Computer Science & Software courses

Elevating Aerospace: Design Thinking for Safety Critical AI is a hands-on, applied course for aerospace professionals seeking practical, responsible, and deployment-oriented AI capabilities in regulated and mission-critical environments. Rather than focusing…

This course moves students from AI awareness and problem framing into structured execution. Building on the problem statements and AI foundations developed in Course 1, students learn how to translate aerospace challenges into practical AI-enabled workflows…

MIT xPRO's Professional Certificate in Coding: Full Stack Development with MERN equips learners with cutting-edge skills in Computer Science & Software. This comprehensive program covers the MERN stack (MongoDB, Express.js, React, Node.js), enabling…

This course develops the practical execution capability needed to design and secure AI-enabled systems in aerospace and other regulated environments. Students become “dangerous with tools” in a controlled and responsible way: capable of experimenting with…

MIT xPRO's Introduction to Quantum Computing course delves into the transformative field of Computer Science & Software, offering a rigorous academic exploration of quantum versus classical computation. Participants will examine the historical context,…

Discover the business and technical implications of the new frontier in computing and how you can apply them to your organization with this two-course program from MIT. Introduction to Quantum Computing Quantum Algorithms for Cybersecurity, Chemistry, and…

MIT xPRO presents Requirements for Large-Scale Universal Quantum Computation, an advanced Computer Science & Software course delving into quantum error correction and fault-tolerant computation thresholds. Students will examine models extending beyond…

This capstone course brings together the full learning journey: problem identification, AI foundations, workflow design, secure architecture, governance, and deployment planning. Students apply what they have learned to design a practical AI solution for a…

This course covers AI fundamentals and concepts as pertaining to finance. The course will review python programming basics such as Basic Input-Output Operations, Basic Operators, Conditional Execution, Loops, and Lists. The focus will be on how to utilize…

The main objective of this course is to introduce the fundamentals of remote sensing and related applications in the era of cloud computing. Our goal is to transition from GUI and/or code based remote sensing software that runs on PCs, MACs and/or local…

This course reinforces and introduces additional key geographic concepts and techniques related to the theory and application of geographic information systems (GIS). Topics such as geographic coordinate systems, automation, geoprocessing, raster data…

This course introduces the methods, techniques, and considerations behind geographic data visualization and GIS mapping. The first and most significant portion of the course covers best practices for cartographic design, including topics and techniques…

This course is a project-based exploration of advanced topics in GIS and geospatial technology, with a focus upon spatial data analysis and visualization techniques. Students complete a series of hands-on weekly projects, each of which focuses upon the use of…

This course introduces concepts and techniques associated with the design, development, and management of geospatial databases, including databases used in shared and scalable enterprise GIS platforms. In addition to learning about relational database theory…

Object-oriented software development. Abstract data type definition and use. Overloading, inheritance, polymorphism. Object-oriented view of data structures: stacks, queues, lists. Algorithm analysis. Trees, graphs, and associated algorithms. Searching and…

Introduction to computer science via theory, applications, and programming. Basic data types, operators and control structures. Input/output. Procedural and data abstraction. Introduction to object-oriented software development. Functions, recursion. Arrays,…

This hands‑on, exercise‑driven course introduces students to the foundational concepts, tools, and analytical techniques that underpin modern data‑driven decision‑making. Learners will explore the role of data science in organizational strategy while…

The internship course offers eligible students the opportunity to earn credit toward their certificate program through a supervised internship of at least 120 hours, allowing for the practical application of knowledge and skills gained in their coursework.…

Introduction to linear algebra: Systems of linear equations Matrix algebra Linear independence Subspaces, bases and dimension Orthogonality Least-squares methods Determinants Eigenvalues and eigenvectors Matrix diagonalization Symmetric matrices

This course offers a modern take on the critical discipline of systems analysis, specifically designed for professionals navigating today's complex technological landscape. We will explore traditional systems analysis methodologies and how they are evolving…

Data Structures and Algorithms provides students with a solid foundation in the essential concepts that support effective software development. Students will build a strong understanding of core data structures and algorithmic principles, including complexity…

This course introduces data engineering. Learn about problems, opportunities and challenges that data engineering and technologies solve, including data collection, storage, processing, and analysis. Explore the technologies and tools used in data…

This 10-week hands-on course takes you from generative AI fundamentals to production-grade applications. You will build real systems using the same tools and frameworks used in industry — PyTorch, Hugging Face, LangChain, and modern LLM APIs — and leave with…

Deep Learning is designed to provide students with a solid understanding of deep learning principles, techniques, and applications. The course is structured to cover both theoretical concepts and hands-on implementation, ensuring students are equipped with…

This course introduces machine learning using R. Students will learn structured and unstructured data processing, linear regression modeling and non-linear modeling methods used in machine learning algorithm development, optimization techniques, neural…