Artificial Intelligence and Machine Learning Certificate Programs

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

Description

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.

Outcomes

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.

Modules

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

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

Description

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.

Outcomes 

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.

Modules

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

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

Description

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.

Outcomes

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.

Modules

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