AIML02 - Applied A.I. and Machine Learning
Program Description
You know how artificial intelligence (A.I.) and machine learning are shaping decisions across industries; now it’s time to put that into practice with real-world applications and data analysis. This online professional certificate program features live sessions that focus on supervised and unsupervised learning, clustering, deep learning, and model interpretation. You’ll learn how modern A.I. tools, including large language models (LLMs), can help you ask better questions and solve data-driven problems. Foundational coding skills are provided through dedicated, self-paced sessions on Python, NumPy, and Pandas materials.
Participants who successfully complete this program will earn a certificate and a skill-specific digital badge recognizing their achievement and expertise that they can add to their LinkedIn profiles.
Learning Objectives:
After completing the program, you will be able to:
- Explain key machine learning concepts, including supervised and unsupervised learning, and identify appropriate use cases for each.
- Interpret and apply provided Python-based workflows for data preparation, analysis, and visualization.
- Evaluate machine learning models by understanding training/testing splits, bias–variance tradeoffs, and model performance.
- Describe foundational deep learning and high-performance computing concepts and their role in modern A.I. applications.
- Use large language models and basic prompt engineering techniques to support data analysis and problem-solving tasks.
Who Should Attend:
- Early- to mid-career professionals in technical or analytical roles (e.g., data analysts, engineers, IT professionals) who want to understand how machine learning works and how to apply it in practice.
- Professionals adjacent to data science—such as product managers, program managers, operations, or domain experts—who work with A.I./ML teams and need to interpret models, results, and tradeoffs.
- Career switchers exploring data science or machine learning who want a structured, practical introduction before committing to deeper technical training.
- Graduate students or advanced undergraduates in STEM or quantitative fields seeking applied exposure to machine learning concepts and tools.
- Upskilling professionals in industry sectors where A.I. adoption is growing (e.g., energy, infrastructure, manufacturing, healthcare, finance).
Dr. Yiyang (Ian) Wang joined MSOE in 2023 and currently serves as an assistant professor in the Computer Science and Software Engineering Department. He received his Ph.D. in computer science from DePaul University in 2023. Ian's research interests encompass data science and machine learning, with a primary focus on their applications in the medical domain.