Start with AI foundations, then choose your path: Low-Code/No-Code tools mastery or Full-Stack AI Engineering
3 Modules
Foundation + 2 Tracks
Flexible Format
Long Island, NY or Online/Live Classes
Harvard Grad
Expert Trainers
Hands-On
Real Projects
Comprehensive AI/ML solutions for every need
Comprehensive AI/ML training from foundations to advanced engineering
Strategic AI implementation and transformation for enterprises
End-to-end AI application development and deployment
Start with foundations, then choose your specialization path
Master AI/ML concepts before diving into hands-on work
AI Concepts: Artificial Intelligence vs Machine Learning vs Deep Learning, Natural Language Processing (NLP) basics, Generative AI: what it is and why it matters
Key Outcome: Understand core terminology, where AI is applied, and how Generative AI differs from traditional ML
Foundation Models (GPT, Gemini, Claude, LLaMA), Prompt Engineering techniques, Context Engineering, LLM Hallucinations, RAG basics, Finetuning & RLHF
Key Outcome: Gain insight into how large models are built, used, and adapted for specific needs
AI Agents & Agentic AI, AI Orchestration (LangChain, LangGraph, LlamaIndex), AI Gateways, AI Guardrails, Inference & Optimization, MCP/A2A (Model Context Protocol, Agent-to-Agent)
Key Outcome: Understand how advanced AI systems are structured and controlled in production environments
AI Tools & Development: SaaS platforms, Low-code/No-code solutions, Pro-code frameworks, "Vibe Coding" tools
Business Applications: Use cases across industries, ROI evaluation, ethical and regulatory considerations
Key Outcome: Identify tools for your role and design simple AI-driven solutions
Master GenAI tools without coding
ChatGPT, Claude, Gemini basics; system vs user prompts; structured outputs
Outcome: Create high-quality prompts; compare model strengths; produce repeatable outputs
Midjourney, DALL·E, Adobe Firefly; prompt patterns; basic editing; licensing & ethics
Outcome: Design on-brand images/video snippets with clear prompt recipes
Zapier/Make: triggers, actions, webhooks; plugging LLM steps into workflows
Outcome: Build end-to-end no-code automations that use LLMs for summarization, drafting, tagging
Notion AI, Microsoft Copilot, Google Workspace AI; meeting notes, doc drafting, analysis
Outcome: Integrate AI into daily ops; create repeatable business templates
Flowise/LangFlow builders; Replit Agents; knowledge-base bots from PDFs/URLs
Outcome: Ship a domain FAQ bot with retrieval and basic tools (web, calculator)
Dataset prep, chunking basics, prompt tests, red-team checks; privacy settings
Outcome: Improve accuracy, reduce hallucinations, and protect data
Plan & implement a real workflow/app (marketing, support, research assistant, etc.)
Outcome: Deliver an MVP integrating 2–3 tools (chat+automation+KB)
Present solution, lessons learned, ROI & risk discussion
Outcome: Communicate impact; document runbook for handoff
Build & deploy full-stack AI applications
Env setup, git, NumPy/Pandas, scikit-learn refresher
Outcome: Productive dev setup; implement simple ML pipeline
REST/GraphQL, async I/O, ETL patterns, cleaning
Outcome: Robust data loaders from APIs/files
Routes, Pydantic, error/logging, testing
Outcome: Ship a clean AI-ready REST API
Schema design, SQLAlchemy, CRUD, migrations
Outcome: Persist users, sessions, logs, configs
OpenAI/HF embeddings; pgvector/Chroma/Pinecone
Outcome: Build semantic search over documents
Chunking, retrieval, re-ranking; LangChain/LlamaIndex chains
Outcome: Ground LLM answers with citations
Chat UIs, streaming, state mgmt, auth flows
Outcome: Usable AI app frontends
CORS, SSE/WebSocket streaming, E2E tests
Outcome: Smooth API↔UI data flow
Dockerfiles, multi-stage builds, env/secrets
Outcome: Reproducible containers for all services
Deployments/Services/Ingress; configs; autoscaling intro
Outcome: Run the app reliably on K8s
EKS/GKE or Cloud Run; GitHub Actions pipelines; secrets managers
Outcome: Push-button deploys to cloud
OpenTelemetry, Prometheus/Grafana; model/version registry; data drift
Outcome: Monitor, alert, and iterate models & prompts
OAuth/JWT, rate-limits, input validation; prompt-injection defenses; PII handling
Outcome: Ship safer AI apps with policy checks
Caching, batching, async; model selection/quantization; autoscaling
Outcome: Faster responses, lower spend
Team architecture, milestones, staging deploy
Outcome: Production-grade LLM/RAG app
Final cloud deploy, load test, demo, post-mortem
Outcome: Operable app with docs, runbook, and roadmap
Build real projects and applications from day one
Personalized attention with limited class sizes
Industry-recognized certification upon completion
Transform your business with strategic AI implementation
We help organizations leverage AI/ML technologies to drive innovation, improve efficiency, and gain competitive advantage. Our expert consultants bring years of experience in implementing AI solutions across industries.
Define your AI roadmap aligned with business objectives
Build tailored AI solutions for your specific needs
Seamlessly integrate AI into existing systems
Upskill your team and provide ongoing support
Ready to transform your business?
Schedule ConsultationWorld-class training from Harvard graduates and leading AI professionals
Expert Trainers
Harvard Graduates
Our lead instructors are Harvard University graduates with specialization in Data Science and AI Engineering
Industry Experience
20+ years of combined experience in AI/ML product development at leading tech companies
Real-World Expertise
Currently leading AI transformation initiatives at Fortune 500 companies
Dedicated Support
Personalized mentorship and career guidance throughout your learning journey
Our Mission: Bridge the gap between academic theory and real-world AI implementation
Join from Long Island, NY or attend online • Live sessions • Recorded lectures
Monday - Thursday: 7:00 PM - 11:00 PM EST
Saturday & Sunday: 7:00 AM - 2:00 PM EST
✔ In-person option in Long Island, NY
✔ Online attendance available
✔ All sessions recorded for review
✔ Dedicated Slack community
12 Weeks Total
4 weeks foundation + 8 weeks hands-on
20 Weeks Total
4 weeks foundation + 16 weeks hands-on
Next Cohort Starts January 2026
Reserve Your SpotContact us for training enrollment or consultancy services
Response time: Within 24 hours
Yes, the 4-week AI Overview module is mandatory for all students. It provides essential conceptual understanding needed for both the low-code and pro-code tracks.
You can decide on your track after completing the 4-week foundation course. However, once you begin either the low-code or pro-code track, we recommend completing it for the best learning experience.
No coding experience is required for the low-code/no-code track. It's designed to teach you how to leverage AI tools without programming.
Basic programming knowledge is helpful but not required. We'll teach Python from scratch in the pro-code track, though familiarity with any programming language will help you progress faster.
Yes! Students can flexibly switch between in-person attendance in Long Island, NY and online participation based on their schedule and preferences. All sessions are recorded regardless of format.
All sessions are recorded and available within 24 hours. You can watch at your convenience and ask questions in our community forum.
Yes, we offer customized corporate training programs tailored to your organization's specific needs. Contact us for details.
Upon successful completion, you'll receive an industry-recognized certificate from AIMLEngineers that you can add to your LinkedIn profile and resume.