Adjunct Associate Faculty in Applied Machine Learning I (Fall '26)

The School of Professional Studies at Columbia University is actively seeking seasoned industry professionals to join our academic team as part-time Adjunct Associate Faculty for a graduate-level course in Cloud Computing. This position provides a unique opportunity to contribute to the instructional process while gaining valuable experience in graduate-level teaching at Columbia University.The Cloud Computing course is designed to expose analytics students to practical applications and concepts of cloud computing, including infrastructure, administration, and various services and applications. Emphasis will be placed on developing hands-on skills for utilizing cloud services to create distributed and scalable analytics applications.Key ResponsibilitiesParticipate in all class sessions, support instructional delivery, lead breakout sessions, and facilitate engaging discussions.Assess and grade student submissions and evaluations as mandated by the course Lecturer.Address and manage student inquiries and concerns proactively.

The School of Professional Studies at Columbia University is actively seeking seasoned industry experts to join our faculty as part-time Lecturers for our graduate-level course in Cloud Computing. As primary instructors, Lecturers play a crucial role in shaping the academic environment and fostering a vibrant faculty community.This course serves to immerse analytics students in the essential concepts and practical applications of cloud computing, with a focus on infrastructure management and the deployment of services and applications. The curriculum is designed to equip students with hands-on skills necessary for building distributed and scalable analytics applications using cloud technologies.Key ResponsibilitiesDeliver engaging lectures, facilitate instructional activities, and lead classroom discussions. Commitment to attending all scheduled class sessions.Proactively address student concerns and inquiries to ensure a supportive learning environment.Assess and grade student assignments and evaluations with fairness and transparency.Hold regular office hours for student consultations and guidance.

Columbia University is seeking skilled analytics professionals to join our faculty as a part-time Adjunct Associate for the graduate-level course Mathematics for AI. As an Adjunct Associate, you will provide essential subject matter expertise and support the instructional process for this course section, gaining valuable exposure to graduate-level teaching at Columbia University.Key Responsibilities:Participate in all class sessions, assist with teaching, and lead breakout sessions to enhance student engagement.Deliver class lectures and facilitate discussions, ensuring a rich learning environment.Assess and grade student assignments and assessments as requested by the course Lecturer.Monitor student inquiries and concerns, providing timely support and guidance.

Columbia University invites accomplished analytics professionals to join as part-time Adjunct Associate Faculty for the graduate-level course on Managing Data. This position offers a unique opportunity to gain firsthand experience in graduate-level teaching while providing critical subject matter expertise. As an Adjunct Associate Faculty member, you will support the instructional process and engage with students in a dynamic learning environment.The Managing Data course equips students with essential skills for effective data management, enabling them to leverage data confidently in collaboration with technology teams. The curriculum addresses the challenges posed by diverse data languages and techniques, offering a comprehensive overview of data technologies, database engines, foundational principles, governance processes, and organizational requirements to ensure data quality.Key ResponsibilitiesAttend all class sessions, assist in instructional activities, lead breakout sessions, and facilitate engaging discussions.Evaluate and grade student assignments and assessments as directed by the course Lecturer.Address student inquiries and concerns promptly and effectively.

Join our team at Columbia University as a part-time Adjunct Associate Faculty for an advanced course on AI User Interfaces for Analytics. This role offers analytics professionals an exceptional opportunity to contribute their expertise while gaining valuable experience in graduate-level education at one of the leading institutions in the world.Key ResponsibilitiesParticipate in all class sessions, assist with instructional delivery, lead breakout discussions, and engage students in meaningful dialogue.Conduct class lectures and oversee instructional activities, ensuring a conducive learning environment.Assess and grade student assignments and assessments as required.

Columbia University is seeking experienced analytics professionals to join our faculty as part-time Adjunct Associate Faculty for a graduate-level course titled Analytics for Cybersecurity Management. This role offers a unique opportunity to contribute your subject matter expertise and support the instructional process for aspiring cybersecurity leaders. Engaging in this capacity will provide valuable exposure to the academic environment at Columbia University.This course serves as a comprehensive introduction to foundational cybersecurity principles, including network security, threat detection, and vulnerability management. It emphasizes the transformative impact of emerging technologies such as AI and machine learning on modern defense strategies. Participants will engage with key frameworks and advanced tools through real-world case studies, gaining insights into the role of analytics in effective threat intelligence, incident response, and regulatory compliance.Students will enhance their practical skills through hands-on exercises and interactive assignments, culminating in a project focused on automating vulnerability analysis. They will learn critical tasks such as log parsing, vulnerability classification, dashboard visualization, and AI-driven anomaly detection, while also addressing ethical, legal, and regulatory issues in cybersecurity. By the conclusion of the course, participants will be equipped to design proactive defense measures and adeptly navigate diverse threat landscapes, leveraging AI and analytics to bolster digital security against evolving cyber threats.Key ResponsibilitiesAttend all class sessions, assist with instruction, lead breakout sessions, and facilitate engaging discussions.Evaluate and grade student assignments and assessments as directed by the course Lecturer.Monitor student progress and address any concerns or inquiries in a timely manner.

