
- Code quality and documentation
- Project presentation skills
- GitHub portfolio preparation
- AI career pathways and next steps
Hands-on Activities:
- Create comprehensive project documentation
- Build project showcase website
- Practice technical presentation
Session 8: Innovator's Showcase & Graduation (1.5 hours)
Core Topics:
- Live project demonstration
- Technical Q&A session
- Peer review and feedback
- Certification and next steps
Hands-on Activities:
- 15-minute project presentation
- Industry professional panel discussion
- Certificate ceremony and portfolio finalization
📚 Homework & Practice:
Final portfolio preparation • Update LinkedIn and GitHub profiles
Week 5 (3 hours)
Specialization and Advanced Topics
Dive deeper into specialized AI areas and advanced techniques
Session 9: Advanced AI Techniques (1.5 hours)
Core Topics:
- Neural Networks: Understanding layers, activation functions, and backpropagation
- Convolutional Neural Networks (CNNs) for image processing
- Recurrent Neural Networks (RNNs) and LSTMs for sequential data
- Transfer Learning and Pre-trained Models
Hands-on Activities:
- Build and train a simple neural network using TensorFlow/Keras
- Experiment with CNNs on image classification tasks
- Implement an RNN for text generation or prediction
Session 10: Specialization Deep Dive (1.5 hours)
Core Topics:
- Natural Language Processing (NLP) fundamentals
- Computer Vision applications and techniques
- Reinforcement Learning basics
- Ethics in specialized AI domains
Hands-on Activities:
- Create a sentiment analysis model using NLP
- Develop a computer vision project for object detection
- Build a simple reinforcement learning agent
📚 Homework & Practice:
Implement a specialized AI model • Research advanced techniques
Week 6 (3 hours)
Final Project and Showcase
Complete your masterpiece and present to industry experts
Session 11: Project Completion (1.5 hours)
Core Topics:
- Final project debugging and optimization
- Code review and best practices
- Performance evaluation and metrics
- Deployment considerations
Hands-on Activities:
- Debug and optimize your final project
- Conduct code review with peers
- Evaluate project performance and iterate
Session 12: Showcase and Networking (1.5 hours)
Core Topics:
- Effective project presentation techniques
- Industry networking and career advice
- Future AI trends and opportunities
- Portfolio building and next steps
Hands-on Activities:
- Present your project to mentors and peers
- Network with industry professionals
- Receive feedback and plan future projects
📚 Homework & Practice:
Finalize portfolio • Prepare for future AI opportunities
Frequently Asked Questions
Have questions about our Summer Camp? Here are some common queries we receive from students and parents.
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