Grant Career Center Report: Fill & Download for Free

A2AHere's the rundown on college rankings.US News reports that it uses “key criteria” to make assessments in their rankings. US News is a popular ranking system, and so it does make fair assessments of schools by using 15 criteria points. US News indirectly uses the career center's abilities thru what is called peer assessments (of each other).However, Education and many higher education associations use the Carnegie system to organize or label their data. In some cases, the Carnegie classifications are used to determine colleges' eligibility for grant money. In short, the Carnegie categories are the accepted standard in U.S. higher education.So, US News is the “consumer" side of the ranking process, for you and your parents and teachers to get excited about, but the data crunching is done by Carnegie system since 1983.

I am currently one of the 57 students of the first cohort of this programme, which started for the first time in October 2015 and will have its second intake in September 2016 (they moved the starting date by one month to have it synchronised with the other masters of the Business School). I am also part of the Student-Staff Committee of the programme.Why I chose this programmeI did my undergraduate studies in Switzerland, studying economics and management (HEC Lausanne) and spent my third and last yeard abroad at the University of Michigan.The Swiss education system is very similar to the German education system, and many companies in those two countries, contrary to the UK and US norm of doing a bachelor degree and directly starting a job after, require you to have a master degree, even to apply to many of the popular internships (which often last 6 months up to a year). Thus, it was natural for me to think about where I would pursue my studies at the postgraduate level.Imperial College was (and still is) one of the only top schools in the world to offer a degree in Business Analytics. I didn't want to keep studying economics as I found it had a too "scientific/researchy" connotation (leading more easily to PhDs and research positions than to the industry), and after looking at the contents of Masters in Management, it was obvious I wouldn't learn much more than I already knew from my undergraduate degree if I studied at one of them. Business Analytics was the perfect combination of technical and business thinking, keeping open doors in both IT firms and traditional finance/strategy companies. And data science is a very hot topic these days.Class ProfileThis is probably the most diverse class I've ever seen, with people coming from almost every possible background. I would say (those are all personal estimations) that we have approximately 60% of the class coming from business/economics/finance background and 40% coming from more typical engineering backgrounds (computer science/mathematics/biology/etc.). The male/female ratio is almost 50/50 (I was a bit surprised given how "geeky" the programme sounds). Most people come from Asia (especially China), a lot come from Europe with a few from England, and even fewer come from the rest of the world (Americans are generally quite underrepresented in European universities, just as Europeans are rare in American universities).Most people came straight from undergraduate with generally at least one or two internships on their resume (I was a bit the exception with no internship, but this is a bit the norm in Switzerland and I compensated it with more extra-curricular). The age ranged from 20 to almost 30 years old, but the median was probably around 23/24. A significant proportion of the class had one or two years of work experience, up to more than five years I believe, mostly in management consulting. Many of those with work experience came hoping to make a partial transition towards a more technical position, either at their company or in a different company, or legitimise their knowledge.Except from the few people who studied computer science, most students had only limited to no past experience in coding. It is my understanding that the recruiting team will give a bit more weight to programming experience this year since people with no coding experience had a really hard time learning everything from scratch.If you already have a lot of experience in data science, you will probably be bored with this programme. You will learn tons of new things for sure, but a lot will be redundant too and you would probably be better off with a regular business degree or a CS master degree.Courses and Programme StructureThe programme is part of the Business School, not of the Computer Science department. As such, almost all the classes had a business component, and some of them were almost only business classes, with a slight "big data focus". Two of our classes have been taught by the CS Department, but were designed specifically for our programme. But this is NOT a computer science programme, so you won't learn to code the same way you would have learned if you did a bachelor in computer science; courses are focused on what is useful for the business and that you can learn in the span of one year.To be honest, because it was the first year the organisation and coordination of the different classes has been quite messy, so a lot of things should be changing based on our feedback (a few courses and professors will be replaced, with a few major content changes).Most of the grading was done by assessed coursework and group projects. We only had two exams this year (there should be more next year). The biggest drawback is you end up being extremely busy some weeks, before a major deadline, and then have a lot of free time the week after, but it isn't always predictable in advance.Like almost all masters in the UK, expect to have around 13-14 hours of class per week + a few hours for extra tutorials + a lot of optional career events. This is really not much (especially compared to the Swiss system where we easily had over 30 hours per week), but it seems to be the standard all around the country (including LSE, UCL, etc.). Each semester consists of 10 weeks of class, and we have a total of 3 "semesters", but the second half of the summer semester is actually a work placement (read "any regular internship") or a consulting project for a company, as well as a short report about your work placement/consulting project and a 5000 words report about any topic you choose (like a mini master thesis), so in reality we only have 25 weeks of classes. Again, this may seem to be relatively little compared to the efforts one has to go through to get a 90 ECTS master in the German/Swiss system, but it is the standard all around the UK (and at LSE they only have 2 semesters of class + 1 full semester of exams).Courses are generally not too complex, i.e. you can almost always understand what the