Columbia University is on the lookout for analytics professionals to join as part-time Adjunct Associate Faculty for an advanced course on Applied Generative AI in Fall 2026. This role offers an incredible opportunity to gain firsthand experience in graduate-level teaching while contributing to the academic community.The Applied Generative AI course introduces students to the fascinating field of generative modeling, a vital aspect of machine learning. Participants will explore theoretical foundations, practical applications, and gain hands-on experience using high-level APIs and open-source foundational models. The curriculum covers essential methodologies for employing, fine-tuning, and programmatically working with cutting-edge Generative AI tools. Students will also delve into the intricacies of low-level model implementations, empowering them to train and understand models based on their data, from foundational principles. Various generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers, will be examined, with applications spanning text, image, audio, and video generation.Key ResponsibilitiesParticipate in all class sessions, assist with instructional duties, lead breakout sessions, and facilitate engaging discussions.Assess and grade student assignments and evaluations as directed by the course Lecturer.Address student inquiries and concerns in a timely and supportive manner.

Columbia University is actively seeking qualified professionals to join our team as part-time Adjunct Associate Faculty for the graduate-level course titled Introduction to Blockchain, Cryptocurrencies & Analytics. This course is designed to impart essential knowledge about blockchain technology and cryptocurrencies to our Master of Science students in Applied Analytics. Topics covered will include cryptographic protocols, hashing, digital signatures, transaction chaining, decentralization through proof of work mining, and smart contracts.The role of an Adjunct Associate Faculty member is pivotal for providing expertise and facilitating the learning process within the course. This position offers an excellent opportunity to gain valuable experience in graduate-level education at Columbia University.

The School of Professional Studies at Columbia University is seeking passionate and qualified professionals to join our team as part-time Adjunct Lecturer for a graduate-level course titled Mathematics for Artificial Intelligence. This course empowers students with critical mathematical skills necessary for comprehending and utilizing artificial intelligence (AI) algorithms. By the conclusion of the course, students will be equipped with a robust mathematical toolkit to adeptly navigate the challenges posed by contemporary AI algorithms.Key Responsibilities:Facilitate engaging class lectures, instructional activities, and dynamic classroom discussions. Attendance at all class sessions is mandatory.Provide support to students by monitoring and addressing their concerns and inquiries.Assess and grade student assignments and evaluations.Hold regular office hours for student consultations.

Columbia University is seeking skilled analytics professionals to join us as part-time Adjunct Associate Faculty for a graduate-level course on Artificial Intelligence of Things (AIOT) starting in Fall 2026. This role provides an exceptional opportunity to engage in graduate-level teaching while contributing subject matter expertise and supporting the instructional process.The course aims to equip students with a thorough understanding of IoT technologies and their integration with AI and robotics. Participants will delve into IoT architecture, critical components, and communication protocols, and will gain hands-on experience with IoT platforms, sensors, and data acquisition devices. The curriculum emphasizes practical AIOT applications for real-time decision-making in various sectors, including manufacturing, public safety, smart cities, and healthcare, while also addressing ethical considerations associated with these technologies.Through a combination of conceptual learning and practical assignments, the course features weekly lectures, readings on IoT fundamentals, and biweekly quizzes to evaluate understanding. Students will apply their knowledge through individual assignments and a collaborative term project, ensuring a solid foundation in IoT analytics and AI-driven robotic automation.

The Applied Analytics program at Columbia University is excited to invite seasoned data analytics professionals to join our team as a part-time Associate Faculty  for the graduate-level course Applied Deep Learning and AI. This advanced course immerses students in deep learning concepts, integrating essential components from Statistical Machine Learning. Participants will establish a robust foundation in supervised learning alongside various algorithms and methodologies. Key topics include Support Vector Machines, Neural Networks, Convolutional Neural Networks (CNN), word embeddings, attention mechanisms, transformers, encoder-decoder architectures, Generative Adversarial Networks (GAN), and Reinforcement Learning. Practical applications will provide students with insights on preparing, training, testing, and validating models.An Associate Faculty member plays a pivotal role in delivering subject matter expertise and enhancing the instructional experience for course participants. This position offers an exceptional opportunity to gain invaluable exposure to graduate-level teaching within the prestigious environment of Columbia University.Responsibilities:Attend and engage in all on-campus class sessions, assist with instruction, lead breakout discussions, and facilitate student engagement.Evaluate and assess student work as directed by the course Lecturer.Address student inquiries and concerns proactively.Conduct regular office hours for student support.

