Introduction to Data Science

Prof Malcolm-White is wonderful. Approachable and easygoing. I took this course because I wanted to learn a bit of R. I have no CS background and found the material very accessible. At times, I felt like the course was narrow and too focused on data visualization . I enjoyed the course but would have appreciated more data science topics and challenging R scripts.

It was a very enjoyable class and all the information was explained clearly! I would definitely recommend taking this class. It is beginner friendly approach to understand data science and R programming language.

This introductory data science course provides a strong foundation in key concepts such as data manipulation, visualization, and basic statistical modeling. Throughout the course, I gained hands-on experience with tools like R and Python, learning how to clean, analyze, and interpret datasets effectively. The structured assignments and projects helped reinforce important skills, particularly in data wrangling and visualization, which are essential for real-world applications. One of the most valuable aspects of the course is the emphasis on problem-solving and critical thinking. Rather than just focusing on coding, the course encourages students to understand the logic behind data analysis, making it accessible even for those without prior programming experience. The collaborative environment, including discussions and group work, also enhances the learning experience. For prospective students, I recommend engaging with the course materials early and practicing coding regularly. While some concepts, such as statistical inference and data cleaning, may seem challenging at first, consistent practice will make them more intuitive. Additionally, leveraging online resources and working on small personal projects can deepen your understanding. Overall, this course provides a great entry point into data science, equipping students with essential skills for future studies or careers in data analytics.

This introductory data science course provides a strong foundation in key concepts such as data manipulation, visualization, and basic statistical modeling. Throughout the course, I gained hands-on experience with tools like R and Python, learning how to clean, analyze, and interpret datasets effectively. The structured assignments a …Read more

Alex is one of the finest professors I've had (if not, the best). He is very clear and does not let people fall behind, and all the work is reasonable. He's incredibly approachable and knowledgeable, and I felt that I could ask him anything. This was a super fascinating course that dealt with R-Studio and taught me a lot of fundamentals that I have been able to use in other courses; it was cool to make graphs and see trends in data based on coding, and as someone that had never taken a coding class before, I felt like this one was perfect. Once you get the hang of it, this class is fun and the assignments are almost like puzzles/games, where you can choose how you answer/approach questions.

Alex is one of the finest professors I've had (if not, the best). He is very clear and does not let people fall behind, and all the work is reasonable. He's incredibly approachable and knowledgeable, and I felt that I could ask him anything. This was a super fascinating course that dealt with R-Studio and taught me a lot of fundament …Read more

I was initially nervous about this class since I was unfamiliar with R, but Professor Malcolm White made the class super engaging, fun, and easy to follow! I think that everything I learned in class was super useful and I have been able to apply what I have learned to some of my other classes and research. I would definitely recommend this class to anyone who is curious about data science or just wants to pick up on a new and useful skill because this was a fun and easy class!

I was initially nervous about this class since I was unfamiliar with R, but Professor Malcolm White made the class super engaging, fun, and easy to follow! I think that everything I learned in class was super useful and I have been able to apply what I have learned to some of my other classes and research. I would definitely recommen …Read more

Emily lectured in the first half of class, then the second half was for homework. The homeworks are all pretty short, so you basically finish the homework in class and have no work for the week. She's also super nice and super helpful when you are confused.

Really great course! My only regret was taking it after already completing MATH 211 and MATH 311. Unfortunately, this course overlapped significantly with the material from those two. However, the review was still useful, and all of the material I hadn't already seen was extremely helpful. I feel like a much more competent R user after this course. I have already put many of the techniques we learned in this class to use in a final project for another course.

Really great course! My only regret was taking it after already completing MATH 211 and MATH 311. Unfortunately, this course overlapped significantly with the material from those two. However, the review was still useful, and all of the material I hadn't already seen was extremely helpful. I feel like a much more competent R user aft …Read more

This course teaches you R, lots of data visualization, and a bit of data analysis. The assignments have detailed instructions and are closely related to lecture contents - they are very approachable. However, as a CS major, the coding part is a bit too easy for me. I suggest you take the class if you have a non-CS background or simply wants an easy A.

I found this to be a fun easy class, though I should mention that I am a computer science major so I have plenty of experience with coding. I feel as though I effectively learned how to perform data science in R, and it inspired me to accept a data science internship for next summer. Lectures were live-coding along with the professor, and homeworks -- which tended to be completed in class -- were very similar to the in-class notes. I would recommend this class to anyone interested in data science -- even if you've never done any sort of coding before.

I found this to be a fun easy class, though I should mention that I am a computer science major so I have plenty of experience with coding. I feel as though I effectively learned how to perform data science in R, and it inspired me to accept a data science internship for next summer. Lectures were live-coding along with the professor …Read more

I took this course particularly because I was interested in taking a data science course. This class helped me learn the fundamental tools in using the software r for data science. I learned how to tidy data and create visualizations and then communicating the results. It does require a lot of coding because it is using a software. The material was new to me, but the instructor was great at explaining the topics through organized presentation slides. Also, after each class students were assigned apex assignments which are small assignments that enable you to practice the things students learned during the class that day. These apex assignments helped the students be more prepared for exams and final projects.