professor says, but quite practical, at least compared to the German/Swiss system.Programming languagesWe used mostly R and Python. Officially some workshops will be offered at the beginning of the semester, but in my opinion you MUST start learning them over the summer if you are not very familiar with those or you will quickly be completely lost. What will happen is that you will have a quick two-day workshop, then the classes will start and programming assignments will already pile up: you won't have time to both do the assignment and learn programming at the same time. This year, a lot of deadline extensions were granted because of that but it might be less flexible next year.One of the classes also required heavy use of Matlab, but it is definitely less important and can be learned later in the year. A little bit of HTML/CSS/Javascript is required for the Visualisation class (using the D3.js library), which might prove challenging, but is probably not worth studying too much in advance (unless you want to of course. Those skills will always be useful later on).A few tools such as AMPL and Tableau will also be used, but you can learn how to use those during the semester.Job searchThe Imperial brand definitely makes a difference, at least to get interviews. Succeeding at them is another story. I think many people have been disappointed this year because they thought they could completely change their career and become data scientists in one year. For most, this is unrealistic (and Imperial is not totally innocent given the way they promoted their programme): unless you have a lot of motivation, some previous experience with programming and follow my advice and heavily prepare over the summer, it will be very difficult to become "data scientist" in one of the big companies. For many recruiters, you won't even be "eligible" unless you have the appropriate bachelor degree. And this would be the same at any other school. The other issue is that many big firms recruit as early as October for the next year's intake, which really doesn't give you much time to get up to date for technical interviews (yes, don't forget to prepare for those interviews, which are totally different from what banks and strategy consulting firms require). However, this is not totally impossible, and a few people in our intake achieved this quite radical conversion.What you can easily become, however, is a data analyst, or work in virtually any business role that requires data expertise (e.g. Google. I am now doing an internship in their finance business intelligence team for my work placement; it is the very technical side of their finance department. This master prepared me perfectly for all the technologies we use here). For such roles, this programme provides an excellent preparation. If you really master the course's content, you will even have a big advantage compared to most of the other applicants.I think the drawback of this programme is that it will require much more effort from you to get a job than would for example a Msc in Management since you will have to quickly master some totally new skills and compete against people who have been studying that for many more years. But this is also what makes it more fun: there is more to learn!Career CenterI think most people would agree that the career center was a really useful resource. Almost everyday we would receive by e-mail positions we could apply for (which doesn't look like much, but this was of great convenience to be notified of all major application deadlines and informed of boutique firms recruiting), and there was almost every week a career event organised specifically for our programme (generally a guest speaker giving a talk about the company he represents, with an opportunity to network at the end. Unfortunately, most of these talks end up being quite boring) + business school career fairs a few times per semester + Imperial career fairs a few times per semester (+ other career events organised by Imperial societies). But if you are active and not afraid to ask questions and speak to the company representatives, there are things to do almost every day!On top of that, you can schedule private sessions with career consultants, which is really helpful to prepare case interviews for consulting. Unfortunately, the career team is not used to technical interviews yet (since it is the first year that business school students apply to Data Science positions) so they are of limited help for that. But this should get better over the years.I would even say that the career center of the business school is even better than at the other departments (which I suspect is partially due to the tuition level we pay).Similar programmesSimilar programme that exist today in the UK are UCL and Warwick's Msc in Business Analytics. My understanding is that UCL's programme is taught by the Computer Science department so is slightly more technical, but from what I have heard it is not fundamentally different. Warwick seems to be even less technical than Imperial's. Unless money is an issue, I think the reputation gain of studying at Imperial makes it a better choice.You might also be interested by programmes such as LSE's Msc Management Science/Operation Research/Information Systems. They are older, more common in other universities around the world, and some would say they are the "old version of business analytics". There is a bit of truth, and a few people of our class actually had offers for both (I myself rejected LSE to go to Imperial). Or if you have a bachelor in CS, I would advise continuing with a master in CS and specialising in a field such as Machine Learning.ConclusionI am personnally not a fan of the British education system (only a few hours of class per week with a lot of independent study expected and relatively easy in-class content), but if you know what to expect and this doesn't bother you, if you know how a typical management class looks like (i.e. you are taught a lot of things that might appear like common sense to you), are not bothered by the exorbitant fees (otherwise go to Switzerland, education is free even in top universities) and you are realistic about what can be achieved in one year, then you won't be disappointed. If you come mostly for the Imperial brand, you will get it. If you come to get skills you can use later in your job, you will get them. If you come mostly for the theoretical knowledge and hope to continue towards a PhD, then maybe choose a more traditionnal programme (perhaps even two years).P.S: Personal advices to learn R and Python over the summer:For all programming languages, there are three different approaches one can adopt:Classic course-taught (going to a class)Classic self-taught (reading a book/text-based website)Modern interactive/practical (on an interactive website where you receive small bits of theory