Columbia University School of Professional Studies is on the lookout for distinguished industry professionals to join our team as adjunct Lecturers. This role involves developing and delivering a variety of impactful courses within the M.S. in Political Analytics program, which uniquely integrates the realms of politics and advanced quantitative methodologies to enhance data-driven decision-making and effective communication in political contexts.For a detailed overview of the program's curriculum, please visit here. Interested candidates are encouraged to indicate their specific areas of expertise in their cover letters, as well as the types of courses they are qualified to teach. Current courses include:Big Data & Political StrategyCampaign Finance & Fundraising AnalyticsData Science for Political AnalyticsElectoral Data & Predictive ModelingThis position may involve course development, leading syllabus approval processes, and direct teaching responsibilities.Key ResponsibilitiesConduct in-person lectures, instructional sessions, and facilitate classroom discussionsAssess student submissions and assign gradesAddress student inquiries and serve as the primary point of contact for questionsMaintain weekly office hours for student supportPrepare, manage, and enhance course materials via Canvas, Columbia University’s learning management systemNew part-time Lecturers at SPS must complete Canvas trainingParticipate in Political Analytics faculty meetingsFor those tasked with designing courses, additional responsibilities include:Establishing course objectives that align with program-wide learning outcomesCreating activity maps that connect course activities to objectives, ensuring relevance to the industryDrafting comprehensive syllabi for review and approval by the Program Curriculum Committee and the Committee on Instruction (COI)Collaborating with Instructional Design to create course materials through a consultative approach, which includes developing dynamic instructional media, maintaining established courses, and providing timely assistance for specific needsThis adjunct Lecturer position offers a unique opportunity to educate and mentor students in the dynamic field of political analytics while fostering valuable professional relationships.

The School of Professional Studies at Columbia University is inviting applications for the role of Adjunct Associate Faculty for a graduate-level course titled Analytics for Business Operations Management, starting in the Fall of 2026. This part-time position offers a unique opportunity to engage in graduate-level teaching while contributing to the academic community at one of the world's leading institutions.This course aims to equip students with analytical techniques to enhance operational decision-making, increase efficiency, and tackle real-world challenges in operations management. Enrolled students will gain hands-on experience in key topics including process analysis, forecasting, queuing theory, simulation, optimization, inventory analysis, project management, supply chain management, and lean operations. By combining lectures with practical coding exercises, the course fosters a comprehensive understanding applicable across various industries.Key Responsibilities:Participate in all class sessions, assist with instruction, and lead breakout discussions.Deliver lectures and facilitate engaging classroom discussions.Assess and grade student assignments as directed by the course Lecturer.Address student inquiries and concerns promptly.

Columbia University’s Master's in Applied Analytics program is actively seeking accomplished industry professionals to join as part-time Lecturers for the graduate-level course on Managing Data.The Fundamentals of Data Engineering course equips students with essential knowledge to confidently manage data. As analytic teams collaborate with technology partners, it's crucial to understand team-specific languages and techniques that may hinder cooperation. This course offers a comprehensive overview of data technology concepts, including database engines and related technologies, while introducing foundational data principles, governance processes, and organizational requirements necessary to ensure data quality and address related challenges.Key ResponsibilitiesConduct engaging lectures, instructional activities, and facilitate classroom discussions while attending all class sessions.Provide guidance and support to students by addressing their concerns and inquiries.Assess and grade student assignments and evaluations.Hold regular office hours for student consultations.

