For teachers, coordinators, instructional designers, academic managers and training professionals who want to move beyond ad-hoc tool use and apply AI to real problems in learning, content, assessment, productivity and education management.
You work on a real challenge across the eight weeks and leave with a demonstrable educational solution, validation criteria and an application plan — not eight disconnected exercises.
8 weeks · 20h live · applied project · no programming required
Joining individually does not mean working only on personal projects. Teachers, coordinators and managers can apply the project where they work. In dedicated cohorts, team problems and capabilities enter the journey design.
For professionals who want to increase their ability to teach, create, assess, analyze and decide with AI.
For organizations that want to build applied capability while their professionals work on real problems from their own education operation.
The program answers different problems depending on the role. Explore what each profile learns and builds — the real challenge remains the common core.
Plan, adapt materials, assess and give feedback with AI without outsourcing pedagogical judgment.
See problems, learning and deliverable
Problems
You learn
You build
Align objectives, practice and assessment and create reusable standards.
See problems, learning and deliverable
Problems
You learn
You build
Prioritize experiments and structure adoption with risk visibility.
See problems, learning and deliverable
Problems
You learn
You build
Turn business needs into learning with practice and transfer.
See problems, learning and deliverable
Problems
You learn
You build
Document good practices and turn individual experience into a shared asset.
See problems, learning and deliverable
Problems
You learn
You build
You do not need to arrive with a ready project. The first activities help identify, scope and turn a real need into a viable project.
Your problem is not on the list? Bring it anyway.
Teachers and institutions already experiment with AI tools. The challenge is turning that use into better pedagogical decisions, learning experiences and ways of working — without giving up authorship, quality, privacy or responsibility.
AI is used because it is available, not because there is a clear teaching, learning or operational need.
Producing content faster does not automatically mean teaching or learning better.
The more AI enters content, assessment and feedback, the more important validation, authorship and professional judgment become.
The idea starts from High Individual Contributor: professionals who use AI to expand their capacity to analyze, decide, build and deliver. At EBAC, we believe this only truly works with Human in Control: people keeping judgment, evidence and responsibility for what AI does.
More capacity to analyze, decide, build and deliver with AI.
People keep judgment, validation, evidence and responsibility.
Apply the method to a relevant problem, product, service or opportunity, with mentoring.
More capability with AI. People stay in control.
Every synchronous HIC program starts from a real problem. The domain changes; the method core does not: learn only what is needed to build, verify, and prepare application and transfer with human judgment.
Define the problem, people, baseline, constraints, expected value, and success criteria before choosing technology.
Technical and methodological depth follows the challenge and participant role — not a fixed tool checklist.
Turn learning into a solution, workflow, analysis, prototype, artifact, or decision that fits the context.
Test quality, evidence, risks, and limits while keeping review, accountability, and Human in Control.
Document, define ownership, and prepare next steps so the learning can be reused and improved beyond one person.
Implementation does not automatically mean production deployment: each context keeps its own security, approval, integration, and decision gates.
The value of the program also changes by institution type. Explore what each context faces, develops and can build — without promising guaranteed systemic transformation.
Train by maturity levels and take good practices to scale.
See context and application
What is usually blocked
What the program develops
What can be built
Simple, applicable solutions with heterogeneous infrastructure.
See context and application
What is usually blocked
What the program develops
What can be built
A coherent AI-use proposal with autonomy and an institutional standard.
See context and application
What is usually blocked
What the program develops
What can be built
New assessment formats and teacher development without removing academic autonomy.
See context and application
What is usually blocked
What the program develops
What can be built
Bring learning and performance closer with more efficient production.
See context and application
What is usually blocked
What the program develops
What can be built
Technology comes after the educational need. The participant starts by understanding the problem, defines what must change, builds a solution proportional to the context and produces evidence to decide what to do next.
Who is affected, what the need is and how the problem is solved today.
Objectives, evidence, constraints and success criteria.
A suitable experience, activity, assessment, content or workflow.
Use AI to accelerate research, production, adaptation, analysis or automation.
Pedagogical quality, accuracy, accessibility, authorship, privacy and risk.
Compare with the baseline using evidence appropriate to the problem.
Document and turn an individual good practice into reusable capability when it makes sense.
8 weeks with practical deliverables applied to the vertical context.
Week 1
Identify a relevant teaching, learning, training or management problem and document how it works today.
Topics
Lab
Brief of the education problem
Validation criteria
Week 2
Understand generative AI capabilities and limits and build a disciplined way of working with it.
Topics
Lab
Work harness applied to the project
Validation criteria
Week 3
Turn the need into objectives, evidence and a coherent solution design.
Topics
Lab
Educational solution blueprint
Validation criteria
Week 4
Build or adapt materials with AI while keeping pedagogical intent, accessibility and authorship.
Topics
Lab
Building the main artifact
Validation criteria
Week 5
Redesign assessment and feedback for a context where learners and professionals also use AI.
Topics
Lab
Assessment and feedback design
Validation criteria
Week 6
Identify repetitive tasks and turn the suitable ones into more efficient, verifiable workflows.
Topics
Lab
Applied workflow or prototype
Validation criteria
Week 7
Test whether the solution is good enough for use and identify conditions needed for implementation.
Topics
Lab
Solution validation
Validation criteria
Week 8
Consolidate the project and decide how it can enter individual, team or institutional practice.
Topics
Lab
Final project consolidation
Validation criteria
Alan Dantas
Managing Director EBAC Business / Fundador Edugital
Academic coordination of HIC Education. Over ten years at the intersection of education, technology, and institutional transformation.
Managing Director of EBAC Business and founder of Edugital. Over ten years at the intersection of education, technology, and institutional transformation.
Training teachers and professionals. Creation of Instructional Design courses and methodologies.
Implementation, governance, and AI training in organizations of different sizes, including EBAC.
Teaching experience at institutions such as Ibmec, EBAC, and other educational organizations, combining pedagogical theory with applied classroom practice.
In-class demonstrations use simulated educational scenarios. Final pedagogical decisions remain under faculty and institutional responsibility. Faculty and guests vary by cohort.
EBAC has been training market professionals for years: we know which skills the market is demanding right now — and where many teams still get AI wrong.
Executive applicationAI as a leadership and decision topic, not just a technical tool.
Team in the fieldHands-on workshops with professionals from leading companies.
Governance and cultureBuilding criteria, not just experimenting — from adoption to control.
Real executionMixed cohorts of HR, leaders and specialists apply in practice.
Fill out the form below and our team will contact you.
Corporate cohorts
Talk to our team about in-company implementation and dedicated cohorts.
Still have questions? Talk to our team.
Chat on WhatsAppYou do not need to arrive with the solution — nor with a fully structured problem. The program helps turn a real need into a viable project, build an answer and decide how to apply it with quality and responsibility.
