Undergraduate course, NORTH-1207, 2026
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Graduate course, Onlne only, 2024
Deep Learning is a subfield of machine learning mostly concerned with concepts and techniques built on top of the artificial neural network which in turn was inspired by the structure and functionality of human brains. This branch of machine learning is increasingly gaining popularity as deep learning systems are taking over all artificial intelligent tasks, ranging from image classification, language modeling, machine translation, playing games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and is behind many recent advances in Artificial Intelligence (AI). In this course you will gain both theoretical and practical knowledge of deep learning concepts and techniques. So, welcome aboard!
Graduate course, SCIENCE-2001 (Tue only), 2023
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Undergraduate course, SCIENCE-2001 (Tue only), 2023
Deep Learning is a subfield of machine learning mostly concerned with concepts and techniques built on top of the artificial neural network which in turn was inspired by the structure and functionality of human brains. This branch of machine learning is increasingly gaining popularity as deep learning systems are taking over all artificial intelligent tasks, ranging from image classification, language modeling, machine translation, playing games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and is behind many recent advances in Artificial Intelligence (AI). In this course you will gain both theoretical and practical knowledge of deep learning concepts and techniques. So, welcome aboard!
Graduate course, SCIENCE-1067 (Tue only) + Online async, 2023
We now live in an era of Artificial Intelligence (AI) where we rely on responses as well as actions by numerous autonomous systems that are crisscrossed in our daily lives. These systems are powered by AI that learn to provide us with reasonable answers for us with respect to our respective perspectives. Reinforcement learning is one of the most advanced and powerful way of developing such systems and are very much in line with the learning paradigms used to make us knowledgeable since our childhood, which is to learn from our mistakes. In this course, students are going to get a solid foundation in the field of reinforcement learning, learn the core challenges, and ideas to bring in newer approaches to make the systems robust, and more humanoid, and better to some degree. Through a combination of lectures, programming assignments students are expected to receive a hands-on-experience in exploring this field effectively. In addition, through the final project in this course, students will advance their understanding of reinforcement learning paradigm and are going to be able to design, develop and demonstrate by the end of the semester smart competitive players in video games, autonomous chatbots, autonomous vehicle control systems, early detection of malicious activities in the communication networks in the field of cybersecurity, and so on.
Graduate course, NORTH-3205 (Tue only) + Online async, 2023
Deep Learning is a subfield of machine learning mostly concerned with concepts and techniques built on top of the artificial neural network which in turn was inspired by the structure and functionality of human brains. This branch of machine learning is increasingly gaining popularity as deep learning systems are taking over all artificial intelligent tasks, ranging from image classification, language modeling, machine translation, playing games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and is behind many recent advances in Artificial Intelligence (AI). In this course you will gain both theoretical and practical knowledge of deep learning concepts and techniques. So, welcome aboard!
Graduate course, SCB-2500A (Tue only) + Online, 2022
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Undergraduate course, LSC-836 (Tue) + online, 2022
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Graduate course, Online, 2022
Deep Learning is a subfield of machine learning mostly concerned with concepts and techniques built on top of the artificial neural network which in turn was inspired by the structure and functionality of human brains. This branch of machine learning is increasingly gaining popularity as deep learning systems are taking over all artificial intelligent tasks, ranging from image classification, language modeling, machine translation, playing games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and is behind many recent advances in Artificial Intelligence (AI). In this course you will gain both theoretical and practical knowledge of deep learning concepts and techniques. So, welcome aboard!
Undergraduate course, KING-312, 2022
Design and analysis of algorithms. Asymptotic analysis as a means of evaluating algorithm efficiency. The application of induction and other mathematical techniques for proving the correctness of an algorithm. Data structures for simplifying algorithm design, such as hash tables, heaps and search trees. Elementary graph algorithms. Assignments include written work and programming assignments.
Undergraduate course, NORTH-1005, 2021
Programming topics in a modern programming language. Student will be introduced to an object oriented programming language. The emphasis is on problem solving using object oriented and generic programming. Topics includes classes, inheritance, polymorphism, virtual functions, abstract classes, exception handling, templates, and the Standard Template Library.
Cross-listed course (ugrad+grad), NORTH-1005, 2021
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Cross-listed (Grad+UGrad) course, Remote, 2021
Deep Learning is a subfield of machine learning mostly concerned with concepts and techniques built on top of the artificial neural network which in turn was inspired by the structure and functionality of human brains. This branch of machine learning is increasingly gaining popularity as deep learning systems are taking over all artificial intelligent tasks, ranging from image classification, language modeling, machine translation, playing games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and is behind many recent advances in Artificial Intelligence (AI). In this course you will gain both theoretical and practical knowledge of deep learning concepts and techniques. So, welcome aboard!
