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SUMMER TRAINING PROGRAM 2026

No/Low-Code
Agentic AI & Automation

An implementation-first learning experience designed to help university students move from AI awareness to real-world system building. Build functional AI workflows, data agents, and operational MicroApps.

125 Total Hours
32h Live Sessions
93h Guided Practice
1,500 EGP Student Price
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AI MicroMind Summer Training Program Poster 2026

Program Executive Summary

The AI MicroMind Summer Training Program is an intensive, 1-month window designed to bridge the gap between abstract AI theory and practical systems engineering.

Participants build explicitly on the MicroMind Platform, a cutting-edge environment allowing rapid prototyping of agentic workflows and custom application deployments.

⚙️

MicroMind Core

A visual node-and-canvas environment powered by advanced concepts from LangChain and LangGraph in the background, allowing students to design complex agentic workflows and automated processes without writing code from scratch.

📱

MicroMind App

The final interaction and deployment layer where students learn to configure custom copilots, embedded website chatbots, webhook integrations, and real-time analytical report bots.

Program Snapshot

  • 🎯
    Program Name: AI MicroMind Summer Training Program (AI Agent Building)
  • 🕒
    Total Duration: 125 Hours (32 Hours Live + 93 Hours Practical Application)
  • 📅
    Delivery Rhythm: 8 Live Sessions (each 4 Hours long) over 1 month
  • 🎓
    Target Audience: University students, recent graduates, innovation clubs, and incubator participants
  • 🗝️
    Prerequisites: No coding background required. Curiosity, consistency, and a willingness to build are expected.
  • 🏆
    Primary Outcome: Design, test, and present a functional AI workflow, data agent, or operational ReportBot & MicroAPP.

What Makes the MicroMind Ecosystem Unique

Move beyond simple chat interfaces and step into operational systems engineering

01

Visual Workflow Automation

Build AI-powered processes visually on a canvas, connecting steps across prompts, conditional logic, external tools, and multi-channel outputs. Move past the limitations of standalone chatbots.

02

Zero-Hallucination Data Agents

Featuring a native, proprietary verification layer. Students learn how to build chat-to-data agents that guarantee 100% accuracy and complete traceability when querying structured enterprise databases, eliminating model hallucinations entirely.

03

Next-Generation ReportBots

Completely replace traditional BI software. Query systems using natural language and receive immediate answers in three distinct, configurable formats: direct answers, structured tables, or visual analytical charts matching the requested chart type.

Detailed 8-Day Curriculum Roadmap

A comprehensive breakdown of your 1-month learning journey

Day 1 AI Foundations, System Thinking & The Core Canvas ▼
📚 Core Concepts
  • AI Family Tree: Clarifying Artificial Intelligence, Machine Learning, and Deep Learning.
  • Transformers: How they work and why they shifted the paradigm toward Generative AI and GPT.
  • Mechanics of Generation: Understanding text generation mechanics on a token-by-token basis.
  • LLM vs. SLM: What raw Large Language Models and Small Language Models are.
  • The Spectrum: Practical differences between an Assistant, an Autonomous Agent, and Agentic AI.
  • Orchestration Frameworks: Why raw LLMs require orchestration to become secure corporate applications.
  • LangChain: Contribution of chains, memory, tool integrations, structured prompting, and predefined agents.
  • LangGraph: State management, conditional routing, cyclic loops, and multi-agent coordination.
  • Canvas Nodes: Mastering node categories on the MicroMind Core canvas and mapping to framework equivalents.
  • Execution Boundaries: Run Once vs. Schedule execution modes.
🛠️ Practical Workshop

Visualizing and constructing a primary multi-step text generation and processing workflow inside the MicroMind Core canvas.

🎯 Homework / Milestone

Create a comprehensive one-page AI system concept map and build a functioning workflow reflecting a specific student or business process use case.

Day 2 Prompt Engineering as Operational Design ▼
📚 Core Concepts
  • Prompts as Source Code: Why prompts act as the functional source code of every non-code AI agent.
  • Structured Prompt Engineering: The single most impactful skill for an enterprise AI system builder.
  • Production Techniques: Zero-shot, few-shot, role prompting, and chain-of-thought, and when to apply each.
  • Reading Research: How to read an AI white paper to get the knowledge into it in practice.
  • Role vs. Persona: The operational difference—and why detailed personas generate consistent, non-deviant business outputs.
  • Evaluation Loops: Designing iterative loops to continuously audit, refine, and improve prompt performance.
  • Node Prompts: Structuring prompts for visual workflow orchestration nodes rather than generic chat windows.
🛠️ Practical Workshop

Rewriting brittle, open-ended user queries into robust, structured prompt packages engineered for multi-path routing.

