EdJAMON connects learners with industry-focused, project-based internship programs and professional mentorship to build job-ready skills. Our programs cover modern technologies, practical projects, and real-world experience to help students and professionals accelerate their careers.

Become a full-stack AI developer in 3 months. Learn frontend, backend, and database essentials before diving deep into Machine Learning, Deep Learning, Generative AI, and AI Agents. Includes hands-on projects, mentorship, and placement support.
This comprehensive 3-month program by Edjamon bridges the gap between web development and AI. It equips learners with the skills to design, build, and deploy AI-powered applications from scratch — covering web technologies, machine learning, LLMs, and AI agents through hands-on projects and real-world mentorship.
Apply your learning through real-world projects that build your portfolio
Progress through our comprehensive program which makes qualified professional to earn their awards





Begin your journey with foundational skills and basic certification.
Master the most in-demand tools and technologies for data analytics
Hear from our students who have transformed their careers
Discover the difference between Edjamon and traditional platforms
| Features & Criteria | EdJAMON | Others |
|---|---|---|
Duration | 3 Months (structured & project-based) | Short courses with no integrated AI focus |
Curriculum Depth | From Web Stack to LLMs & AI Agents | Focuses on isolated AI topics only |
Project-Based Learning | 3 Major AI Projects + Capstone | Limited or no real-world projects |
Deployment Training | Docker, Flask, FastAPI, Cloud Deployments | No deployment or CI/CD coverage |
Mentorship & Review | Live mentor sessions, weekly feedback | Pre-recorded self-paced content |
Placement Support | Resume building, mock interviews, job drives | No placement or community support |
Explore exciting career opportunities
Explore our specialized programs to accelerate your career
Access curated external resources to deepen your understanding
Official guide for GPT models and API usage
Pre-trained models, datasets, and community resources
Open-source LLaMA models and implementation guides
Claude AI research papers and documentation
Complete guide to building LLM applications
Data indexing framework for LLM applications
Step-by-step RAG implementation
Efficient open-source LLM models
Cloud-native vector database for AI applications
Facebook's efficient similarity search library
Open-source ML-first vector database
Open-source embeddings database
OpenAI's official prompt engineering best practices
Academic foundation for RAG architectures
Real-world RAG implementation patterns
Security and ethical considerations for AI apps
Containerization and deployment guide
CI/CD automation and workflow automation
Build data apps with simple Python scripts
Cloud deployment and infrastructure setup
Complete Python language reference
Modern Python web framework for APIs
Numerical computing with Python
Data manipulation and analysis library
Find answers to common questions