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IT, Cloud & Networking12-month programme · Applied AI

Forward Deployed Engineering (FDE), Kochi, Kerala

Build AI. Integrate Industries. Deploy Real Solutions.

Become an industry-focused AI and software engineer who understands real business problems, builds intelligent applications, integrates enterprise and engineering systems, and deploys solutions into production. A 12-month programme at SMEClabs, Kochi, combining software engineering, artificial intelligence, industrial technologies and business operations.

  • Applied AI and software engineering, focused on deployment
  • Exposure to industrial, building, logistics and healthcare systems
  • Hands-on engineering labs and six industry projects
  • A final forward-deployment capstone, documented like real work
  • Two ways to learn: in the classroom at Kochi, or hybrid with online sessions
Who can join
  • B.Tech / BE
  • BCA / MCA
  • BSc Computer Science
Apply nowSee the curriculum

Prefer to talk? Call +91 99588 73874

A central AI platform linked to a factory, a hospital, logistics, automation, servers, a smart building, oil and gas, and embedded systems
programme
12 months
industry projects
6
industry pathways
9
Department
IT, Cloud & Networking
Mode
Classroom or hybrid
Duration
12 months

Your 12-Month Journey to Applied AI Engineering

A central AI platform linked to a factory, a hospital, logistics, automation, servers, a smart building, oil and gas, and embedded systems

Advanced

Forward Deployed Engineering (FDE) with Applied AI

Software engineering, applied AI, cloud deployment and industry systems over 12 months, ending in a forward-deployment capstone. Taught in the classroom or hybrid.

  • 12 months
Eligibility:
B.Tech / BE (CS, IT, Electronics, Electrical, Instrumentation), BCA, MCA, BSc Computer Science
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The 12-month curriculum

  1. Phase 1 (months 1–2): Programming & Engineering Foundations
    • Python programming
    • JavaScript and TypeScript fundamentals
    • Programming logic
    • Data structures and algorithms
    • SQL and database fundamentals
    • Linux
    • Git and GitHub
    • Software debugging
    • Unit testing
    • Technical communication
    • Practical outcome: a Python application connected to a database.
  2. Phase 2 (months 3–4): Full-Stack Software Engineering
    • React
    • Next.js
    • Backend development
    • FastAPI
    • REST APIs
    • PostgreSQL
    • Authentication and authorisation
    • Database design
    • API security
    • Application architecture
    • Automated testing
    • Practical outcome: a complete web application with authentication, APIs and a database, developed and deployed.
  3. Phase 3 (months 5–6): Applied AI & Intelligent Systems
    • AI and machine learning fundamentals
    • Large language models
    • LLM API integration
    • Prompt engineering
    • Retrieval-augmented generation (RAG)
    • Vector databases
    • AI agents
    • Function calling
    • Workflow automation
    • AI evaluations
    • AI security
    • Human-in-the-loop systems
    • Practical outcome: an AI assistant that retrieves information from documents and works with business APIs.
  4. Phase 4 (months 7–8): Industry Systems & Integration
    • Industrial automation overview
    • PLC and SCADA integration concepts
    • Instrumentation and sensor data
    • Embedded systems and IoT
    • MQTT and OPC UA
    • Networking and cybersecurity
    • Building management systems
    • Logistics and supply chain systems
    • Hospital administration workflows
    • HR and enterprise operations
    • Industry data integration
    • Practical outcome: a simulated or authorised industry data source integrated with a software and AI application.
  5. Phase 5 (months 9–10): Industry Specialisation
    • One primary pathway, chosen from the proposed pathways (which are open in an intake is confirmed at admission):
    • Industrial AI & Automation
    • Industrial IoT & Embedded AI
    • Smart Buildings & Energy
    • Networking & Cybersecurity
    • Oil, Gas & Marine Engineering Systems
    • Civil & Construction Operations
    • Logistics & Supply Chain
    • Healthcare Operations
    • HR & Enterprise Automation
    • Practical outcome: a domain-specific AI and software solution.
  6. Phase 6 (months 11–12): Forward Deployment Capstone
    • Client requirement gathering
    • Workflow analysis
    • Solution architecture
    • Agile project execution
    • System integration
    • Production deployment
    • Monitoring
    • Troubleshooting
    • Security reviews
    • Technical documentation
    • User acceptance testing
    • Project presentation
    • Technical interview preparation
    • Practical outcome: a working, documented, production-style industry solution.

