Machine Learning Engineering Certification

Transform Data into Insight with Advanced Analytics & AI

Gain the technical and analytical skills to uncover patterns, build intelligent systems, and communicate complex information through impactful data storytelling. This graduate certification combines hands-on experience in data visualization, deep learning, and modern database systems, preparing students to work with large-scale data and emerging AI technologies across a wide range of industries. 

This graduate-level certification includes three dynamic courses:

• Data Exploration & Visualization (ADS 637): Explore the fundamentals of data visualization, including data preprocessing and the tools and techniques needed to turn complex data into clear, compelling visuals. Students learn design principles, perception, color theory, and how to create charts, maps, and network visualizations using tools like Tableau, Python, and R to successfully deliver real-world visualization projects. 
• Database Systems (ADS 638): Build a strong foundation in database systems and learn how to design, implement, and query data using SQL and modern data tools. Students also explore cutting-edge approaches for managing large-scale and unstructured data, including NoSQL, Hadoop, and data warehousing, preparing for real-world data science challenges. 
• Agentic AI & Skills: Intelligent Agent System Design (ADS 655): Gain practical experience designing intelligent agent systems powered by modern AI frameworks and tools. Students will build, test, and deploy agentic AI solutions that address real organizational challenges while exploring governance, risk management, and responsible AI practices.

Whether you're an aspiring data scientist, IT professional, software developer, or analyst looking to expand your expertise, this certification equips you with the advanced skills to work with complex data, build intelligent AI-driven systems, and transform insights into impactful solutions.

Explore the online academic catalog for detailed course descriptions, program requirements, and additional curriculum information.

Start with a Certification. Continue Toward Your Master's.

Complete this certification on its own or apply the 3 courses toward the 10-course requirement for your MBA +C or another +C graduate degree.

Admission Requirements

If you are a current BPU undergraduate student or BPU alumni, please contact Graduate Admissions to discuss your requirements.

For consideration, applicants must submit the following admission requirements:

1. A completed application - Apply Now 
2. Official undergraduate and graduate transcripts (a GPA of 3.0 or higher is preferred)
3. An original essay of at least 250 words on the topic: "Why a Machine Learning Engineering Certification is important to my personal and professional goals."
4. A current resume
5. Two recommendations - Download the recommendation form here

Official Transcripts 

Official transcripts must be sent directly to Bay Path's Graduate Admissions Office from the issuing institution's records office either by mail or through a secure electronic transcript service (such as Parchment or National Clearinghouse). For transcripts sent through a secure transcript service, please select Bay Path University from the vendor's dropdown list to ensure the transcript is routed to the correct place. If an email address is requested, you can route to graduate@baypath.edu. Transcripts sent by the student are unofficial and will not be accepted.

How to Submit Your Graduate Application Materials

All documentation, including recommendation forms and official transcripts, may be mailed or emailed directly to the Bay Path University Office of Graduate Admissions: