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Artificial Intelligence (AI) is proven to be a key element in technological innovations in the ever-expanding digital age. As Computer utilization becomes more sophisticated, analyzing problems and programming solutions requires advanced AI algorithms to deal with Big Data such as machine learning, deep learning, data mining, and pattern recognition.
The degree program merges multiple disciplines with computer science, incorporating mathematics, statistics, and cognitive psychology to provide a comprehensive understanding of AI. This allows students to gain an integrated understanding of AI systems, their development, and their implications.
Why LTU?
Course Name
Course #
Credits
College Composition develops students’ acquisition of the fundamental principles of academic writing. This course focuses on the development of writing thesis statements and main arguments, topic sentences, transitional words and phrases, supporting paragraphs, use of evidence, essay organization, and research skills. Extensive writing and research practice is required.
COM1103
3
An overview of computer science for CS and non-CS majors with the overarching objective to develop a computational mindset. For CS majors, to gain an appreciation of the relevance of the various computing topics and interrelationships for future courses. For non-CS majors, to provide the necessary technological background to appreciate and integrate into today’s technical society.
MCS1243
3
Topics include, limits and continuity, differentiation of algebraic and transcendental functions, mean value theorem, applications of differentiation, anti-derivatives, indefinite integrals, inverse trigonometric functions, substitutions, definite integrals, the Fundamental Theorem of Calculus, applications of integration. Applications will be emphasized. In addition to regular class meetings, all students are required to participate in calculus lab sessions. The schedule, frequency, and modality of these labs may vary by section. Refer to the class schedule and course syllabus for details.
MCS1414
4
A historical survey that develops students’ abilities to critically engage texts of the ancient global world, placing an emphasis on the way these texts reflect their context and human experience. Readings may draw from philosophy, history, literature, visual art, and more. Class activities include reading of primary sources, seminar discussion, and writing in various genres. May be taken concurrently with COM 1103.
HUM1213
3
Total Credits:
13
Course Name
Course #
Credits
A historical survey that develops students’ abilities to engage texts of the modern global world, placing an emphasis on the way these texts reflect their context and human experience. Readings may draw from philosophy, history, literature, visual art, photography, film, digital media, and more. Class activities include reading of primary sources, seminar discussion, and writing in various genres. May be taken concurrently with COM 1103.
HUM1223
3
Hyperbolic functions, L’Hospital’s rule, techniques of integration, application to arc length and surface area, polar coordinates, infinite series, Taylor Series. In addition to regular class meetings, all students are required to participate in calculus lab sessions. The schedule, frequency, and modality of these labs may vary by section. Refer to the class schedule and course syllabus for details.
MCS1424
4
Introduction to programming with C++. Binary, two’s complement, decimal, hex, and octal representations. Variable types. Simple, iterative, and conditional statements. Procedure and functions with parameters by value and reference with or without a returning value. Arrays and vectors, multidimensional arrays, bubble and selection sorts, linear and binary search. Pointer and dynamic memory allocation, character and C-strings, file input/output (sequential). Classes, friends, array of objects, and operators’ overloading. Inheritance, polymorphism, virtual function, and recursion.
MCS1514
4
LLT Elective
LLT2XX3
3
This one credit course will focus on programming languages such as Scratch, Python, Javascript, Ruby, R, PHP, C# or Matlab. Students will be expected to work in groups on coding projects that will focus on syntax and semantics with application to a specific language.
MCS1111
1
Total Credits:
15
Course Name
Course #
Credits
SSC Elective
SSC2XX3
3
Three-dimensional analytic geometry. Vectors, vector-valued functions, motions in space, functions of several variables, partial differentiation, multiple integration, integration of vector fields, Green’s Theorem and Divergence Theorem.
MCS2414
4
Records, advanced file input/output (random access), dynamic memory allocation. Static and dynamic implementation of stacks, linked lists (ordered and unordered), queue (regular and priority), circular queues. Selection and insertion sort, binary search. Lecture 3 hrs., Lab 1hr.
MCS2514
4
Number Theory, review of induction and recursion, advanced counting, equivalence, partial ordering, graphs, trees.
MCS2523
3
This one credit course will focus on programming languages such as Scratch, Python, Javascript, Ruby, R, PHP, C# or Matlab. Students will be expected to work in groups on coding projects that will focus on syntax and semantics with application to a specific language.
MCS1111
1
Total Credits:
15
Course Name
Course #
Credits
Training in a systematic method for producing effective technical communication, written reports, letters, and memos as well as oral presentations. Lecture 3 hours. 3 hours credit
COM2103
3
Analysis of algorithms, Big Oh notation, asymptotic behavior. Advanced sorting (heapsort, quicksort), external sorting. Binary, multiway, and AVL trees. Lecture 4 hrs.
MCS2534
4
This course is a brief overview of software engineering topics including software development models, requirements, software design & implementation, software debugging & testing, software maintenance, software quality & metrics, and software project management. Focused in depth learning goals include system modelling & analysis tools, model-based design, coding standards, IDE tools, version control systems, and the introduction of agile software development methodologies. In addition to theories, students will practice in the development of a long-running software project applying & utilizing software engineering techniques & tools covered in class.
MCS3643
3
An introduction to functional programming. Induction and recursion, symbolic computation, higher-order functions, polymorphism, data abstraction and modularity, invariants, demand-driven programming, exception handling, and computability. Lecture 3 hrs.
MCS3633
3
Systems of linear equations, matrices, determinants, eigenvalues, eigenvectors, Finite-dimensional vector spaces, linear transformations and their matrices, Gram-Schmidt orthogonalization, inner product spaces. Lecture 3 hrs.
