⚡ The world is moving fast. Don't get left behind.

Learn Every AI Buzzword. Then Build With Them.

LLMs, Transformers, RAG, Agents, MCP, Embeddings, Multimodal — understand them all, then choose your path: Low-Code or Full-Stack AI Engineering

Course 1

Everyone AI

5 Weeks · No Coding

Learning, Using, Building, Scaling, and Optimizing AI.

Course 2

Embedded AI

8 Weeks · Low-Code

Hands-on with Copilot, Cowork, OpenClaw, automation & no-code agents.

Course 3

Embrace AI

16 Weeks · Full-Stack

Build RAG, agents, MCP servers. Deploy with Docker, K8s, cloud.

🎯

3 Programs

Foundation + 2 Tracks

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Fully Online

Live Classes + Recorded

👨‍🏫

Harvard Grad

Expert Trainers

🚀

Hands-On

Real Projects

Your AI Learning Journey

3 Phases of AI Adoption: Everyone AI → Embedded AI → Embrace AI

AI Foundations

5 Weeks Everyone AI

Learn every AI buzzword. Understand, use, build, scale, and optimize AI.

Foundation Topics:

  • Week 1: Learning AI — AI, ML, DL, GenAI, LLMs, Transformers, Encoder-Decoder, Embeddings, Multimodal AI, Training vs Inference, Reasoning Models, Agents & MCP
  • Week 2: Using AI — Prompt Engineering, Context Engineering, Models, APIs, Model Pricing, Hugging Face, Vibe Coding, Claude Code & Cowork, Computer Use & Browser Agents
  • Week 3: Building AI — RAG Pipelines, Text to SQL, AI Orchestration, Agents, Benchmarks, AI Safety and Guardrails
  • Week 4: Scaling AI — GPUs, NVIDIA, Cloud, Kubernetes, Running AI Locally, Hosting Open Source, Inference Servers, Model Deployment, Real-World Applications, Scale of Modern AI
  • Week 5 (Optional): Optimizing AI — Fine-Tuning, Quantization, Optimization, Hyperparameters, GPU Optimization

Everyone AI — 5 Week Foundation Curriculum

Week 1: Learning AI

Topics: AI, ML, DL, GenAI, LLMs, Transformers, Encoder-Decoder, Embeddings, Multimodal AI, Training vs Inference, Reasoning Models, Agents & MCP. Tokens & context windows. Self-attention & multi-head attention. Three types of language models. Parameters.

Tools: ChatGPT, Claude, Gemini, Perplexity AI

Outcome: Understand every core AI concept — from tokens to transformers to agents.

Week 2: Using AI

Topics: Prompt Engineering, Context Engineering, Models (Claude 4.6, Gemini 3.1, GPT-5, DeepSeek R1, LLaMA 4), APIs, Model Pricing, Hugging Face, Vibe Coding, Claude Code & Cowork, Computer Use & Browser Agents. Proprietary vs open source. Multimodal AI: images, video, voice, music.

Tools: ChatGPT, Claude, Gemini, Midjourney, Hugging Face, Claude Code, Cowork

Outcome: Navigate the full AI ecosystem — know what models exist, how to prompt them, and how to use AI tools hands-on.

Week 3: Building AI

Topics: RAG Pipelines, Text to SQL, AI Orchestration (LangChain, Google ADK, CrewAI), Agents, Benchmarks (MMLU, MTEB, SWE-bench, RAGAS, Chatbot Arena), AI Safety and Guardrails. Copyright & legal. Function calling & tool use.

Tools: Claude Code, Cursor, OpenClaw, Flowise, Dify

Outcome: Understand RAG, agents, orchestration, and the safety guardrails that matter.

Week 4: Scaling AI

Topics: GPUs (A100 → H100 → Blackwell Ultra), NVIDIA, Cloud (AWS, Azure, GCP), Kubernetes, Running AI Locally (Ollama, LM Studio, GPT4All), Hosting Open Source Models (vLLM, TGI), Inference Servers (NVIDIA Triton, TensorRT-LLM), Model Deployment, Real-World Applications, Scale of Modern AI.

