epicITAPPLIED AI ACADEMY
Programs / Machine Learning & AI EngineerAdvanced PATHWAY

Train. Evaluate. Deploy.

Developers and data professionals building predictive systems. Learn to build systems with hands-on projects and applied engineering.

PROGRAM OVERVIEW

Machine Learning & AI Engineer

Train. Evaluate. Deploy.. Develop practical competencies through focused labs, project work and a final capstone.

Who this program is for

Developers and data professionals building predictive systems.

Career alignment

Machine Learning Engineer, AI Engineer. Role alignment describes relevant skills and does not guarantee employment.

YOUR LEARNING BLUEPRINT

From understanding
to implementation.

01Mathematical Foundations+

Skills and technologies you’ll develop:

PythonStatisticsLinear Algebra

Hands-on lab: apply these concepts, test the results and document engineering decisions.

02Machine Learning+

Skills and technologies you’ll develop:

Supervised LearningUnsupervised LearningFeature Engineering

Hands-on lab: apply these concepts, test the results and document engineering decisions.

03Deep Learning+

Skills and technologies you’ll develop:

Neural NetworksPyTorchTransformers

Hands-on lab: apply these concepts, test the results and document engineering decisions.

04Model Adaptation+

Skills and technologies you’ll develop:

Fine-TuningModel Evaluation

Hands-on lab: apply these concepts, test the results and document engineering decisions.

05Production ML+

Skills and technologies you’ll develop:

ML PipelinesGPU ComputingModel Serving

Hands-on lab: apply these concepts, test the results and document engineering decisions.

Show what you can build.

PROJECT 1

Predictive model

Build a working system with defined requirements, evaluation and documented limitations.

PROJECT 2

Model evaluation suite

Build a working system with defined requirements, evaluation and documented limitations.

PROJECT 3

Deployed inference service

Build a working system with defined requirements, evaluation and documented limitations.

FINAL CAPSTONE

Demonstrate practical competency.

Train or fine-tune and deploy an ML/AI model against a defined business problem.

Before you begin.

Prerequisites

Python and readiness for statistics and linear algebra.

Professional credential

Machine Learning & AI Engineer Professional Certificate. Completion requires published coursework, assessments, projects and capstone requirements. Final passing scores, exam attempts and grading policies will be confirmed for your cohort before enrollment. This is an Epic IT certificate, not a university degree or third-party accredited qualification.

Career pathway

Build on this program with a related engineering pathway or industry specialization.

Questions, answered.

How long is this program?

Schedule and duration to be confirmed.

What is the delivery format?

Online, live and in-person options subject to cohort availability.

What is tuition?

Tuition information coming soon. Pricing, payment plans, start dates and enrollment deadlines will be confirmed before purchase.

What technology do I need?

A reliable computer, internet access and the ability to run development tools. Cloud/API requirements and additional costs will be disclosed in the cohort syllabus.

Is employment guaranteed?

No. Programs develop competencies and portfolio evidence; employment depends on individual preparation and market conditions.

Keep building.

Apply Now