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Algo Labs Professional Diploma

Professional Diploma in
Forward Deployed AI Engineering

Programme at a Glance

Duration6 Months
Structure24 Weeks
Live Training120 Live Hours
What is Forward Deployed AI Engineering?

Forward Deployed AI Engineering combines AI engineering, business discovery, enterprise integration, production deployment and adoption ownership to move AI systems from problem definition into real operational use.

120 live hours of training across 24 weeks, with applied project work between sessions.

What will I build?

Permission-aware RAG systems
Agentic reasoning workflows
Deployed AI web applications
Evaluation & metrics harnesses
Architecture & threat models
Production API services
Stakeholder discovery artefacts
Scoped enterprise pilots

What a Forward Deployed Engineer does

Forward Deployed AI Engineering combines AI engineering, business discovery, enterprise integration, production deployment and adoption ownership to move AI systems from problem definition into real operational use.

Embedded Problem Solving
End-to-End Engineering
Measured Adoption

The delivery lifecycle

  1. 01DISCOVER

    Business problem discovery with stakeholders

  2. 02SCOPE

    Value hypothesis, guardrails, success measures

  3. 03ARCHITECT

    Solution, data and security architecture

  4. 04BUILD

    Engineering, evaluation and iteration

  5. 05DEPLOY

    Enterprise integration and production operations

  6. 06ADOPT

    UAT, adoption evidence and ownership handover

This is not another Generative AI tools course: the emphasis is business problem discovery, engineering, enterprise integration, production deployment, UAT, adoption and ownership.

Weekday Cohort

  • Monday – Friday
  • 1 hour / day
  • 5 live hours / week
  • 24 weeks = 120 live hours

Weekend Cohort

  • Saturday – Sunday
  • 2.5 hours / day
  • 5 live hours / week
  • 24 weeks = 120 live hours

Who is this programme for?

Final-Year Technology Learners
Graduates Entering AI Careers
Early-Career Software Engineers
Data & ML Practitioners
Systems Architects
Technology Consultants
Applied AI Researchers
Enterprise Solutions Engineers

Starting readiness

Python basics, Git, JSON, HTTP APIs, SQL, VS Code, Docker and structured problem solving.

Applicants may come from different academic or professional backgrounds if they demonstrate the required technical readiness.

Six-month curriculum

Six progressive months. Expand any month for detail — the outcome stays visible.

Month 1Engineering FoundationsShip a tested Python service backed by a real relational schema.
  • Python, Git and testing discipline
  • SQL, PostgreSQL and pgvector
  • AI solution selection and trade-offs
Month 2LLMs & Enterprise RAGBuild and evaluate a permission-aware retrieval system.
  • Prompt and context engineering
  • Embeddings, hybrid search, FAISS/ChromaDB
  • Evaluation harnesses and RAG security
Month 3Workflows, Agents & MCPDeliver a constrained agent with human approval gates.
  • LangChain and LangGraph state machines
  • Checkpoints and human-in-the-loop approval
  • MCP tools, memory and authorization
Month 4Enterprise ProductionRun your system as a secure, observable production service.
  • FastAPI, Pydantic, OAuth/OIDC, RBAC
  • Docker and Azure Container Apps
  • CI/CD, observability and rollback
Month 5Forward DeploymentTurn an ambiguous operational need into a scoped, piloted solution.
  • Stakeholder discovery and scoping
  • Architecture and value hypothesis
  • Pilot, UAT, adoption and handover
Month 6Domain Immersion + Project ORBITDefend an end-to-end enterprise outcome with evidence.
  • Responsible AI and India DPDP awareness
  • Domain discovery immersion
  • Project ORBIT build, UAT and viva
Signature Capstone

Project ORBIT

An evolving enterprise scenario. One defended outcome.

DISCOVERBUILDEVALUATEDEPLOYUATDEFEND

Example Programme Scenario

Permission-aware banking-operations knowledge assistant with approvals, integration, monitoring and adoption evidence.

Example programme scenario · Not a client project, live client engagement or placement project

Evidence Gates

DiscoveryArchitectureSecurityDeploymentUATAdoptionValueHandover

Outcomes

Discover & Scope
Architect & Govern
Build & Evaluate
Integrate & Secure
Deploy & Operate
Pilot & Adopt

Graduate evidence can include

Python servicePostgreSQL schemaFastAPI backendEvaluated RAGLangGraph workflowConstrained agentSecure MCP integrationDocker / Azure deploymentCI/CD pipelineObservabilityRollback runbookDiscovery packArchitecture & threat modelUAT & adoption plan

Assessment weighting

Overall programme weighting. The 20% capstone weight is the programme-level share of Project ORBIT and is separate from the internal capstone rubric used to grade it.

Exercises
10%
RAG
15%
Agents
15%
Production
15%
FDE Design
15%
Capstone
20%
Viva
10%
Total100%

Career pathways

Entry / Transition

  • AI Implementation Associate
  • Junior AI Solutions Engineer

Adjacent

  • Applied AI Engineer
  • GenAI Engineer
  • AI Integration Engineer

Progression

  • Forward Deployed AI Engineer
  • AI Delivery Consultant

The realistic first role depends on prior experience, demonstrated capability and employer requirements.

No job guarantee.

Employment, designation and compensation are not guaranteed. Compensation examples are published only in the FDE Career Guide.

Credentials

Professional Diploma in Forward Deployed AI Engineering

Issuance is subject to applicable programme, attendance, assessment, examination, evidence and authorised CTDS issuing requirements.

Optional External Credential / Examination Pathway
Microsoft Azure
Optional External Credential / Examination Pathway
IBM

Microsoft and IBM credentials are optional external examination pathways, separately issued by those organisations. Algo Labs does not award Microsoft or IBM certificates, and this diploma is not a government certified or government accredited diploma.

Ready to own the outcome?