I took this course particularly because I was interested in taking a data science course. This class helped me learn the fundamental tools in using the software r for data science. I learned how to tidy data and create visualizations and then communicating the results. It does require a lot of coding because it is using a software. T …Read more

This course covers a good deal about wrangling and visualizing data. By the end of the course, you are able to apply these skills to a project of your own interest which you should feel proud about. Becky is enthusiastic and clear with her teaching. It takes very little effort to keep up with the classwork; that is until the end when the project seems like a bit too much work for such little time.

This course covers a good deal about wrangling and visualizing data. By the end of the course, you are able to apply these skills to a project of your own interest which you should feel proud about. Becky is enthusiastic and clear with her teaching. It takes very little effort to keep up with the classwork; that is until the end when …Read more

Professor Emily Malcolm-White is one of the greatest professors I've ever had. Data science is revolves largely around using R studio to analyze data and is rooted in computer science. I have no background in compute science whatsoever, but Professor Malcolm-White made approaching it really easy and straightforward. She walks through every step of what you need to understand during her class presentations during the first half of class, and then she's available for the second half of class to help along with the TA on homework! If you're interested in statistics, graphing, and analyzing data, this course would be great for you! This course, however, is not about statistics and doesn't delve too deeply into statistics math. This is not a very math-heavy course.

Professor Emily Malcolm-White is one of the greatest professors I've ever had. Data science is revolves largely around using R studio to analyze data and is rooted in computer science. I have no background in compute science whatsoever, but Professor Malcolm-White made approaching it really easy and straightforward. She walks through …Read more

Favorite class and favorite professor so far. The lectures are super enjoyable and interactive. We often broke out into groups and worked on implementing what we were learning in class and he would help us with any questions we had. Although the exams were difficult and time-consuming, they were open note and open internet. The final group project assignment is very fun and if taken seriously can possibly become a resume piece. In terms of grading, definitely not an easy A, but achievable. I would estimate the average grade in the class was a B+.

Favorite class and favorite professor so far. The lectures are super enjoyable and interactive. We often broke out into groups and worked on implementing what we were learning in class and he would help us with any questions we had. Although the exams were difficult and time-consuming, they were open note and open internet. The final …Read more

I really liked this course. It is very relevant to my studies (computer science and math) so I had touched on some of the topics in previous classes. That being said, Becky was very reachable and very helpful in office hours if I was ever stuck. I also really enjoyed our end of semester project.

Emily is an awesome professor! This was one of the easiest classes I've taken at Middlebury, but the knowledge I gained was so important. I took this course with no coding background, but I was concurrently enrolled in CS 0145. The class is structured so that you do an assignment in class and then do a homework assignment based on that material and I usually finished the homework in class. Towards the end there were some trickier concepts, but the TAs and Emily were super accessible. The midterm and final were just analyzing a dataset in different ways.

Emily is an awesome professor! This was one of the easiest classes I've taken at Middlebury, but the knowledge I gained was so important. I took this course with no coding background, but I was concurrently enrolled in CS 0145. The class is structured so that you do an assignment in class and then do a homework assignment based on th …Read more

This course was one of the easiest I have taken at Middlebury thus far. We had two homework assignments a week, and we had half of each class period to work on these assignments and ask the professor and TA any questions about them. There were two projects during the semester. The first one was a partner assignment where you picked from three datasets to analyze. The second project, which was considered our final, was essentially the same thing, but it was an individual project and you had to find your own dataset. Emily and the TAs were easy graders, and while the homework/projects were difficult at times, Emily was always happy to help. Overall, I would highly recommend this course to anyone wanting an easy class that isn't too much work outside of class.

This course was one of the easiest I have taken at Middlebury thus far. We had two homework assignments a week, and we had half of each class period to work on these assignments and ask the professor and TA any questions about them. There were two projects during the semester. The first one was a partner assignment where you picked f …Read more

The course is designed to learn R from its basis, Professor Malcolm-White is very accommodating and makes sure all students understand and can follow the flow. The last 30 minutes of class are made left for homework, which really decreases outside class study. Would totally recommend taking a class with her.

EMW is an exceptional professor! She was very helpful and patient when teaching material like using R which is often new for many students. Her organization of all course materials is impressive with the notes being posted in advance for the whole semester so it's easy to look back on something you may have forgotten how to do. Overall really recommend!

Emily typically sets class up in this way: the first 45 minutes are a follow along presentation, she provides fill-in-the-blank notes for you to follow along with, and the last 30 minutes are reserved for completing homework and asking questions. It is definitely an easier course. It is also R-based, but I found that to be super helpful and I honestly learned a ton from the class!