Tools: Ollama, LM Studio, vLLM

Outcome: Understand the full deployment landscape — from local to cloud to enterprise-scale inference.

Week 5 (Optional): Optimizing AI

Topics: Fine-Tuning (SFT, RLHF), Quantization (GPTQ, AWQ, GGUF), Optimization techniques, Hyperparameters (temperature, top-k, top-p), GPU Optimization (mixed precision, batching, KV caching). When to fine-tune vs RAG.

Tools: Hugging Face Transformers, PEFT/LoRA, Ollama quantized models

Outcome: Know when and how to optimize AI models for cost, speed, and quality.

Choose Your Specialization Path

Embedded AI Specialist

8 Weeks Phase 2

Master AI Inside the Tools You Already Use

Prerequisite: Everyone AI Foundation (5 Weeks)

Track Highlights:

  • Productivity Copilots (Microsoft, Google, Apple)
  • AI Desktop Agents & Browser Automation
  • Workflow Automation (Zapier, n8n, OpenClaw)
  • AI for Images, Video, Voice & Music
  • No-Code Agents & Chatbots (Dify, Flowise)
  • Data, Evaluation & Guardrails
  • Capstone Build & Demo

Embedded AI Specialist — 8 Week Curriculum

Week 1: Productivity Copilots & Office AI

Topics: Microsoft Copilot in Word, Excel, PowerPoint, Outlook, Teams. Copilot Cowork (powered by Claude). Google Workspace AI: Gemini in Gmail, Docs, Sheets, Meet. Claude add-in for Excel & PowerPoint. Apple Intelligence: Siri, writing tools, notifications.

Outcome: Automate real weekly workflows using embedded AI tools across Microsoft, Google, and Apple ecosystems.

Week 2: AI Desktop Agents & Browser Automation

Topics: Claude Cowork: desktop agent for file management, reports, expense tracking. Claude in Chrome: browser reading, clicking, form-filling. OpenAI Operator. Claude Plugins & MCP Connectors. OpenClaw: personal AI assistant via WhatsApp/Telegram/Discord.

Outcome: Set up Cowork + Chrome agent + OpenClaw for real daily tasks.

Week 3: Workflow Automation & AI Pipelines

Topics: Zapier AI, Make (Integromat), n8n: triggers, actions, AI steps. MCP connectors for Google Drive, Slack, Notion, CRM. Always-on automations: cron jobs, webhooks, monitoring. AI inside Airtable, Retool, Notion.

Outcome: Build end-to-end automation (email → AI summarize → Slack → spreadsheet).

Week 4: AI for Images, Video, Voice & Music

Topics: Text-to-Image: Midjourney, DALL-E 3, Adobe Firefly, Leonardo AI, Flux. Text-to-Video: Sora, Runway, Pika Labs, Seedance 2.0. Voice: ElevenLabs, NotebookLM. Music: Suno, Udio. Canva Magic Studio, HeyGen, Synthesia.

Outcome: Create a brand kit (logo + video + voiceover) using only AI.

Week 5: No-Code Agents & Chatbots

Topics: Visual agent builders: Dify, Flowise, LangFlow, Botpress. Microsoft Copilot Studio. Knowledge-base chatbot from PDFs/URLs. Adding tools: web search, calculator, calendar. OpenClaw skills: building and installing community skills.

Outcome: Deploy a working customer support or internal FAQ agent.

Week 6: Data, Evaluation & Guardrails

Topics: Data prep for AI: chunking, cleaning. Testing: Chatbot Arena, Promptfoo, red-teaming. Prompt injection awareness & content filtering. EU AI Act basics. Copyright & ownership. Deepfake detection.

Outcome: Red-team your own chatbot, find and fix weaknesses.

Week 7: Capstone Build Sprint

Topics: End-to-end design and implementation. Example projects: "Build a Cowork workflow for weekly reporting", "Create an OpenClaw skill for team standup", "Design an MCP-powered Slack bot".

Outcome: Deliver a working MVP integrating 2–3 embedded AI tools.

Week 8: Capstone Demo & Review

Topics: Project presentation, ROI evaluation, risk discussion, lessons learned.