Questions about this syllabus?

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  • Is Forward Deployed Engineering right for my degree?
  • Which industry pathway fits me?
  • The fee and the next intake at Kochi

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What Is Forward Deployed Engineering?

Beyond coding. Beyond AI. Into real-world engineering.

Forward Deployed Engineering is an approach in which technical professionals work closely with organisations to understand their operational problems, then develop, integrate, deploy and improve the software that solves them.

Forward Deployed Engineers combine software development, AI integration, systems engineering and problem solving. Unlike roles that only build isolated applications, forward deployment means putting solutions to work inside real business and engineering environments.

Traditional Software Developer

Builds software applications and features.

AI Application Engineer

Develops AI-powered applications and intelligent workflows.

Forward Deployed Engineer

Connects software, AI, business workflows and existing systems to deliver practical solutions.

  1. Industry problem
  2. Understand systems
  3. Build the solution
  4. Integrate
  5. Deploy
  6. Monitor & improve

Three Centres of Expertise. One Integrated Engineering Programme.

The programme brings together three parts of the SMEC group, each teaching the field it works in.

IT Division

Software, Data Science & Artificial Intelligence

  • Python programming
  • Full-stack development
  • Data science fundamentals
  • AI and generative AI
  • AI agents
  • RAG applications
  • Databases and APIs
  • Cloud deployment
  • Software engineering
  • DevOps

Engineering

Core Engineering & Industrial Technologies

  • Industrial automation
  • PLC and SCADA systems
  • Instrumentation and control
  • Embedded systems
  • Industrial IoT
  • Mechanical engineering systems
  • Civil engineering workflows
  • Oil & gas engineering
  • Networking: Cisco and Microsoft
  • Cybersecurity
  • Building management systems

Management

Industry Operations & Management Systems

  • Supply chain management
  • Logistics operations
  • Marine logistics
  • Hospital administration
  • Human resource management
  • Enterprise operations
  • Inventory and procurement
  • Business process management
  1. Full stack in AI
  2. Software + Engineering + Industry Operations
  3. Forward Deployed Engineering

From Programming Fundamentals to Industry Deployment

Software Engineering

Python, TypeScript, SQL, Git, Linux, software architecture, APIs, testing and full-stack applications.

Artificial Intelligence

LLM APIs, generative AI, RAG, AI agents, prompt engineering, tool calling, evaluation and responsible AI development.

Cloud & DevOps

Docker, CI/CD, cloud hosting, deployment pipelines, monitoring, application security and production troubleshooting.

Engineering Systems

Industrial automation, instrumentation, embedded systems, networking, IoT, BMS and engineering data integration.

Business & Industry Operations

Logistics, hospital administration, supply chain, enterprise operations, inventory, HR workflows and business systems.

Forward Deployment

Client requirement analysis, solution architecture, integration, implementation, deployment, testing, documentation and technical communication.

From Fresher to Industry-Focused AI Engineer

Six stages over 12 months; the modules of each stage are in the curriculum.

  1. FoundationMonths 1–2: programming, algorithms and databases
  2. BuildMonths 3–4: full-stack software applications
  3. IntelligenceMonths 5–6: AI, RAG and agents in your applications
  4. IndustryMonths 7–8: engineering and business systems
  5. SpecialiseMonths 9–10: one industry pathway
  6. DeployMonths 11–12: a complete industry-focused capstone

Your Portfolio. Your Projects. Your Engineering Career.

One Engineering Foundation. Multiple Industry Opportunities.

In months 9–10 you choose one primary pathway. These are proposed pathways: which ones are open in your intake is confirmed at admission.

Industrial Automation

AI-supported applications for factory monitoring, maintenance and industrial data analysis.

  • PLC data
  • OPC UA
  • MQTT
  • Python
  • RAG

Example: an assistant that answers maintenance questions from equipment manuals and alarm history.

Embedded Systems & IoT

Connect physical devices, sensors and edge systems with cloud and AI applications.

  • Microcontrollers
  • Sensors
  • MQTT
  • Edge devices
  • Cloud APIs

Example: sensor readings streamed to a cloud dashboard that flags anomalies.

Smart Buildings

Energy monitoring, building analytics and facility management applications.

  • BMS data
  • Energy meters
  • Time-series data
  • Dashboards

Example: an energy report that flags unusual HVAC consumption.

