New England College

The Data Science Tools class offers an excellent introduction to essential tools and techniques for anyone pursuing a career in data science. The quality of the class is top-notch, as the curriculum is well-structured and balances theoretical concepts with practical application. The course covers key tools such as Python, R, and Jupyter Notebook, and provides ample opportunities to practice through hands-on assignments. The homework load is manageable but requires consistent effort. Weekly assignments are designed to reinforce class topics and push students to apply what they've learned. While the workload might feel intense at times, it ultimately enhances understanding and ensures skill development. Classroom discipline is well-maintained, creating an environment conducive to learning. The professor sets clear expectations and enforces policies, such as no use of distractions like phones during lectures. Attendance requirements are strict but fair, and active participation is encouraged, which helps in building a collaborative learning atmosphere. The professor's teaching style is engaging and effective. They make complex topics approachable by breaking them down into simpler concepts and providing real-world examples. They are also approachable outside of class and genuinely invested in student success. Overall, this class is a valuable learning experience, especially for students passionate about data science. The balance of rigor and support makes it challenging yet rewarding, and it leaves students well-prepared to use essential tools in future projects or professional roles.

Overall, Professor Shawn Desince’s class is well-received by students. His teaching is highly rated for its clarity, engaging nature, and the depth of knowledge he brings to each lesson. While the homework load can be demanding, it is manageable and aligned with the course objectives, and students appreciate the meaningful feedback he provides. His classroom discipline and attendance policies are fair and structured, contributing to a focused and productive learning environment. Students frequently praise his ability to explain complex topics in accessible ways and his willingness to offer additional help outside of class. His teaching style promotes active learning, and the interactive elements of the course make it easier for students to stay engaged. His approachability and commitment to student success also stand out, making him a well-regarded professor who goes above and beyond to ensure his students succeed. In conclusion, students can expect a rigorous but rewarding experience in Professor Desince’s class. Whether you are a student looking to deepen your knowledge in the subject or someone who thrives in an interactive, student-focused learning environment, this class provides a strong foundation for academic growth and achievement.

The "Introduction to SQL for Data Analytics" course has been a valuable learning experience that provided me with a strong foundation in one of the most critical tools for data analysis: Structured Query Language (SQL). Below, I’ve outlined my thoughts on various aspects of the course, including its quality, workload, classroom discipline, attendance requirements, the professor's teaching style, and my general evaluation. This course is exceptional in its structure and content delivery. The syllabus is thoughtfully designed to cater to both beginners and those with some prior exposure to SQL. The material starts with basic concepts, such as SELECT statements and filtering data, and gradually builds up to advanced topics like JOINs, subqueries, and window functions. What stood out the most was the balance between theory and practical application. The class emphasized real-world scenarios, allowing students to understand how SQL is used in data analytics projects. The incorporation of hands-on exercises and case studies was a highlight. Instead of merely focusing on syntax, the course pushed us to think critically about how to design efficient queries and extract insights from data. This practical focus made the class engaging and directly relevant to my career aspirations in data analytics. The "Introduction to SQL for Data Analytics" course is a must-take for anyone interested in building a career in data analytics or related fields. It combines theoretical depth with practical application in a way that few courses manage to achieve. The professor’s teaching style, coupled with the well-organized curriculum, makes this class an enriching experience for students at any level of expertise. I would highly recommend it to anyone looking to strengthen their data analysis skills and prepare for real-world challenges in the field of analytics.

easy assignment, ChatGPT is ok, full score as long as you completed it.

easy assignment, low load, can use ChatGPT for assignment. Almost all full score of assignment

Some reading every week, homework is reasonable load

The videos are straightforward, the amount of homework is about right. I do learn a lot from the course.

Lots of reading (2 textbooks for this course) and they are not fun to read (dry content). Discussion posts (25%) every week and writing assignments (20%) almost every week. Grading is very strict - must meet the grading rubric criteria in order to score. For example, you won't earn full points on discussion if you do not 'advance the conversation' by asking a question or offering a counter argument. The instructor is also very strict on citation format (since this is a writing course). The instructor does provide grading feedback for each assignment so you know where you can improve. There are a few multi-choice quizzes (15 %) and they are pretty easy.

Reading assignments are not too heavy. The textbook is not boring to read, and the instructor provided some online videos that kind of summarize that week's assigned reading. Discussion posts (1/3 of course grade) every week and a writing assignment (1/3 of course grade) every other week (approximately). Grading is fair (i.e., not too strict), and the instructor will provide detailed feedback for each assignment so that you address any issues.