This was the best-organized class I have taken. Professor Malcolm-White designed the Canvas page extremely well - it had easy access to cheat sheets for R packages as well as filled-in notes. It's still useful to me now. Each lesson came with a short homework assignment which was always due the same time, so it was usually 2 a week. Projects involved choosing your own dataset, which was nice.

This was the best-organized class I have taken. Professor Malcolm-White designed the Canvas page extremely well - it had easy access to cheat sheets for R packages as well as filled-in notes. It's still useful to me now. Each lesson came with a short homework assignment which was always due the same time, so it was usually 2 a week. …Read more

This was a super easy, very digestible course that focuses exclusively on programming in R Studio. Emily is a super direct and concise instructor; she explains things simply and makes it comprehensible for someone who's not an amazing math student in general.

This class was one of the most low stress courses I have ever taken at Middlebury. Professor Malcom-White really works with students to make sure they understand material, and she does not want to punish students with difficult problem sets or projects. Assessments provided fair opportunity to show understanding and I would certainly take a class with her again if possible.

This class was really engaging and useful, while also being an extremely manageable course. There was time in class to start working on the homework with the professor and TA walking around to help. This format really reinforced my learning and has been one of the most enjoyable classes I’ve taken at Middlebury. Highly recommend!

Intro to Data Science was a super chill but informative class. I had zero previous experience in data science or programming in R, but Prof. Malcolm-White made sure everyone is the same place as me would get lost in the course content. For any one who enjoys programming and is looking for a mellow, applied-programming course, this is a great one to go for.

This course is what the title makes it to be — an introductory level class to Data Science. I had no prior experiences to R, and this class eases you into R basics which was useful for me taking future courses with Becky. Overall a fun class and learning experience!

Alex is the absolute best professor I have had here. He is a great professor, and is someone that always cares about his students. I loved learning R with him, and I am pursuing more courses in this major because of the amount that he opened my eyes to. His teaching style is really good, and I have loved doing research with him now.

Professor Lyford was very passionate and he taught us a lot of interesting things and valuable skills about data analysis. He was very engaging in the lectures and I have found so much fun in this class.It was an eye-opening course for me and I benefitted a lot from it!

I think that Becky is very knowledgable for her field. She teaches intro R better than Rao does in Econ stats, and I feel like I understand how the code interacts with what we want the end result to be. That being said, there is often a lot of confusion on what the expectations for the homework are so I lost a lot of points due to not a lot of clarity.

This class was interesting, the grading was based on your personal background and what you were interested in getting out of the class, and Alex Lyford is one of the best professors I've had. I learned a lot of R.

Tang was a great professor, really nice and helpful when you needed help. She is kinda a hard grader and kinda strict sometimes with like deadline typa things. But not very hard class for a CS major and pretty fun

Professor Tang was great. This is a great introduction to R and all of the basics you would need to get your feet wet in data science. All of the grading was very fair and group work is encouraged which is nice. The final project was fun.

This class was one of the most relaxing classes I've ever taken at Midd. An easy introduction into the world of coding and data science, and a very good way to earn your DED credit. Emily Malcolm-White is super kind, she's the kind of prof you don't mind having a class at 9 am with.

This was an awesome introduction to R for someone who'd never used the language before. The information was easy to follow and was introduced in a way that made sense. Most of the homework was completable in class time

One of my favorite courses I have taken at Midd! It was the perfect combination of learning a lot but also not stressful at all. You can complete most of the homework assignments during class as she gives you time to do that.

Professor Lyford is one of the most enthusiastic and personable professors I have had so far at Middlebury. The class is super rewarding and introduced a new topic in a very manageable way. The HW assignments do take some time to finish.

Alex is hands down the best instructor at Middlebury. He is explains concepts really well and in a compelling way. He is also incredibly accessible if you run into a coding issue. I would totally recommend this course.

This class was awesome! I enjoyed the material and felt it was a very manageable amount of work. Alex's enthusiasm for the course made me even more motivated to learn. I would definitely take this course or a similar one again.

As a computer science major, this class was extremely easy and I found myself not having to do any work outside of the class. I took it as a prereq for 216 and it was a good experience to have a class this easy in my workload.

Alex is great - he put so much effort on teaching and you could tell that he does enjoy interacting w/ students (at least speaking for the class which was when he does not have tenure yet). He structures the course to have very useful materials too.

Data Science with Malcolm White provides an enriching educational journey. White's expertise shines through his engaging teaching methods and clear communication. With fair assessments and insightful guidance, she fosters a strong understanding of data science principles.

It was online, so it was harder to receive feedback and further instructions from the Professor, especially about how to navigate around R. It is very project-based and you need to do 3 or 4 throughout the semester. I would recommend pairing up with someone to make the workload easier when doing the projects.

Professor Lyford is one of the two most enthusiastic and energetic professors I've had with the STEM departments (the other teaches CS150 :). The class is R-based and heavy in R-coding, which most find easier than coding in Python or Java. The projects and take-home exams may take a while but are manageable.