The School of Professional Studies at Columbia University is actively seeking experienced industry professionals to join our team as Adjunct Lecturers in the exciting field of Project Management for the upcoming Fall 2026 semester. As part of our commitment to providing top-notch education, you will have the opportunity to develop and teach in-person courses in our innovative M.S. in Project Management program, designed to equip students with essential strategic, analytical, and leadership skills necessary for successful project management across diverse industries.For a detailed overview of the program's curriculum, please click here. Interested candidates are encouraged to specify their areas of expertise in their cover letters, particularly indicating their qualifications to teach one or more of the following core courses:Project Management Fundamentals: Understand the core principles, frameworks, and methods essential for effective project management.Project Planning, Scheduling, and Control: Explore the foundations of project planning, critical path analysis, and performance monitoring.Finance and Accounting for Managers: Apply financial principles within the context of project management.Leadership and Team Dynamics: Learn the principles of leadership, team collaboration, and high-performance team management.Capstone Project: Engage in a real-world, project-based capstone that synthesizes learning across the curriculum.Key Responsibilities:Facilitate dynamic in-person lectures, instructional activities, and engaging classroom discussions.Assess student submissions, providing timely feedback and grades.Serve as the primary point of contact for student inquiries and concerns.Conduct weekly office hours to support student learning.Prepare and maintain course materials in Canvas, Columbia University's learning management system.New part-time lecturers must complete Canvas training upon appointment.Participate in Project Management faculty meetings.If responsible for course design, additional duties include:Developing course objectives that align with broader program learning outcomes.Creating activity maps that connect course activities with objectives to ensure industry relevance.Drafting a comprehensive syllabus (course description, schedule, grading criteria, and assessments) for committee review and approval.Collaborating with Instructional Design to develop course materials through an interactive process.

Columbia University’s School of Professional Studies (SPS) is eager to invite qualified candidates to apply for a part-time position as an Adjunct Lecturer. This role involves teaching a graduate-level course focused on AI User Interfaces for Analytics. The course is designed to provide students with an in-depth understanding of user experience (UX) design principles while exploring effective techniques and best practices for developing user interfaces (UIs). Participants will engage in creating intuitive, interactive, and visually compelling websites and dashboards that highlight AI-generated insights. The curriculum encompasses the entire lifecycle from design to implementation and evaluation of UIs, ensuring students acquire practical experience with web development technologies including HTML, CSS, JavaScript, and associated cloud services. Moreover, the course incorporates advanced AI technologies to facilitate the creation of intelligent and interactive UIs.Key Responsibilities:Deliver engaging lectures, lead instructional activities, and foster classroom discussions. Classes typically convene weekly for up to 2 hours.Address student inquiries and concerns effectively.Evaluate and grade student assignments and assessments.Hold regular office hours for student consultations.

The School of Professional Studies at Columbia University is actively seeking qualified candidates for the role of Adjunct Associate Faculty in the graduate-level course on Financial Securities Analysis and Portfolio Management. This part-time position offers a unique opportunity for individuals to gain valuable experience in graduate-level instruction at one of the nation's premier educational institutions.This course delves into the intricate world of financial securities, equipping students with the analytical tools necessary to evaluate financial assets and devise effective investment strategies. It serves as a comprehensive introduction to key investment topics that are crucial for those pursuing careers in investment analysis or portfolio management.Key Responsibilities:Participate in all class sessions, assist in instructional duties, lead breakout discussions, and facilitate engaging classroom interactions.Deliver lectures, oversee instructional activities, and actively participate in classroom conversations.Assess and grade student assignments and evaluations as directed by the course Lecturer.Address student inquiries and concerns, providing support and guidance throughout the course.

The School of Professional Studies at Columbia University is actively seeking seasoned industry professionals to join our team as part-time Lecturers for the graduate-level course in Analytics for Cybersecurity Management. This course provides a thorough introduction to essential cybersecurity concepts, including network security, threat detection, and vulnerability management. It emphasizes the transformative potential of emerging AI and machine learning techniques in contemporary defense strategies. Students will engage with critical frameworks, sophisticated tools, and real-world case studies that illustrate how analytics supports strategic threat intelligence, incident response, and compliance with regulations.Key Responsibilities:Facilitate engaging class lectures, instructional activities, and discussions while attending all class sessions.Address student concerns and inquiries promptly and effectively.Assess and grade student assignments and performance.Hold regular office hours for student support.

Join the School of Professional Studies at Columbia University as an Adjunct Lecturer for our graduate-level course in Artificial Intelligence of Things (AIOT), commencing in Fall 2026. We are seeking seasoned industry professionals passionate about sharing their expertise in this rapidly evolving field.This course offers an in-depth exploration of IoT technologies and their integration with AI and robotics. Engage students in critical discussions about IoT architecture, essential components, and communication protocols, while providing them with practical experience using IoT platforms, sensors, and data acquisition tools. The curriculum focuses on real-world AIoT applications that facilitate immediate decision-making in sectors such as manufacturing, public safety, smart cities, and healthcare, while also addressing the ethical implications of these innovative technologies.Blending theoretical knowledge with hands-on assignments, the course includes weekly lectures, readings on the fundamentals of IoT, and biweekly assessments to evaluate student comprehension. Participants will demonstrate their understanding through individual assignments and a collaborative term project, laying a strong foundation in IoT analytics and AI-driven robotic automation.