Outcome: Present final solution, document a reuse-ready runbook. Certificate ceremony.

Embrace AI Engineer

16 Weeks Phase 3

Build, Deploy & Scale Full-Stack AI Applications

Prerequisite: Everyone AI Foundation (5 Weeks)

Track Highlights:

  • Python, Claude Code & Vibe Coding
  • APIs, SDKs & Function Calling
  • RAG Pipelines & Vector Databases
  • Full-Stack AI (FastAPI + React)
  • AI Agents & Orchestration (LangChain, ADK, MCP)
  • Docker, Kubernetes & Cloud Deployment
  • Security, Guardrails & Performance

Embrace AI Engineer — 16 Week Curriculum

Week 1: Python, Dev Environment & AI-Assisted Coding

Git, Conda, VS Code/Cursor, Claude Code. Python refresher: NumPy, Pandas, scikit-learn. Vibe coding workflow. Claude Code: terminal-based agentic coding, voice mode, agent teams.

Outcome: Build a simple ML pipeline using vibe coding.

Week 2: APIs, SDKs & Function Calling

REST/GraphQL, async I/O. Anthropic SDK, OpenAI SDK, Gemini API. Structured outputs & function calling. Streaming responses (SSE). Building your first MCP server.

Outcome: Build data loaders + a working function-calling demo.

Week 3: Backend with FastAPI

Routes, Pydantic models, error handling, testing. Streaming LLM responses (SSE patterns).

Outcome: Ship a clean, modular AI-ready REST API.

Week 4: Databases & Vector Search

PostgreSQL, SQLAlchemy ORM. pgvector. Qdrant, Chroma, Pinecone. Embedding model selection (MTEB leaderboard).

Outcome: Implement semantic search over documents.

Week 5: RAG Pipeline Development

Chunking, retrieval, re-ranking (Cohere, cross-encoders). LangChain/LlamaIndex. Agentic RAG. Evaluation with RAGAS framework.

Outcome: Build a RAG system with citations.

Week 6: Frontend (React) for AI UX

Chat UIs, streaming, state management, auth flows. Vercel AI SDK.

Outcome: Build a real-time AI chat frontend.

Week 7: Full-Stack Integration

FastAPI + React; CORS, SSE/WebSockets, E2E testing.

Outcome: Deliver a full-stack, real-time AI chat app.

Week 8: Docker & Compose

Dockerfiles, multi-stage builds, secrets, Compose orchestration.

Outcome: Containerize your entire full-stack AI app.

Week 9: AI Agents & Orchestration

LangChain & LangGraph. Google ADK. OpenAI Agents SDK. CrewAI. Multi-agent systems.

Outcome: Build a multi-agent system.

Week 10: MCP Servers & A2A/ACP Protocols

Building production MCP servers. Advanced tool composition. A2A & ACP protocols. OpenClaw architecture case study.

Outcome: Build & publish an MCP server.

Week 11: Kubernetes & Scaling

Deployments, Services, Ingress, autoscaling. GPU scheduling.

Outcome: Deploy your AI app on K8s.

Week 12: Cloud Deployment (AWS/GCP/Azure)

EKS/GKE/Cloud Run, GitHub Actions CI/CD. Ollama for local/on-prem. Secrets management.

Outcome: One-click cloud deploys.

Week 13: AIOps, MLOps & Observability

OpenTelemetry, Prometheus/Grafana. LangSmith/LangFuse. Model registry, data drift detection.

Outcome: Monitor and alert on your AI pipeline.

Week 14: Security, Guardrails & Compliance

OAuth/JWT, rate limits. Prompt injection defense (OpenClaw case studies). MCP permissions. EU AI Act compliance. NeMo Guardrails, Guardrails AI.

Outcome: Harden your AI app against attacks.

Week 15: Performance, Cost & Optimization

Caching, batching, quantization, structured outputs. Prompt caching. Model routing (cheap vs expensive). Autoscaling.

Outcome: Reduce costs by 50%+ on your AI app.

Week 16: Capstone Launch & Presentation

Architecture planning, build sprint, staging deploy. Final deploy, load test, demo. Runbook documentation.