Networking & Cybersecurity

Intelligent network monitoring and incident investigation tools.

  • Syslog
  • SNMP concepts
  • Python
  • Log analysis

Example: a tool that groups network alerts and drafts an incident summary.

Oil & Gas

Engineering documentation, equipment information and maintenance workflow applications.

  • Document search
  • RAG
  • Maintenance records
  • Dashboards

Example: an equipment information assistant over technical documents.

Civil & Construction

Project monitoring, material tracking and construction operations tools.

  • Project data
  • APIs
  • SQL
  • Reporting

Example: a material-tracking dashboard for a construction site.

Logistics & Supply Chain

Shipment tracking, inventory intelligence and procurement applications.

  • SQL
  • APIs
  • AI agents
  • Dashboards

Example: shipment tracking with early delay alerts.

Healthcare Operations

Administrative workflow, scheduling and hospital operations applications.

  • Scheduling data
  • APIs
  • Synthetic data
  • Dashboards

Example: an appointment and queue dashboard for hospital administration.

HR & Enterprise Operations

Employee workflow, onboarding, reporting and business automation systems.

  • Workflow automation
  • APIs
  • AI agents
  • Reporting

Example: an onboarding workflow in which people approve each step.

Don’t Just Study Technology. Build Solutions for Real Industries.

Six flagship projects, built with simulations, synthetic data or authorised read-only data.

Engineers in a factory control room reviewing equipment-health dashboards beside PLC panels

Industrial Automation

Factory Intelligence Platform

An AI-supported industrial monitoring and maintenance platform that combines equipment data, technical documentation and intelligent fault analysis.

  1. PLC, sensors or simulated equipment
  2. Industrial gateway
  3. MQTT / OPC UA
  4. Backend API and database
  5. AI knowledge assistant
  6. Dashboard and maintenance advice
  • Python
  • FastAPI
  • MQTT
  • OPC UA
  • PostgreSQL
  • RAG
  • Next.js

Built on simulations or authorised read-only data: student AI systems never connect to live machine controls.

An operations analyst tracking shipments and warehouse data on several screens beside a warehouse

Logistics & Supply Chain

Smart Logistics Control Tower

A logistics intelligence platform for shipment monitoring, inventory visibility, delay analysis and operational reporting.

  1. Shipment, warehouse and inventory data
  2. API integration
  3. Central data platform
  4. AI analysis
  5. Logistics dashboard
  6. Operational recommendations
  • Python
  • SQL
  • APIs
  • Next.js
  • AI agents
  • Cloud
A hospital administrator managing appointment schedules on a computer at the front desk

Healthcare Administration

Hospital Operations Intelligence

An AI-supported hospital administration platform that helps manage appointments, queues, resources and administrative workflows.

  1. Appointment and scheduling data
  2. Hospital workflow integration
  3. Backend and database
  4. AI administrative assistant
  5. Operations dashboard
  • Next.js
  • FastAPI
  • PostgreSQL
  • APIs
  • AI

Synthetic data and privacy-safe practice; an administrative tool, never a diagnostic or medical decision-making system.

An engineer watching network topology and alert dashboards in front of server racks

Networking & Cybersecurity

Intelligent Network Operations Centre

A network operations platform that collects authorised telemetry, identifies anomalies, summarises incidents and supports troubleshooting.

  1. Routers, switches and network logs
  2. Monitoring integration
  3. Event processing
  4. AI incident assistant
  5. Network operations dashboard
  • Python
  • APIs
  • Syslog
  • SNMP concepts
  • PostgreSQL
  • AI
  • Next.js
A facility engineer reviewing HVAC and energy dashboards with rooftop air-handling units outside

Building Management Systems

Smart Building Intelligence

A building analytics platform for HVAC monitoring, energy reporting, equipment alarms and maintenance planning.

  1. BMS, HVAC and sensors
  2. Authorised data integration
  3. Data processing
  4. AI analytics
  5. Building management dashboard
  • Python
  • BMS data
  • Time-series data
  • AI analytics
  • Dashboards
A team of young engineers discussing workflow dashboards on a large screen

Enterprise Management

Enterprise AI Operations Platform

An integrated enterprise operations platform for CRM, HR, procurement, reporting and AI-assisted workflow management.