MCS3863
3
Each Spring, the faculty in Mathematics and Computer Science will provide students with an overview of the research they are working on. This will provide students with the opportunity gain critical exposure to research ideas early on in their academic careers. Each week a different faculty member will host the meeting to allow students to ask questions and to learn what is current in the field of math and computer science. Meetings will be hosted virtually, via Zoom.
MCS2111
1
Total Credits:
17
Course Name
Course #
Credits
Organization of database systems. Data definition, retrieval, manipulation. Relational databases, SQL. Practice using standard databases.
MCS2543
3
Basic Structure of computer hardware and assembly programming. Internal representation, processing unit arithmetic, memory addressing modes, stack processing, CISC, RISC. Lecture 3 hrs.
MCS3663
3
Math Elective
MCSXXX3
3
General Elective
XXX3
3
Calculus based kinematics and dynamics of particles, conservation of energy, momentum, rotational dynamics and statics, fluids, temperature and heat, and laws of thermodynamics. 3 Credit hours. Lecture 3 hrs., Studio 1 hr. The following course can be taken concurrently with this course: MCS1424.
PHY2413
3
Introductory laboratory experiments to complement University Physics 1. 1 Credit Hours. Lab 2 hrs.
PHY2421
1
Total Credits:
16
Course Name
Course #
Credits
This course focuses on the core concepts that underlie contemporary operating systems. It introduces the structure and responsibilities of operating systems, discusses the cutting-edge advances in computing that are redefining operating systems, and addresses design considerations, such as performance, fault tolerance, security, modularity, and cost.
Topics include Operating System Architecture, Process Concepts and Management, Thread Concepts, Asynchronous Concurrent Execution, Concurrent Programming, Deadlock and Indefinite Postponement, Processor Scheduling Algorithms, Real Memory Organization and Management, Virtual Memory Organization and Management, Disk Performance Optimization, RAID, File Systems, and Case Studies.
MCS4663
3
MCS Topics
Neural Networks, Deep Learning w/ Python
MCS4993
3
Natural Sciences Elective
BIO/PHY/CHM/GLG/PSC
XXX3
3
This course introduces the fundamental concepts & methods of knowledge representation, perception, reasoning, problem solving, data-mining, and machine learning in Artificial Intelligence (AI). Topics covered include Knowledge-Based Systems, Rule-Based Expert Systems, Uncertainty Management, Fuzzy Systems, Artificial Neural Networks, Evolutionary Computation, Semantic Web, and Autonomous Robotics.
MCS4633
3
The Data Science course delivers the fundamentals of data sets analysis arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. The content of this course introduces theories and practices of data science concepts based on mathematical and statistical concepts. This course offers a multitude of topics relevant to the analysis of complex data sets accompanying programming and code algorithms in R that underpinning data science. This course is ideal for students and practitioners without a strong background in data science. The students will also learn analyses of foundational theoretical subjects, including the history of data science, matrix algebra, and random vectors, and multivariate analysis; a comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity; introductions to the R programming languages, including basic data types and sample manipulations; an exploration of algorithms, including how to write one and how to perform an asymptotic analysis; and, a comprehensive discussion of several techniques for analyzing and predicting complex data sets. Towards the end of the class, students will develop a case study by gathering data to apply and practice the learned concepts in a large-scale project.
MCS2403
3
Total Credits:
15
Course Name
Course #
Credits
Transmission media, local asynchronous communication (RS232) long distance communication, LAN Technologies, network topologies, hardware addressing, LAN wiring, physical topologies, interface hardware, extending LANs, fiber modems repeaters, bridges, and switches, WAN topologies and routing. Lecture 3 hrs.
MCS4613
3
Course not found.
MCS4833
3
Jr./Sr. Elective
SSC/PSY
3/4XX3
3
MCS Elective
MCSXXX3
3
A dive deep into the evolving world of textual data analysis. This course is meticulously crafted to provide students with a comprehensive understanding of how machine learning algorithms work for text. We will also get an introduction to large language models and gain practical experience. Beyond technical skills, students will also engage in thoughtful discussions about the ethical implications and potential biases of text-based machine learning. In addition, this course has been designated as a CRE-based course which includes a significant research component. We will review and discuss papers on a specific topic and problem, which will cultivate in the development of a research project and paper.
MCS4223
3
Pathways 4001 is the capstone course for CoAS majors’ Pathways Program. The course meets for 4 half-day Saturday sessions fall term. The course’s work requirements are satisfied throughout students’ final year under the supervision of the Pathways Program Director. Requirements include: a) mentoring first-year CoAS majors in the Pathways 1001 course, b) participation in an extra- or co- curricular activity related to major research field, c) incorporation of leadership / ethics issues in senior thesis / capstone project.
COM4001
1
Total Credits:
16
Course Name
Course #
Credits
LLT Jr./Sr. Elective
3/4XX3
3
This course will cover survey of the four various programming languages in the imperative, multiprogramming, functional and logical domains. An understanding of the fundamental design and language concepts provides the foundation for the critical examination and implementation of programming language paradigms from lexical and syntactical perspective.
MCS4643
3
Beginning course on theory of computation. Regular languages, finite automata, context-free language, Turing Machine, Chomsky hierarchy, applications to parsing. Lecture 3 hrs.
MCS4653
3
Course not found.
MCS4843
3
The objective of the course is to study, understand, and practice the concepts of machine learning and pattern recognition. The course will cover the basic aspects of pattern recognition and machine learning such as different approaches to feature selection, classification methods, interpolation methods, and techniques of machine learning performance evaluation. In the end of the course the students will be able to implement all aspects of pattern recognition to create a working machine learning system that will solve a real-life pattern recognition problem.
MCS5623
3
Total Credits:
15
Use Your Cell Phone as a Document Camera in Zoom
From Computer
Log in and start your Zoom session with participants
From Phone
To use your cell phone as a makeshift document camera
