Artificial Intelligence and Machine Learning Certificate Programs

The Artificial Intelligence & Machine Learning Certificate Program at the University of Miami offers 3 individual Certificate of Completion in progressive format: Fundamentals, Elite and Grand Master, and it is intended for individuals with an active interest in seeking jobs in the high-demand Artificial Intelligence-related fields. During each level of the program, students will explore topics, technology, and skills required in the successful application of AI/ML techniques to support key industry needs and demands

Quick Facts About the Programs

Artificial Intelligence (AI) and Machine Learning (ML) Fundamentals


Our Artificial Intelligence (AI) and Machine Learning (ML) Fundamentals level has no prerequisites and aims to provide learners with a comprehensive coverage of core concepts and technologies for AI/ML while steering perspective talents to potential technique areas. In this introductory level, we use an application-driven organization that covers a much broader range of technologies in key application areas. We also cover mathematical skills and programming tools when needed. This approach allows us to cover exciting technologies earlier in the course while providing rigorous foundations and skills needed for innovative research and development.


Upon successful completion of the AI/ML Fundamentals level, learners should be able to demonstrate proficiency in:

  • Representing and visualizing data in an effective manner.
  • Using features to represent data.
  • Preprocessing data before it can be used in AI related tasks. 
  • Computing the performance metrics of classifiers and comparing them.
  • Computing the histogram of an image.
  • Transforming an image by converting it to gray scale, reassigning colors, matching a histogram, changing contrast, filtering by different methods, etc.
  • Understanding how language is represented and processed in the realm of AI.
  • Loading, editing, and saving an image programmatically.
  • Understanding the basic principles of artificial neural networks (architecture, training).
  • Applying the most common techniques to extract features from a dataset or image. 
  • Understanding what classification in AI means and how it is achieved.


  • Concepts
  • Tabular Data Analytics and decision support
  • Computer Vision
  • Understanding Natural Language



Artificial Intelligence (AI) and Machine Learning (ML) Elite


Our Artificial Intelligence (AI) and Machine Learning (ML) Elite level builds on the foundations of our AI/ML Fundamentals level. It enhances AI/ML learners skill set on how to establish a comprehensive knowledge structure suitable for web service development, intelligent consumer electronics design and prototyping , related product development and validation, and broader engineering tasks in related AI/ML fields. Through this level of the AI/ML program, we aim to provide an equivalent coverage of two key high-utilization components: a comprehensive coding tool/technique package and a comprehensive mathematical modeling package with theoretical AI/ML framework derivation capacity with a computational simulation/evaluation module. This progressive level of our AI/ML programmatic offerings covers sufficient core material for performing MS/ME/Ph.D level AI.ML job roles while keeping the remaining material and future research-level conferences and journals within easy grasp when needed. The enjoyment of AI/ML science and technical wonders will activate a lifetime of learning and achievement for learners.


Upon successful completion of the AI/ML Elite level, learners should be able to demonstrate proficiency in:

  • Solving prediction problems by applying linear regression.
  • Computing approximation and classification errors in prediction models.
  • Selecting the most adequate activation functions in AI models.
  • Understanding how supervised and unsupervised training works.
  • Applying methods to prevent AI models from memorization.
  • Using Python language to process data and design, train and test AI models.
  • Understanding the mathematical foundations of artificial neural networks.
  • Representing and interpreting probabilistic events.
  • Using mathematical methods such as PCA for dimensionality reduction. 
  • Applying statistical tests to accept/reject hypothesis about data.