Cross-listed (UGrad+Grad) course, Remote, 2020
We now live in an era of Artificial Intelligence (AI) where we rely on responses as well as actions by numerous autonomous systems that are crisscrossed in our daily lives. These systems are powered by AI that learn to provide us with reasonable answers for us with respect to our respective perspectives. Reinforcement learning is one of the most advanced and powerful way of developing such systems and are very much in line with the learning paradigms used to make us knowledgeable since our childhood, which is to learn from our mistakes. In this course, students are going to get a solid foundation in the field of reinforcement learning, learn the core challenges, and ideas to bring in newer approaches to make the systems robust, and more humanoid, and better to some degree. Through a combination of lectures, programming assignments students are expected to receive a hands-on-experience in exploring this field effectively. In addition, through the final project in this course, students will advance their understanding of reinforcement learning paradigm and are going to be able to design, develop and demonstrate by the end of the semester smart competitive players in video games, autonomous chatbots, autonomous vehicle control systems, early detection of malicious activities in the communication networks in the field of cybersecurity, and so on.
Cross-listed (UGrad+Grad) course, Remote, 2020
Biological sciences are undergoing a revolution in how they are practiced. In the last decade, a vast amount of data (Electronic Health Records (EHR), DNA sequences, protein sequences, etc.) has become available, and computational methods are playing a fundamental role in transforming this data into scientific understanding. Bioinformatics involves developing and applying computational methods for managing and analyzing information about the clinical, sequence, structure and function of biological molecules and systems. Topics will include understanding the evolutionary organization of genes (genomics), the structure and function of gene products (proteomics), the dynamics for gene expression in biological processes (transcriptomics), and other omics data including tumor tissue imaging, MRIs, EEG, ECG, and numerous human diseases and disorders. Students will also learn about the technology behind the Next Generation Sequencing (NGS), also known as the High Throughput Sequencing (HTS), Genome Wide Association Studies (GWAS) and get skills to analyze associated datasets to decipher useful information.
Cross-listed course (ugrad+grad), Student Commons -1500+ Remote, 2020
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Cross-listed (Grad+UGrad) course, NORTH 1003, 2019
Deep Learning is a subfield of machine learning mostly concerned with concepts and techniques built on top of the artificial neural network which in turn was inspired by the structure and functionality of human brains. This branch of machine learning is increasingly gaining popularity as deep learning systems are taking over all artificial intelligent tasks, ranging from image classification, language modeling, machine translation, playing games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and is behind many recent advances in Artificial Intelligence (AI). In this course you will gain both theoretical and practical knowledge of deep learning concepts and techniques. So, welcome aboard!
Cross-listed course (ugrad+grad), Student Commons -2504, 2019
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. Over the very recent years, the field has expanded so much in every direction of our daily lives that we mostly are unaware of its existence. But, as a concerned citizen of the world, we are going to know the nuts and bolts of machine learning.
Cross-listed (Grad+UGrad) course, CU BLDG 470, 2018
Welcome to Deep learning course. What is Deep learning? It is actually a subfeld of machine learning mostly concerned with concepts and techniques built on top of the artifcial neural networi which in turn was inspired by the structure and functionality of human brain. This branch of machine learning is increasingly gaining popularity as deep learning systems are taiing over all artifcial intelligent tasis, ranging from image classifcation, language modeling, machine translation,cplaying games, autonomous vehicle driving, speech recognition, cancer detection and numerous other applications and dominating over most competing systems. In this course you will gain both theoretical and practical inowledge of deep learning concepts and techniques. So, welcome aboard!
Cross-listed course (ugrad+grad), Lawrence Street Center - 840, 2018
Welcome to Machine learning course. What is machine learning? It is concerned with the question of how to write computer programs that automatically improve with experience. The field has expanded so much in every direction of our daily lives that we mostly are unaware of its presence. Interestingly, there may be two perspectives to this oblivion. First one is that the machine learning applications have greatly improved themselves over time and became part of your lifestyle. However, a completely opposite perspective is that we became part of it, and unknowingly feeding input to the program as if we are in a computer simulation? In this class, you will learn about machine learning, its application in diverse domains, get to implement them yourself and raise awareness of its presence and associated implications in our day-to-day lives. Once again welcome aboard.
Undergraduate course, PLAZA-112, 2017
Programming topics in the C++ language. The emphasis is on problem solving using object oriented and Generic Programming. Topics include advanced I/O, classes, inheritance, polymorphism and virtual functions, abstract base classes, exception handling, templates, and the Standard Template Library.