Course Selection - Making the Right Choices
Choosing the right courses can often feel like solving a complex puzzle. As an international student at UMass Amherst and a graduate student in computer science, I understand the challenges of finding that perfect balance between fulfilling graduation requirements, exploring personal interests, and acquiring skills for future career prospects. Through my own experiences, I have learned valuable lessons and gained insights on how to make informed decisions when it comes to course selection. In this chapter, I will share my stories and advice on how to navigate the course selection process and make the right choices for your academic and career goals.
My first semester: Finding my footing
During my first semester at UMass Amherst, having transitioned from the startup sector, I ambitiously enrolled in three 600-level courses. This decision, driven by my work experience and overconfidence, propelled me deep into advanced academic topics. It was an immersive dive that broadened my research interests and intellectually challenged me. However, the complexity and intense workload of these courses were higher than I had anticipated.
Despite the initial struggle, this experience turned into a valuable lesson about the importance of understanding my own capabilities and boundaries. It taught me that while ambition is essential, it is equally important to balance it with pragmatism. It's critical to be realistic about how much workload you can handle to avoid burnout and maximize your learning experience.
While this approach might not suit everyone, it worked for me. However, it's a strategy I caution others about. It's essential to gauge your limits accurately and select a course load that aligns with your academic goals and personal strengths. Always aim for a balance between testing your limits and ensuring you can effectively handle the challenges that come your way. Remember, the goal is not just to survive your academic journey, but to thrive in it.
Evolution of interests: How course selection helped
Initially, my interest was primarily focused on computer vision due to my previous work experience in graphics. However, I was eager to explore other courses, as I saw computer science not as an isolated discipline but as a versatile tool for problem-solving applicable across various fields.
During my first semester, I enrolled in Advanced Natural Language Processing (NLP), a decision that ended up being instrumental in shaping my academic path. Despite being outside my primary area of interest, this course equipped me with skills that later proved vital for a collaborative project with Meta involving multi-modal learning in the spring of 2022. This interdisciplinary approach to course selection not only deepened my understanding but also broadened my horizons, opening up new and exciting opportunities.
One such opportunity was the chance to work in the Human-Centered Robotics Lab under Professor Hao Zhang. This was made possible due to the diverse knowledge and experience I had gained, particularly from my collaboration with Meta. My story underscores the value of stepping outside one's comfort zone in course selection. While it's essential to maintain focus on your core interests, exploring different areas can lead to unforeseen opportunities, contributing to a well-rounded skillset and more rewarding academic and career experiences.
Course choices: Direct impact on career
Choosing the right courses can significantly impact your career by shaping your knowledge base, skills, and future prospects. While the temptation to stick to easier courses and fulfill basic graduation requirements is understandable, I encourage you to consider a different approach. Challenging yourself with more demanding courses not only broadens your interests but also opens up new opportunities. These challenging courses, despite their rigor, can deepen your understanding and equip you with an edge in your future career.
Courses with a substantial project component are especially valuable. These courses allow you to apply academic concepts to real-world scenarios, enhancing your learning experience. Moreover, these projects serve as tangible proof of your skills and can be a great addition to your resume, demonstrating your competency to potential employers.
Lastly, undertaking challenging courses allows you to acquire a depth of knowledge that can give you an advantage in job interviews. Discussing complex subjects showcases your understanding of the subject matter and reflects your passion and commitment to learning. Although the journey might be tougher, the rewards of taking harder courses are significant. They contribute to both personal growth and career advancement, making the journey a rewarding experience.
My course recommendations
Based on my own experiences, I have compiled a list of courses that I recommend. These courses are challenging but rewarding, providing a practical understanding of academic concepts and equipping you with valuable skills for your future career.