  1. CRM, HR and procurement systems
  2. APIs and data integration
  3. AI workflow engine
  4. Management dashboard
  5. Human-approved actions
  • APIs
  • PostgreSQL
  • AI agents
  • Workflow automation
  • Next.js

People approve every action the AI proposes.

From Industry Challenge to Working Solution

  1. DiscoverThe customer’s business, technical systems and operational challenges.
  2. AnalyseWorkflows, data sources, requirements, security and integration constraints.
  3. DesignSoftware architecture, database models, AI workflows and an implementation plan.
  4. BuildApplications, APIs, AI agents, dashboards and integrations.
  5. IntegrateSoftware connected with authorised enterprise, cloud and engineering systems.
  6. DeployA release with testing, access controls, monitoring and documentation.
  7. ImprovePerformance monitored, feedback collected, issues fixed, the system improved.

Learn in an Integrated Engineering Environment

AI Software Engineering Lab

Programming, APIs, databases, AI systems and full-stack applications.

Industrial Integration Lab

PLC, SCADA, instrumentation, embedded systems, IoT and industrial data integration.

Networking & Cloud Lab

Routers, switches, servers, cloud deployment, monitoring and cybersecurity.

Forward Deployment Studio

Industry case studies, requirement analysis, client simulations and capstone projects.

Career Pathways Beyond Traditional Software Development

A typical progression, step by step:

  1. Graduate
  2. Junior Software, AI or Implementation Engineer
  3. Software Integration or Solutions Engineer
  4. Forward Deployed Engineer
  5. Senior FDE, Solutions Architect or Technical Lead

Entry-level roles

  • Junior Software Engineer
  • AI Application Developer
  • Junior AI Integration Engineer
  • Implementation Engineer
  • Junior Solutions Engineer
  • Software Integration Engineer
  • Technical Support Engineer (software systems)
  • Junior Cloud / DevOps Engineer
  • Associate Forward Deployed Engineer, where openings exist

Progression depends on your skills, professional experience and employers’ requirements. Placement assistance is subject to institutional policy, your eligibility and performance, and employer selection.

Designed for the Next Generation of Engineering Graduates

Who can join

  • B.Tech / BE Computer Science
  • B.Tech / BE Information Technology
  • B.Tech / BE Electronics
  • B.Tech / BE Electrical
  • B.Tech / BE Instrumentation
  • BCA
  • MCA
  • BSc Computer Science

What you need

  • Basic computer knowledge
  • Logical reasoning
  • An interest in programming and AI
  • Willingness to learn industry systems
  • A problem-solving mindset

New to programming?

Students without programming experience may need a foundation module or a readiness assessment first. Other technical graduates join after an eligibility assessment.

Forward Deployed Engineering: Questions

What is Forward Deployed Engineering?

Forward Deployed Engineering focuses on understanding customer requirements and implementing software solutions within real operational environments. It combines software engineering, integration, deployment and communication skills.

Can fresh graduates learn Forward Deployed Engineering?

Yes. Fresh graduates can build the required foundations through structured software engineering, AI integration, industry exposure and deployment projects. Many professional FDE positions ask for prior experience, so graduates may begin in related junior roles.

Is coding required?

Yes. Programming is a core part of this programme. Students learn Python, TypeScript, databases, APIs and software development practice.

Do students learn artificial intelligence?

Yes. The curriculum includes applied AI, LLM APIs, RAG, AI agents, workflow automation, evaluation and AI integration.

Will students learn all engineering industries?

Students get an introduction to several engineering and business sectors, then focus on one primary pathway rather than trying to master every industry.

Is this a data science course?

No. The programme includes the data and AI concepts it needs, but its focus is building, integrating and deploying software and AI solutions.

Does the course include practical projects?

Yes: software applications, AI integration projects, industry simulations and a final deployment capstone.

What is the course duration?

12 months.

How is the course taught?

In two modes: in the classroom at SMEClabs, Kochi, or hybrid, which combines classroom sessions with online learning. A course advisor can help you choose the one that suits you.

What career opportunities are available?

Relevant pathways include software development, AI application development, systems integration, implementation engineering, solutions engineering and selected junior FDE roles.

Is placement guaranteed?

No. Placement opportunities depend on your skills, performance and eligibility, and on employers’ requirements.

Start your journey in Forward Deployed Engineering

The Future of Engineering Is Connected.

Learn to build intelligent software, understand real industries, integrate complex systems and deploy solutions that solve practical problems.

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