  • Coding Intensive AI/ML System Implementation
  • Coding for AI/ML
  • Math for Data Science



Artificial Intelligence (AI) and Machine Learning (ML) Grand Master


Our Grand Master AI/ML level builds upon our Fundamentals and Elite levels and aims to provide learners with research-level background AI/ML materials in a fast-paced intensive format. The intent of this advanced Certificate of Completion is to establish a high-precision AI/ML knowledge base beyond the utilization or adaptation of existing toolboxes and reference projects. In this level learners will explore the concepts and methodologies under the "surface" application layer. This highest-level of AI/ML focuses on tailoring technology precisely toward commercial developments and academic research while reducing the dependency on pre-existing or general-purpose development. It aims at complete freedom of technical adaptation, which leads to full utilization of the potential of this new and exciting technology. Our AI/ML areas and its application fields, facilitating cutting-edge technology growth and fast-tracked career development.


Upon successful completion of the AI/ML Grand Master level, learners should be able to demonstrate  proficiency in:

  • Applying the gradient descent algorithm to loss minimization problems.
  • Understanding how basic classification algorithms work. 
  • Applying regularization methods for AI models.
  • Handling data imbalance.
  • Understanding what autoencoders and compression mechanisms are.
  • Applying Bayes' Theorem in predictions problems.
  • Modeling classification problems by applying prediction trees.
  • Running statistical tests to validate hypothesis about data.


  • Deep Learning Mechanisms
  • Machine Learning Mechanisms and Algorithms
  • Massive Scale AI/ML
  • Research, Reasoning and Optimal Decisions


The 3-level progressive Artificial Intelligence and Machine Learning Certificate of Completion program is 24 weeks long in total, or 8 weeks per level. However, each level can be taken independently and leads to a Certificate of Completion by level. The program is offered in a Live Online format. The Fundamentals Level takes place on Saturdays, while the Elite and Master Levels take place in the evenings during the week. Learn more and enroll in the next program start on our enrollment page.

The program cost is $2,800 per level.

Refund policy & Students Rights

The office of Professional Advancement (OPA) is excited to announce that in a partnership with the TOPPEL Career Center at the University of Miami are now offering to our students and alumni a comprehensive suite of career services available via our career services platform Handshake!

What is Handshake?

Handshake is a career services platform created for students and alumni to use in their career development. It's used by over 200,000 employees, including all Fortune 500 companies! Thousands of internships and job opportunities are posted on Handshake by employers specifically looking to hire students.

All students have a Handshake account that is automatically created for them once they begin their program of study at the U. Once you receive an email notification, all you have to do is log into Handshake to activate your account. Handshake will then recommend certain positions to you based on your profile allowing for easy searching. Comparing and updating your profile will provide Handshake with a better idea of which job interviews/internships  listing s you may be interested in.

Here are some of the awesome things you can do with Handshake:

  • Apply for jobs & internships
  • Register for career fairs, workshops, & info sessions
  • Upload your resume for an online critique from the Toppel Career Center
  • Research thousands of employers
  • Network with recruiters and other students for career insights

The office of Professional Advancement (OPA) is excited to announce that our students now have access to the Otto G. Richter Library services throughout the duration of their respective Certificate Programs. 

Students can use the online resources at

For accessing certain resources, students may need to go through UM IT authentication and enter their CaneID and passwords. Students can retrieve their CaneID and password at

Students are also able to check out books in person. To do so, they may stop by the Access Services desk to pick up a library card on their first visit to the Richter Library Building, located at Otto G. Richter Library Building, 1300 Memorial Drive, Coral Gables, Florida 33146

Melvin Ayala

Melvin Ayala, PhD, Postdoctoral Associate

Melvin Ayala received his BA and PhD in Economic Engineering from the University of Applied Sciences Zittau/Gorlitz in Germany and his PhD in Electrical and Computer Engineering from Florida International University (FIU). He has held teaching positions at the Technological University of Havana, Cuba and Universidad de Sao Paulo, Brazil, where he has taught courses on computer science (CS) and artificial intelligence (AI)

Prior to joining IDSC, Ayala has also held positions as a researcher at FIU's CATElab and as a software developer at Beckman Coulter. He has coauthored several scientific publications and three patents, mostly in the area of AI with biomedical applications. His research interests include data mining, natural language processing, image processing, and AI for pattern recognition and prediction.

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