It is not a good place to study. Queen Mary does not care about the students at all. Nobody is replying to my emails and if I’m lucky to receive a reply, it does not solve any issues. Student life is 0. Facilities are small, unclean and toilets are always gender neutral which is uncomfortable. It is extremely difficult to get support because they never list appropriate telephone number. Don’t even get me started with accommodation support in London. Overall I’m extemely unhappy here and I feel like QM doesn’t live up to the name of a Russel Group university
read full review
I wouldn't recommend this course to anyone. It is a complete waste of money, and it wouldn't develop you professionally. It is not challenging because the past papers were pretty much. It is relatively easy to achieve distinction. Don't waste your money. You don't need a degree to be a data scientists.
The title "Big Data" is misleading. The core module "Big Data Processing" was compressed from 12 weeks to 8 weeks, and the Big Data technology was shut down for half of the semesters up to a few days before the first exams. Unfortunately, we could not do the Big Data project and were substituted by easier quizzes for markings. You write basic code in Hadoop and Pyspark to retrieve word counts and join, which weigh 40% of the overall marks. No ETL processing was involved.
Avoid modules that involve group projects such as Digital Media and Social Network. There were a lot of students I came across in group projects who had no knowledge of programming prior to the MSc. How do you expect them to request API from Reddit and create a network graph in the first semester without understanding the fundamentals of Python? Sadly, those who contributed nothing to the project received equal marks. Also poor support from mentors for the project who rarely attend meetings.
The course content is very confusing for people who have no knowledge of coding or a basic understanding of it. The first semester consists of 5 modules instead of 4. You need to know R programming to complete Applied Statistics the MCQs. You will need to know Python to do Machine Learning, Cloud Computing and Digital Medial and Social Network (DMSM) modules. Cloud computing requires you to write Flask Application to retrieve API requests. DMSM requires you to extract a lot of information from Reddit and build a network graph using the network library. Pretty much some students were clueless. They wouldn't survive if this were an individual project.
Natural Language Processing marking is split by 40% MCQ and 60% coursework. There are three coursework, not hard if you are good at using google. There are ten quizzes, and you can attempt them twice. You can get 10/10 easy without much effort.
It was challenging to arrange an appointment with my professor when I did my dissertation. He always tells me his too busy. Lack of contact hours and support.
It is all about networking in the course. The coursework is the same as September starters or prior years. Access to answers is not hard, especially if you have good googling skills.
read full review
You are successfully registered
