Applied AI Systems - ML and LLM Engineering
Build practical AI systems using Python, XGBoost, LangChain, OpenAI APIs, MLflow, and Retrieval-Augmented Generation (RAG). Through one continuous enterprise project, students develop job-ready skills in machine learning, LLM applications, and production AI workflows.
Why Learn Applied AI Systems?
While many AI courses focus on theory or individual tools, Applied AI Systems focuses on what employers need today: professionals who can design, build, deploy, evaluate, and manage complete AI systems that combine Machine Learning (ML) with Large Language Models (LLMs) in real business environments. The program is specifically designed to teach production-grade hybrid AI systems rather than isolated AI techniques.
Integrates machine learning, natural language processing, LLM engineering, and cloud deployment into one comprehensive, high-value career pathway.
Organizations across banking, healthcare, retail, and technology are aggressively investing in practical AI applications and enterprise system integration.
Stay at the forefront of technology with cutting-edge tools: Python, XGBoost, LangChain, OpenAI APIs, MLflow, Docker, and Retrieval-Augmented Generation (RAG).
Career opportunities upon graduation
This program will prepare you with skill and experience to be competent and competitive in the following positions:
Admission Requirements:
1. University degree in data analytics, statistics, mathematics, business analytics, computer science, marketing, healthcare analytics, finance, engineering or a related field — OR equivalent professional experience.
2. Able to use at least one analytical tool or language (SQL, Python, R, Excel, or Power BI).
3. Pass an admission interview.
Who Should Take This Course?
This course is designed for professionals and graduates seeking to build or elevate their enterprise data analytics capabilities.
- Data Analysts
- Business Analysts
- IT Professionals
- Healthcare Professionals
- Software Developers
- Recent University Graduates
- Career Changers
What You Will Learn
The course is organized into three progressive subjects. Throughout the course, you will develop a continuous enterprise analytics project that demonstrates your practical skills and serves as a professional portfolio.
Subject 1 – Machine Learning Foundations & AI System Design
Build core machine learning skills in Python, model evaluation, and gradient-boosted modelling. Students apply these skills to Project Phase I by developing and documenting the foundational model for the continuous enterprise project.
Subject 2 – LLM Engineering & Hybrid AI Systems
Build an LLM-powered RAG pipeline and integrate it with the Phase I machine learning model. Students create a hybrid AI decision platform, track experiments with MLflow, and complete Project Phase II with a live demonstration and technical report.
Subject 3 – AI Systems Capstone: Governance & Delivery
Transform the Phase II platform into a governed, monitored, production-style AI system. Students develop governance, CI workflow, and drift-monitoring artifacts, finalize the GitHub portfolio, and present the completed system as the capstone project.
Build an Enterprise Project
Using Machine Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), LangChain, MLflow, and GitHub, you'll progressively develop a hybrid AI platform from initial model development to production monitoring and governance. By graduation, you'll have a portfolio-ready, GitHub-hosted AI solution that demonstrates your ability to build real-world AI systems and showcases your technical skills to prospective employers. The program is intentionally structured around one continuous enterprise project that integrates machine learning, LLM orchestration, evaluation, governance, and deployment.
Throughout the project, you'll gain hands-on experience with:
- Machine Learning Models
- Retrieval-Augmented Generation (RAG)
- LLM Applications
- Monitoring & Deployment
- GitHub Portfolio
- AI Governance
- Live Industry Presentation
Why Study at Metro College?
Metro College of Technology has delivered SAS training for more than 23 years as part of more than 25 years of career education. The revised course combines instructional experience with current enterprise analytics practices, AI-assisted workflows, and portfolio-based learning.
- Career-Focused Learning
- One Continuous Project
- Live Instructor-Led Delivery
- Small class sizes
- AI with Validation Discipline
- Flexible Delivery
Selected Employers That Have Hired Metro SAS Graduates
SAS Certification
In today's data-driven economy, organizations rely on trusted analytics to make business-critical decisions. While many analytics professionals work with Python, R, and SQL, SAS remains a leading analytics platform in highly regulated industries where accuracy, governance, auditability, and compliance are essential. Earning SAS certification or developing SAS skills can help you demonstrate your ability to work with enterprise analytics tools that continue to be widely used in sectors such as banking, insurance, healthcare, pharmaceuticals, government, and public health.
If you want to know more about the SAS certificate exam, please visit SAS® Global Certification Program website.
Frequently Asked Questions
Find answers to common questions about the Applied AI Systems - ML and LLM Engineering course.
Rather than focusing only on theory, this program teaches students how to build, deploy, monitor, and govern complete AI systems using machine learning and LLMs.
Yes. Students develop one continuous enterprise AI project and graduate with a GitHub-hosted portfolio demonstrating production-ready AI engineering skills.
You'll work with Python, XGBoost, LangChain, OpenAI APIs, MLflow, Docker, GitHub, vector databases, and modern AI engineering workflows.
Applicants should have a degree in any field or relevant experience in data, analytics, or software development, or related field, along with good computer skills.
Graduates may work as Applied AI Engineers, Machine Learning Engineers, Senior Data Analysts, Data Scientists, AI Systems Analysts, LLM Applications Developers, and related AI professionals.
If you are interested in a career as data analyst or data scientist, please visit our Data Science and Artificial Intelligence program.
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