🎯 Homework / Milestone

Submit a targeted prompt package containing at least three high-reliability variants for automated customer classification and support workflows.

Day 3 Knowledge Grounding & Retrieval-Augmented Generation (RAG) ▼
📚 Core Concepts
  • Knowledge Gaps: Why public LLMs are inherently insufficient for business-specific data, and analyzing the three critical corporate knowledge gaps.
  • RAG Mechanics: How retrieval algorithms and text generation mechanics work together to ground answers in trusted information.
  • Architecture Phases: The clear distinction between the Ingestion Phase (one-time processing) and the Retrieval + Generation Phase (runtime query execution).
  • Precision Parameters: Configuring chunk size, text overlaps, and Top-K document retrieval thresholds.
  • Embedding Consistency: The embedding consistency rule: Utilizing identical embedding models for vector indexing and user query processing.
🛠️ Practical Workshop

Ingesting corporate document packages, setting up vector retrieval nodes, and comparing grounded outputs against baseline models.

🎯 Homework / Milestone

Build and deploy a functional knowledge assistant mapped to a chosen operational domain (e.g., University Admissions FAQs, Student Services guidelines, or company policies).

Day 4 Autonomous Agents, External APIs & System Observability ▼
📚 Core Concepts
  • Agents vs. Chains: How autonomous agents differ fundamentally from linear chains: Reasoning vs. executing a predefined sequence.
  • Core Agent Loop: Deconstructing the core agent loop: The Think → Act → Observe → Repeat (ReAct) pattern.
  • Architectural Decisions: When to deploy an agent versus a structured chain, and how this architectural decision impacts system stability and maintenance cost.
  • Canvas Tools: Analyzing MicroMind's 27 built-in canvas tools across standard, token-based, custom, and advanced action categories.
  • Web APIs: Understanding Web APIs and how structural JSON data payloads flow smoothly into an agent's reasoning loop.
  • Observability & Tracing: Production-grade debugging and execution tracing: Leveraging LangSmith backend concepts for real-time visibility into multi-agent systems.
🛠️ Practical Workshop

Developing an autonomous tool-using agent that dynamically selects external web services based on changing user contexts.

🎯 Homework / Milestone

Document an agent-driven process flowchart outlining precise tool boundaries, conditional failover paths, and a tracing validation checklist.

Day 5 Enterprise Data Agents & Zero-Hallucination SQL Architectures ▼
📚 Core Concepts
  • Database Structures: Relational query structure and dialect nuances across major corporate systems: PostgreSQL, MySQL, SQL Server, SAP HANA, Oracle, and Odoo.
  • Schema Hallucinations: Why generic AI agents hallucinate on database schemas: Unpacking the three terminal failure modes.
  • Schema-Aware Prompting: The single most critical technique for building highly reliable relational database query agents.
  • Zero-Hallucination Design: MicroMind's Five Zero-Hallucination Design Patterns: Runtime schema injection, strict data safety boundaries, automated SQL validation loops, programmatic error handling instructions, and validation chains.
  • Secure Connections: Structuring, managing, and authenticating secure database connection strings across 8 supported platforms.
🛠️ Practical Workshop

Engineering a secure, verification-first data agent that takes natural language data requests and extracts accurate relational queries with zero hallucinations.

🎯 Homework / Milestone

Author a comprehensive blueprint for a departmental database assistant, detailing the schema guardrails, validation rules, and connection parameters.

Day 6 Social Media Use Cases & External Channel Routing ▼
📚 Core Concepts
  • Micro-Architectures: Extending internal platform workflows to public-facing environments via MicroMind App micro-architectures.
  • Webhook Intake: Designing webhook intake channels to receive real-time, event-driven communications from external platforms.
  • Intelligent Routing: Constructing automated multi-path message routers that evaluate customer intent, extract fields, and prioritize response urgency.
  • Campaign Automation: Social media campaign automation: Structuring auto-response nodes, managing contact tags, and tracking campaign interactions safely.
  • Governance Rules: Setting hard rate-limits, input filtering, and configuring seamless human-in-the-loop escalation rules.
🛠️ Practical Workshop

Connecting an active webhook node to an automated text processing canvas to reply and route incoming customer interactions.

🎯 Homework / Milestone

Expand your core capstone architecture to incorporate at least one user-facing external communication channel or webhook pipeline.

