R&D-backed, project-based curriculum taught by active practitioners — from ML fundamentals to cutting-edge LLMs and Agentic AI
From beginner to advanced — structured AI programs built on our real R&D and project experience
Master core ML concepts with hands-on Python projects. Learn how R&D principles apply to building reliable, reproducible models.
Build, train, and deploy deep learning models using TensorFlow and PyTorch — grounded in research-led best practices.
Explore prompt engineering, fine-tuning LLMs, RAG pipelines, and building AI-powered applications from research to product.
Design and deploy autonomous AI agents that plan, reason, and execute complex multi-step tasks — the frontier of applied R&D.
Learn to build end-to-end ML pipelines, deploy models, and maintain AI systems at scale — bridging R&D with production.
Build vision systems for image classification, object detection, segmentation, and video analytics — applied to R&D problems.
Our training is powered by our active R&D work and real-world AI project experience
Our syllabus evolves with our ongoing research — you learn from the bleeding edge, not outdated textbooks.
Build a portfolio of real AI and R&D projects. Every module ends with something you can showcase.
Learn directly from engineers and researchers who actively build and ship AI products — not just trainers.
Career coaching, resume reviews, mock interviews, and direct referrals to our partner companies.
All course recordings, materials, and community access remain yours for life — update your skills anytime.
Completion certificates endorsed by our industry partners and backed by our R&D credentials.
Join professionals and students who learn from active AI researchers and engineers at Thinguva AI Solutions.