DataRev — Data Revolution
Official Curriculum6/6 Modules • 9.0 Total Hours
Executive & Technical Program for Enterprises

Learning Path in Artificial Intelligence

Sequential and comprehensive path: from LLM fundamentals and token economics to agentic architecture, data engineering, and corporate governance.

Active Modules

6 / 6

Total Duration

9.0 Hours

Per Module

1.5 Hours

Methodology

Theory + Live Demos

Faculty & Institutional Pedigree

Taught by senior consultants who work, research, and teach at world-leading institutions.

Google

Professional experience & technical AI leadership

MIT

Faculty teaching & executive AI certification

Cambridge

Research & complex systems analysis

Wharton

Executive strategy & financial business vision

Columbia

Digital economics & leadership programs

Berkeley

Technological innovation & data architectures

Tec de Mty

Faculty professor & digital transformation leader

1.5 hrs

Module 1: AI Fundamentals

Conceptual foundations, internal LLM architecture, taxonomy and rigorous model evaluation criteria.

  • AI Background: Adoption curve and global industry impact.
  • What is AI really? LLM architecture and training datasets (Web, Reddit, public corpus).
  • Real usage patterns: HBR report insights (from productivity to companionship/coaching).
  • AI Taxonomy: Predictive, Generative and Agentic.
  • Modalities: Text, Audio, Video and Multimodality.
  • Model Evaluation: Benchmarks, LMSYS Chatbot Arena and LLM tracking.
  • Prompt Engineering Foundations: Structure and direct interaction techniques.
7 key topicsArchitecture & Evaluation
1.5 hrs

Module 2: AI-Driven Decision Making & Economics

Financial efficiency, token analytics, operational KPIs, and cost optimization via model routing.

  • AI Data-Driven Decision Making: Assisted executive decision making.
  • Tokenmaxing: Why more tokens do not equal higher productivity.
  • Monitoring & Control: Production token tracking and cost control tooling.
  • New KPIs: Measuring efficiency in Human-Machine collaboration.
  • LLM Economics: Cost structure and Model Routing strategies.
5 key topicsTokens & Cost Efficiency
1.5 hrs

Module 3: Intro to Vibe Coding & Code Quality

New programming dynamics with generative AI, code hygiene and synthetic redundancy elimination.

  • Intro to Vibe Coding: Intuition & AI-guided software engineering.
  • Deslopping: Techniques to detect and eliminate AI-generated code slop.
  • Real-time Demos: Live build and interaction in real environment.
  • Vibe Coding vs Pair Programming: Operational differences and strategic fit.
4 key topicsDeslopping & Live Demos
1.5 hrs

Module 4: Agentic Workflows & Architecture

Transitioning to autonomy: MCP protocols, orchestrators, evaluator agents, and visual vs custom code automation.

  • Intro to Agentic Workflows: From static responses to autonomous workflows.
  • No-Code vs Custom Code: No-Code Automation (n8n) vs Custom Code / Pair Programming.
  • Agent Ecosystem: MCPs (Model Context Protocol), Skills, Tools and Protocols.
  • Multi-Agent Architecture: Orchestrators, critique subagents and validation loops.
4 key topicsMulti-Agent Systems & MCP
1.5 hrs

Module 5: Advanced AI Engineering & Data Systems

Production infrastructure: Harness engineering, persistent memory, next-gen RAG architectures and semantic layers.

  • Harness Engineering: Designing execution harnesses for agents.
  • Fine-Tuning vs Context: Fine-Tuning vs Context Augmentation.
  • RAG Evolution: Traditional RAG, GraphRAG and Hybrid RAG.
  • Agent Memory: Short-term and long-term memory management.
  • Observability & Lineage: Observability, Monitoring and Lineage in AI systems.
  • Text-to-SQL: Natural language querying with a Semantic Layer.
6 key topicsGraphRAG & Agentic Memory
1.5 hrs

Module 6: Governance, Security & Ethics in AI

Corporate hardening, prompt injection prevention, algorithmic bias mitigation, and governance frameworks.

  • AI Governance: Control frameworks in corporate environments.
  • AI Cybersecurity: Vulnerabilities, Prompt Injection, privacy and data leakage.
  • AI Ethics: Biases, transparency and corporate accountability.
3 key topicsCompliance & Cybersecurity
Corporate Investment Structure & Custom Quote

Proportional Calculator & Enterprise Packages

Select attendees, adjust module duration, and check/uncheck modules of interest. Investment and per-head pricing update 100% proportionally and transparently.

Proportional Quote Simulator

Active config: 6 of 6 modules • 1.5 hrs/module

Proportional Scaling:100%
30 pax
10 pax (Mínimo)50 pax (Base $25k)100 pax (Enterprise)
1.5 hrs / mod
0.5h (Express)1.5h (Estándar Base)3.0h (Profundo Labs)
3. Select Modules to Include:6 / 6 Selected
Price per Attendee$550 USD
Configured Duration9.0 total hrs
Estimated Investment$16,500 USD
Savings vs. US Courses~$49,500 USD

Basic Tier

Core Training Anchor

$25,000USD
  • 9 hours of live delivery covering all 6 modules
  • Standard course materials and slide decks
  • Coverage for up to 50 participants ($25,000 USD flat package)
  • Digital completion certificate
Corporate Sweet Spot

Recommended Tier

Corporate Sweet Spot

$38,000USD
  • 9 hours of live training (all 6 modules)
  • Company AI maturity analysis included
  • Final graded assignment & project assessment included
  • Executive materials, prompt cheatsheets, code & workflow templates
  • Full video recordings of all 6 sessions for attendees
  • Optimized coverage for up to 75 attendees ($38,000 USD flat package)
  • Asynchronous Q&A support for the duration of the course

Premium Enterprise

Maximum Value & Custom Adaptation

$55,000USD
  • Enterprise coverage for up to 100+ attendees ($55,000 USD corporate cap)
  • Use case customization with company real data & process flows
  • Full access to executive materials, tools, and interactive labs
  • Private 4-hour Advisory & Q&A session with C-Level / VPs
  • Pre-training agentic maturity assessment & implementation roadmap included
🧠 ROI Justification & Corporate Academic Value:In-person executive courses at institutions like MIT PE or Emeritus range between $1,500 and $3,500 USD per person. Bringing this modular program in-house with tailored duration and topic selection delivers massive budget savings and immediate team upskilling.

Modular Cumulative Progression Methodology

Selected setup: 6 modules with 1.5h per module (9.0 total hours).