Algorithms and Complexity This course focuses on the development of correct and efficient algorithmic solutions to computational problems, on the underlying data structures to support these algorithms, and on the social implications of algorithms. Topics include computational complexity, analysis of algorithms, proof of algorithm correctness, some advanced data structures, algorithmic techniques including greedy and dynamic programming, and the consequences of real-world applications of algorithms. The course complements the treatment of NP-completeness in CSCI 0301.

The Immigrant Experience In this seminar we will explore the diverse experiences of immigrants to the United States through literature and experiential, community-engaged learning. We will examine themes such as migration, identity, belonging, labor, language, race, and intergenerational change. Readings include novels, memoirs, and essays from writers who draw on their own immigrant experiences and scholars who study migration across cultures and generations. We will engage immigrant voices through conversation and hands-on cultural exploration. We will critically think about and reflect on the links between individual stories to broader questions about immigration in American life. We will focus on lived experience, storytelling, and cultural expression rather than contemporary political debates surrounding legal and illegal immigration.

Data Structures In this course we will study the ideas and structures helpful in designing algorithms and writing programs for solving large, complex problems. The Java programming language and object-oriented paradigm are introduced in the context of important abstract data types (ADTs) such as stacks, queues, trees, and graphs. We will study efficient implementations of these ADTs, and learn classic algorithms to manipulate these structures for tasks such as sorting and searching. Prior programming experience is expected, but prior familiarity with the Java programming language is not assumed.

Artificial Intelligence Artificial Intelligence (AI) is the study of computational systems that exhibit rational behavior. Applications include strategic game playing, medical diagnosis, speech and handwriting recognition, Internet search, and robotics. Course topics include intelligent agent architectures, search, knowledge representation, logical reasoning, planning, reasoning under uncertainty, machine learning, and perception and action. We will also discuss the social implications of AI systems. This course fulfills the Responsible Computing requirement for the Computer Science major.

Posse Scholars Leadership Development This course is designed to promote the intellectual, social, and civic development of first-year Posse scholars, both individually and as a group. Students will attend weekly workshops drawing from the Posse Foundation’s leadership curriculum. Workshops will also draw on the instructor’s areas of expertise and will focus on topics most pertinent to students’ goals and needs. Some workshops will include guest lectures, experiential learning, and student-facilitated discussion.  Students will reflect on their learning in bi-weekly meetings with the instructor, as well as in writing.  They will also identify initiatives or projects they wish to promote on campus or in the local community, applying what they have learned. (This course is only open to sophomores.)

Senior Thesis The senior thesis is required for all CSCI majors who wish to be considered for high and highest departmental honors, and is recommended for students interested in pursuing graduate study in computer science. Students will spend the semester researching and writing, and developing and experimenting as appropriate for their topic. All students will be expected to report on their work in the form of a written thesis, a poster, and an oral presentation at the end of the semester. In addition, throughout the semester, students will meet as a group to discuss research and writing, and will be expected to attend talks in the Computer Science lecture series. Before approval to join the class is granted, students are expected to have chosen a thesis adviser from the CSCI faculty, and determined a thesis topic with the guidance and approval of that adviser.

Ananya Das

Reviews and ratings for Ananya Das at Middlebury College.Ananya Das teaches Algorithms and Complexity, The Immigrant Experience, Data Structures and more.  Explore top rated instructors and find the best for you.Is Ananya Das good ? Find out on MiddCourses.

You have to take this for the major, and it is nothing more than that. The content was not particularly interesting and does not feel as relevant for the major as some of the other mandatory classes. While very kinda, Professor Das did not explain the concepts particularly well and often left me confused. 

This class is notoriously hard with Professor Das, and I got the feeling that everyone in the class was having a hard time. The professor had us solve the biweekly problem sets in groups of 3 or 4, which was both helpful but annoying to coordinate. The exams are fair, though, with most problems being similar to the homework and practice problems.

Homework is just based on submission but 70% of the grade is based on the exam. The average exam score was around 80 so I think it's hard to get a good grade in this class. Her explanation about algorithms was pretty clear, and the pace was good