Hands-on AI, LLMs & Python
AI Expert: Hands-On AI, LLMs & Python
Advanced AI for teens — LLMs, NLP, vision, and real Python projects
- Grades
- Class 8–12
- Duration
- 60 live sessions
- Projects
- 30+ projects
- Rating
- 4.9 (140+)
12+ AI Builds
- Train & evaluate machine-learning models hands-on
- LLM-powered apps with prompt engineering
- NLP, computer vision & capstone AI projects
- 60 live sessions of advanced AI classes
What Hands-on AI, LLMs & Python covers
GeekashramJr's Hands-on AI, LLMs & Python course is an advanced live program for Class 8–12 teens with strong Python basics. Over 8–12 months, students train machine-learning models, build LLM-powered apps with prompt engineering, complete NLP and computer vision projects, and ship a capstone AI portfolio piece — all with live mentors from strong technical backgrounds.
By the end, your child will have
- Trained and evaluated a real machine-learning prediction model in Python
- Built an LLM-powered app using APIs, chains, and prompt engineering
- Completed a capstone AI portfolio project (vision, NLP, or LLM app) ready for hackathons or college profiles
- Advanced AI sessions
- 60Advanced AI sessions
- Portfolio AI projects
- 12+Portfolio AI projects
- Apps & prompt engineering
- LLMApps & prompt engineering
- Models & evaluation
- MLModels & evaluation
This course is for your child if they are…
A Teen Coder
Already comfortable with Python and ready for deeper AI engineering.
A Competition Prepper
Wants portfolio projects for hackathons, Olympiads, or admissions.
An AI Builder
Interested in LLMs, vision, NLP, and how real AI products work.
A Future Engineer
Aiming at CS, AI, or data science pathways after school.
Hands-on AI, LLMs & Python syllabus at a glance
Typical full-course pace: 60 live sessions. Modules run in order, and mentors adjust depth to the student.
| # | Module | Duration | Topics covered | Projects |
|---|---|---|---|---|
| 1 | Python for AI | 12–15 sessions | NumPy, pandas, and data workflows; Supervised learning fundamentals; Model training and evaluation | Dataset cleanup notebook; First ML prediction model |
| 2 | LLMs & Prompts | 12–15 sessions | How large language models work; APIs, chains, and tool use; Build LLM-powered applications | LLM chatbot app; Prompt engineering experiments |
| 3 | Vision & NLP | 12–15 sessions | Image classification projects; Text processing and NLP basics; Multimodal mini applications | Image classifier; Sentiment analysis tool |
| 4 | Capstone | 12–15 sessions | Scope a real-world AI problem; Ship and document the project; Present for competitions or admissions | Capstone AI portfolio project |
Projects students actually build
A sample of the work that comes out of Hands-on AI, LLMs & Python — every one built live with a mentor, not followed along from a video.
ML prediction model
Students work with NumPy/pandas datasets, train a classifier or regressor, and evaluate accuracy — foundational ML engineering practice.
- NumPy
- pandas
- Model evaluation
LLM-powered assistant app
A Python app that calls an LLM API with structured prompts, tool use, or chained steps — mirroring how real AI products are built.
- LLMs
- Prompt engineering
- APIs
Computer vision or NLP capstone
Image classification, sentiment analysis, or speech-related project polished for a portfolio demo and mentor review.
- Computer vision
- NLP
- Portfolio
Skills covered
- Python + AI tools
- Machine learning
- Neural networks
- LLMs & NLP
- Prompt engineering
- Vision & speech projects
Prerequisites & who can join
Strong comfort with Python basics is recommended. Class 8–12 students new to Python can start with our Python with AI track first (25–30 live sessions on average).
- Grade range
- Class 8–12
- Estimated duration
- 60 live sessions
- Class format
- Live online with GeekashramJr mentors
Hands-on AI, LLMs & Python — questions parents ask
Straight answers on syllabus depth, projects, pace and pricing for live Hands-on AI, LLMs & Python classes.
GeekashramJr's Hands-on AI, LLMs & Python course is an advanced live program for Class 8–12 teens with strong Python basics. Over 8–12 months, students train machine-learning models, build LLM-powered apps with prompt engineering, complete NLP and computer vision projects, and ship a capstone AI portfolio piece — all with live mentors from strong technical backgrounds.
Hands-on AI, LLMs & Python is taught live module by module (60 live sessions). Parents can review the full syllabus table on this page — topics, projects, and typical session time per module — plus download the curriculum brochure.
Students complete mentor-guided projects throughout the course. By the end they typically have: Trained and evaluated a real machine-learning prediction model in Python; Built an LLM-powered app using APIs, chains, and prompt engineering; Completed a capstone AI portfolio project (vision, NLP, or LLM app) ready for hackathons or college profiles. Sample project screenshots and walkthroughs are shown above.
Hands-on AI, LLMs & Python is for students in Class 8–12 (Class 3 to 12 at GeekashramJr). Strong comfort with Python basics is recommended. Class 8–12 students new to Python can start with our Python with AI track first (25–30 live sessions on average).
GeekashramJr Explorers starts at ₹499 per session (5 students), Champions is ₹799 per session (3 students), and Super Mentors 1:1 is ₹999 per session. Try a session to see the teaching style before choosing a plan. The trial fee is adjusted on enrolment.
Classes are live online with GeekashramJr mentors — not passive video courses. Students get real-time feedback, debugging help, and project reviews in every session.
Strong comfort with Python basics is recommended for Class 8–12 students. Teens new to Python can start with our Python with AI track first, then move into this advanced AI engineering course.
Students cover Python for AI, LLMs, prompt engineering, NLP, computer vision, model training, and a capstone AI portfolio project with live mentor guidance.
Yes. The capstone is designed as a documented portfolio piece — useful for hackathons, Olympiads, or admissions profiles — with mentor reviews on scope, evaluation, and presentation.
Most teens complete the journey in about 8–12 months of live sessions, depending on prior Python strength and how ambitious the capstone is.
Related reading
Parent guides and STEM articles that pair well with Hands-on AI, LLMs & Python.
- AI for Kids6 Minutes
Chatbots for Kids: How to Explain LLMs and AI to an 8-Year-Old | 2026
An LLM is like a super-fast pattern reader that predicts the next words — not a magic brain. Here’s a simple way to explain chatbots and AI to an 8-year-old, plus safe habits parents can teach at home.
Read - Python for Kids6 Minutes
Python Certification for School Students: Is It Worth It? | 2026
A Python certificate can motivate school students, but a project portfolio usually matters more. Certificates are worth it when they follow real skills — not when they replace learning with a paid PDF.
Read - AI for Kids7 Minutes
AI Literacy for Kids: What It Is and Why Schools Are Teaching It | 2026
AI literacy means kids can understand what AI is, where it is used, how to prompt safely, and when not to trust it. Schools are adding it because AI now shapes homework, creativity, and future careers.
Read
Not sure which track fits your child?
Book a 45-minute trial session. A mentor works with your child, sees how they think, and recommends the track. The trial fee is adjusted if you continue.