Day 7 ERP Report Bots, Microapps & Capstone Studio ▼
📚 Core Concepts
  • Microapp Deployment: Deploying complex visual workflows into functional business microapps accessible to organizational users.
  • Report Bot Configuration: Configuring multi-view Report Bots: Mastering direct answering text, structured tabular formatting, and formal executive report formatting.
  • Replacing BI: Teaching an agent to convert a user question into a dynamic visual chart matching a requested chart layout.
  • Report Explorer: Utilizing the platform's Report Explorer View to log, cache, audit, and save routine operational reports.
  • Architecture Review: Capstone Architecture Review: Running technical evaluations on prompt security, data boundaries, and tool calling stability.
🛠️ Practical Workshop

Building an operational ERP Report Bot that takes raw business metrics and builds custom tables, reports, and visual chart cards instantly.

🎯 Homework / Milestone

Finalize your end-to-end capstone system configuration, script the presentation flow, and prepare the solution architecture validation notes.

Day 8 Final Project Demo Day & Career Portfolio Review ▼
📚 Core Concepts
  • Pitch Standards: Presentation and pitch standards for technical supervisors, business stakeholders, and enterprise partners.
  • Architectural Articulation: Articulating agent architectures, node logic, data grounding paths, and clear business outcomes.
  • System Governance: Addressing system limitations, data governance considerations, and mapping out subsequent operational phases.
  • Career Workshop: Translating no/low-code AI building experiences into clear portfolio items, resume lines, and talking points for corporate interviews.
🛠️ Practical Workshop

Live capstone project executions, end-to-end user experience demonstrations, and evaluation panel reviews.

🎯 Homework / Milestone

Submit your final production documentation package, including workflow canvas files, prompt manifests, and user guides for certification clearance.

Practical Capstone Project Tracks

Choose your track and build a functional agent for real-world enterprise needs

Track 1

Grounded Admissions / Student Support FAQ Bot

Build a specialized Retrieval-Augmented Generation (RAG) system grounded in official academic handbooks, university admissions guidelines, and calendars. Features human-in-the-loop escalation routing rules for complex inquiries.

Track 2

Enterprise Relational Data Q&A Assistant

Develop a verification-oriented database agent utilizing schema guardrails to query corporate relational databases safely. Delivers 100% accurate, hallucination-free SQL-based analytical results.

Track 3

Multi-View ERP Department Report Bot

Create an analytics microapp allowing business users to query key performance indicators using natural language. Generates direct text explanations, structured data tables, or visual analytical charts on the fly.

Track 4

Social Media Lead Intake & Routing System

Design a real-time event-driven automation pipeline. Receives public incoming messages via webhooks, evaluates customer lead intent using multi-path routers, and syncs fields across third-party CRM tools.

Assessment & Certification Framework

Certificates of completion are issued strictly to students who satisfy attendance guidelines and maintain passing scores across our structured evaluation metrics:

Capstone System Build Quality 40%
Weekly Labs & Homework Submissions 20%
Mini-Assignments & Short Reflections 15%
Final Demo Day Presentation 15%
Attendance & Lab Participation 10%

Strategic Value for Partners

  • Practical Career Readiness

    Students graduate with functional, verified project portfolios rather than abstract or passive theoretical exposure alone.

  • Broad Cross-Faculty Inclusion

    No coding requirements mean students from Business, Engineering, Information Systems, and Media can build advanced AI workflows side by side.

  • Direct Operational Value

    Capstone projects can be customized to resolve real institutional challenges, including student services support or administrative automation.

Training Gallery: Rounds Before in Action

Visual records showcasing the collaborative environments, practical laboratories, and presentation sessions from our past training cohorts.

Interactive Visual Orchestration Labs

Cohort Collaborative Labs

Students gather for peer testing and milestone reviews.

Hands-On Technical Mentorship

Hands-On Technical Mentorship

Direct guidance from industry experts on prompt schemas and tool integration.

Peer Testing & Iteration Checkpoints

Active Canvas Development

Deploying state logic and configuring webhooks inside MicroMind Core.

Start Your Journey Today

Take the leap from building prompts to engineering complete enterprise-grade agent systems. Cohort spaces are limited to ensure direct mentorship quality.

1
Form Filling

Please fill out the application form submitted with this training details email.

2
Make Payment

Transfer the fees (check pricing discount cards for student eligibility) and attach the receipt reference in your form submission.

3
Confirmation

You will receive a confirmation email with your assigned cohort location, start dates, and credentials.

OFFICIAL TRAINING TICKET

SUMMER 2026
27,000 EGP
1,500 EGP

* To claim the 1,500 EGP student rate, you must upload a valid student ID, university enrolment document, or graduation certificate.

Official Training Application & Payment Portal

Submit your application, select your preferred city, choose your cohort preference, and upload your payment transfer receipt directly in one single unified interface.