Course Number | Course Name | Professor | Course Website | Semester | Recommendation Level |
---|---|---|---|---|---|
COMPSCI 514 | Algorithms for Data Science | Cameron Musco, Andrew McGregor | Fall 2022, Spring 2023 | Fall, Spring | ★★★★★ |
COMPSCI 515 | Algorithms, Game Theory and Fairness | Yair Zick | Fall 2023 | Fall | ★★★★ |
COMPSCI 520 | Theory and Practice of Software Engineering | Heather M. Conboy | Spring 2023 | Fall, Spring | ★★★ |
COMPSCI 532 | Systems for Data Science | Peter F. Klemperer, Hui Guan | Fall 2022, Spring 2023 | Fall, Spring | ★★★ |
COMPSCI 546 | Applied Information Retrieval | Hamed Zamani | Spring 2022 | Spring | ★★★ |
COMPSCI 560 | Introduction to Computer and Network Security | Parviz Kermani | Fall 2023 | Fall | ★★★ |
COMPSCI 574/674 | Intelligent Visual Computing | Evangelos Kalogerakis | Spring 2023 | Spring | ★★★★★ |
COMPSCI 576 | Game Programming | Evangelos Kalogerakis | Fall 2022 | Fall | ★★★ |
COMPSCI 578 | Cloud and Distributed Computing | Arun Venkataramani | Fall 2021 | Fall | ★★★★★ |
COMPSCI 589 | Machine Learning | Hui Guan, Bruno Castro da Silva | Fall 2023, Spring 2023 | Fall, Spring | ★★★★★ |
COMPSCI 603 | Robotics | Hao Zhang | N/A | Spring | ★★★★ |
COMPSCI 611 | Advanced Algorithms | Hung Le | Spring 2023 | Fall, Spring | ★★★★ |
COMPSCI 630 | Systems | Emery Berger | Spring 2023 | Spring | ★★★★ |
COMPSCI 646 | Information Retrieval | Hamed Zamani | Fall 2023, Fall 2022 | Fall | ★★★★ |
COMPSCI 651 | Optimization in Computer Science | Madalina Fiterau | Spring 2023 | Spring | ★★★★ |
COMPSCI 677 | Distributed and Operating Systems | Prashant Shenoy | Spring 2023 | Spring | ★★★★★ |
COMPSCI 682 | Neural Networks: A Modern Introduction | Subhransu Maji, Chuang Gan | N/A | Fall | ★★★★ |
COMPSCI 683 | Artificial Intelligence | Yair Zick | Spring 2023 | Spring | ★★★★ |
COMPSCI 685 | Advanced Natural Language Processing | Mohit Iyyer | Spring 2023 | Spring | ★★★★★ |
COMPSCI 687 | Reinforcement Learning | Bruno Castro da Silva | Fall 2023 | Fall | ★★★★★ |
COMPSCI 689 | Machine Learning | Benjamin Marlin | Fall 2023 | Fall | ★★★★★ |
Remember, while these courses are challenging, they offer a wealth of knowledge and practical experience that can be directly applied to your future career. In line with my personal strategy, I would suggest taking two 600-level courses and one 500-level course each semester. This combination allows for a balanced workload, providing the opportunity to delve into more complex topics while still ensuring you have the time and energy to dedicate to each course.
Resources for course selection
- MS Requirements: This resource outlines the academic requirements for a Master's degree in Computer Science at UMass Amherst.
- List of MS Core Classes: Here, you can find a list of core classes for the MS degree.
- Course Load Survey: CICS Graduate Students were polled on the amount of time they spent on their classes. Results are from the January 2021 survey.
- CICS Course Offering Plan: This is a plan in every sense of the word, things can change.
- Pre-Approved Non-Computer Science Courses: This list provides pre-approved non-CS courses that count towards the MS degree.
- Information about the Data Science Industry Mentorship Class- CS 696DS: This resource provides information about a unique course that pairs students with industry mentors.
- Field Experience Concentration: This resource provides details about the field experience concentration.
- Data Science Concentration: Here, you can find information about the data science concentration and its elective requirements.
- Security Concentration: This resource provides information about the security concentration.
- Rate my Professor: This is a great resource for finding out more about professors and their teaching styles.
- Independent studies: This document provides information about independent studies and how to enroll in them.
This book was created by Subramanya Nagabhushanaradhya with the help of wonderful friends. For feedback, errata and suggestions, the author can be reached on linkedin. copyright ©2023 Subramanya Nagabhushanaradhya