Basics of Artificial Intelligence Certificate Program
Our Basics of Artificial Intelligence Certificate program offers a comprehensive learning journey that equips candidates with the knowledge and skills to navigate the intersection of artificial intelligence and cybersecurity. By enrolling in this program, participants can expect to gain: Masterful Understanding of AI Principles: Delve into the core principles of machine in order to gain a solid foundation in mathematical models, algorithms, and statistical tools essential for machine learning tasks. Through practical programming examples, grasp the concepts of moduleification, regression, neural networks, and more. Develop a comprehensive understanding of model selection, optimization, and regularization techniques, enabling you to implement AI solutions effectively.
Expertise in Deep Learning & Natural Language Processing: Gain in depth knowledge on advanced natural language processing and deep learning techniques. Acquire skills in analyzing and processing text using statistical method sand deep neural networks. Explore the application areas, including sentiment analysis, machine translation, and question answering. Dive deep into topics like optimization, neural network architectures, and transfer learning, enhancing your ability to handle complex language-related AI tasks. Proficiency in Computational Design & Data Analytics: Understand the fundamentals of computational design and its integration with AI. Develop end-to-end AI-driven design and manufacturing workflows. Learn how AI methods are shaping digital manufacturing and design ecosystems. Acquire skills in 3D modeling, simulation, procedural design, and data-driven design evaluation. This expertise will enable you to revolutionize design processes using AI-driven insights.
Ethical AI Implementation and Practical Applications: Engage in discussion on the ethical dimensions of AI in the context of big data. Explore the potential social, ethical, legal, and policy issues arising from the use of AI in industry, academia, and research. Understand the role of AI in countering biases and mitigating misuse of data. Grasp the responsibilities and considerations in developing AI systems that align with ethical standards, ensuring you can implement AI solutions that uphold societal values.Enrolling in the Basics of Artificial Intelligence Certificate program equips candidates with a comprehensive skill set in AI principles, deep learning, computational design, and ethical AI implementation. With this unique combination of expertise, participants will be prepared to navigate the intricate landscape of AI while ensuring ethical and secure implementation.
MODULE 1: PRINCIPLES OF MACHINE LEARNING
This module introduces the fundamental mathematical models, algorithms, and statistical tools needed to perform core tasks in machine learning. Applications of these ideas are illustrated using programming examples on various data sets. The module is a systematic introduction to machine learning, covering theoretical as well as practical aspects of the use of statistical methods. Topics will include pattern recognition, PAC learning, overfitting, decision trees, linear regression, logistic regression, gradient descent, feature projection, dimensionality reduction, maximum likelihood, Bayesian methods, neural networks, support vector machines, regularization, and model selection.
MODULE 2: DEEP LEARNING & NATURAL LANGUAGE PROCESSING
This module focuses on modern natural language processing using statistical methods and deep learning. Problems addressed include syntactic and semantic analysis of text as well as applications such as sentiment analysis, question answering, and machine translation. Topics will include optimization, computer vision, computer graphics, unsupervised feature learning, and deep language models. Machine learning topics covered include sequence tagging, feedforward, recurrent, and self-attentive neural networks, and pre-training / transfer learning.
MODULE 3: COMPUTATIONAL DESIGN & DATA ANALYTICS
This module will cover the fundamentals of computational design. It will be an introduction to developing end-to-end AI-based design and manufacturing workflows. It will explore how AI methods are advancing digital manufacturing and the entire design ecosystem. Topics will include 3D modeling, 3D representation, procedural modeling, simulation, and computational interaction. Students will also learn about evaluating designs by user studies and hypothesis testing.
MODULE 4: ETHICS OF AI & PRACTICAL APPLICATIONS
This module introduces the ethics related to Big Data in industry, business, academia, and research settings.Students will learn the social, ethical, legal and policy issues that underpin the big data phenomenon. Machine learning algorithm programs are typically promoted as fair and free of human biases; but human error is possible. Topics will include various AI/ML techniques that can be used to counterbalance the potential abuse and misuse of learning from big data, but also the effects of these technologies on individuals, organizations, and society, paying close attention to what our responsibilities are as computing professionals.