Outcome: Launch a production-grade, cloud-ready AI product. Certificate ceremony.

🎯

Hands-On Learning

Build real projects and applications from day one

👥

Small Cohorts

Personalized attention with limited class sizes

📜

Certificate

Industry-recognized certification upon completion

Our Services

Comprehensive AI/ML solutions for every need

🎓

Professional Training

Comprehensive AI training across all 3 phases of AI adoption

  • 5-week Everyone AI foundations
  • 8-week Embedded AI track
  • 16-week Embrace AI engineering track
Learn More →
💼

AI Consultancy

Strategic AI implementation and transformation for enterprises

  • AI strategy development
  • Custom AI solutions
  • Implementation support
Learn More →
⚙️

AI Development

End-to-end AI application development and deployment

  • Custom AI applications
  • MLOps & AIOps
  • Cloud deployment
Get Started →

AI/ML Consultancy Services

Transform your business with strategic AI implementation

Enterprise AI Solutions

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.

1

AI Strategy Development

Define your AI roadmap aligned with business objectives

2

Custom AI Development

Build tailored AI solutions for your specific needs

3

Implementation & Integration

Seamlessly integrate AI into existing systems

4

Training & Support

Upskill your team and provide ongoing support

Our Expertise

🤖

Machine Learning

🧠

Deep Learning

💬

NLP & LLMs

👁️

Computer Vision

⚙️

MLOps & AIOps

☁️

Cloud AI

Ready to transform your business?

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Learn from Industry Experts

World-class training from Harvard graduates and leading AI professionals

👨‍🏫

Expert Trainers

Our Training Team

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

Flexible Learning Options

Classes fully online • Live sessions • All lectures recorded

Class Schedule

Weekday Evening Batch

Monday - Thursday: 7:00 PM - 11:00 PM EST

Weekend Batch

Saturday & Sunday: 7:00 AM - 2:00 PM EST

✔ Classes fully online — attend from anywhere

✔ Online attendance available

✔ All sessions recorded for review

✔ Dedicated Slack community

Program Duration

Foundation + Embedded AI Track

13 Weeks Total

5 weeks foundation + 8 weeks hands-on

Foundation + Embrace AI Track

21 Weeks Total

5 weeks foundation + 16 weeks hands-on

Next Cohort Starts Soon

Reserve Your Spot

Get Started Today

Contact us for training enrollment or consultancy services

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Response time: Within 24 hours

Ready to Start Your AI Journey?

Next sessions starting July 2026 — Limited Seats! Contact us to discuss your training needs.

Next sessions starting July 2026 — Limited Seats! Reach out to block your spot NOW.

Frequently Asked Questions

What are the 3 phases of AI adoption?

Everyone AI = use AI tools directly (ChatGPT, Claude). Embedded AI = AI inside apps you already use (Copilot in Excel, Gemini in Gmail). Embrace AI = build with AI (RAG, agents, LangChain, Kubernetes). Our training takes you through all three.

Do I need to take the foundation course?

Yes, the 5-week Everyone AI foundation is mandatory for all students. It provides essential understanding needed for both the Embedded AI and Embrace AI tracks.

Can I switch tracks after starting?

You can decide on your track after completing the 5-week foundation. However, once you begin either track, we recommend completing it for the best learning experience.

Do I need coding experience for the Embedded AI track?

No coding experience is required. The Embedded AI track teaches you to leverage AI tools like Copilot, Cowork, and OpenClaw without programming.

What prerequisites are needed for the Embrace AI track?

Basic programming knowledge is helpful but not required. We'll teach Python from scratch, though familiarity with any programming language will help you progress faster.

Are classes in-person or online?

All classes are fully online with live instruction. Attend from anywhere in the world. All sessions are recorded so you can review at your own pace.

Do you offer corporate training?

Yes, we offer customized corporate training programs tailored to your organization's specific needs. Contact us for details.

What kind of certificate will I receive?

Upon successful completion, you'll receive an industry-recognized certificate from AIMLEngineers that you can add to your LinkedIn profile and resume.