together with assignements)Depending on the approach you prefer:My advice for python:Classic course-taught: The Coursera Python specialization from the University of Michigan: https://www.coursera.org/specializations/python (it's like following an introductory undergraduate CS class at the university)Classic self-taught: http://www.python-course.eu/python3_history_and_philosophy.php (it's like reading a very good book on python)Modern interactive/practical: https://www.codecademy.com (free) or https://www.datacamp.com/ (free trial, then 25$ per month. More oriented towards data science, very good website. Worth paying for one month and using intensively)Once you have reached a decent level in Python, you can start trying to solve the programming problems on http://projecteuler.net. It's a fun website that gives you mathematical problems to solve in increasing difficulty with any programming language. The problems are all made in such a way that your code can run in only a few seconds (often less than a second), but if you don't code it properly it will take a few minutes or hours to run. So it forces you to optimize what you write, to play with the different data structure and really think practically about what you are doing. It starts with really easy problems solved by half a million users, but if you take the last problems they are so difficult that only a few dozen people have found the solution.My advice for R:Classic course-taught: The R Programming course on Coursera from Johns-Hopkins University: https://www.coursera.org/learn/r-programming (it's like following an introductory undergraduate CS class at the university)Classic self-taught: (don't know any)Modern interactive/practical: https://www.datacamp.com/ (I used this one and I recommend. Free trial, then 25$ per month. More oriented towards data science, very good website. Worth paying for one month and using intensively)P.S2: I also answered a few questions for a student profile on the Business School’s application website, which might contain a few more bits of information: imperial.ac.uk/business-school/programmes/msc-business-analytics/our-community/student-profiles/jonathan-zimmermannUPDATE as of December 2016: My opinion on the programme has not changed much so my views on this post are still valid, but I have heard from the new cohort that the programme team did many changes on the courses structure following the recommendations of our cohort. Thus I would advise to contact someone from the new class to get an updated view.As of myself, I have now returned to McKinsey Geneva for a full-time position; while I am usually not writing code anymore as a consultant, the knowledge I acquired in the master has been extremely useful in my last engagements. I notably had the opportunity to work with(in) QuantumBlack, the analytics firm that McKinsey acquired, and I know most consulting competitors have similar initiatives to grow their analytics arm. I unfortunately don’t have a large enough perspective to provide accurate destination/employment data about my classmates.

My personal struggle.Almost every police officer who graduates from a police academy is usually in the best shape of their life. The transformation from a physically fit officer to, well jumbo officer takes years.Look at the photograph, which is not me! Do you think this officer could run from his car, 50 yards to a house, and then run-up two flights of stairs and physically engage and overpower an assailant?I seriously doubt it. An officer in this condition is likely to suffer a heart attack during an event such as I described. It’s hard to serve and protect in an emergency situation when you are not physically capable.In my very first year, I worked shift work, grabbed fast food meals on the run, and spent the majority of my day sitting in a police car, and the process had begun.Sitting behind a typewriter or computer screen doesn’t help either. It doesn’t happen all at once. I tried to work out and jog on my days off and only gained a few pounds per year. But it was a few pounds every year, going from 185 pounds out of the academy to 200 pounds after four years on the street.From there it was a slow steady progression of just a couple of pounds a year. I would work at it and level off at 215 for three or four years but then the weight would continue to slowly rise. Bear in mind, I was considered one of the more physically fit officers in the department. I worked on street crimes and narcotics. It’s even worse for the officers in patrol cars working rotating shifts.I found, the more stress I was under the more I ate. Burger King, McDonald's, and those personal pizzas from Little Ceasers were my favorite. I can still taste them. I did have a year that I ate only Subway subs for lunch, but then they closed and I was back to Pizza-Pizza, in a box ready to go for five bucks.Most departments don’t have exercise programs or incentives for officers to stay in shape. When I became a lieutenant, our department moved into a newer, old building which unlike the last old building was not full of asbestos.The newer building had a full basement which I wanted to turn into a fitness and workout area for the officers.I completed a detailed final project for my Certified Public Manager course consisting of plans for a fitness center at the department. It had sample policies regarding the use of the facility and the funding sources were all in place.The center would include dumbbells, specific plate stack machines, a cable crossover machine, treadmills, and other cardio fitness equipment.I had grant money in place for building walls and rubber floors, and the purchase of equipment. The union loved the idea!I made a presentation to our chief, who very quickly said no. He believed that officers would injure themselves on the equipment and claim duty injuries. I suggested waivers of liability, but the plan died a quick and quiet death.The chief pointed to our paid fire department that had a nice exercise facility which we could use. The only problem was we couldn’t workout at night or in the early morning hours because the firefighters were all sleeping. (Yes, that always bugged me, getting paid to sleep)After six years in Internal Affairs which was all behind a desk, conducting interviews and writing detailed reports, with massive stress, I topped out at 245 pounds. That’s sixty pounds I added during my career!Once I retired it took me two years to get my weight back down to two hundred pounds which is where I’m trying to keep it. My health is now my number one concern and without all the stress, life is much better, and fast food is but a distant memory.I think going forward; departments owe it to their officers and the public to keep their officers healthy, and physically fit. This should be done either through monetary incentives verified by testing or by providing an exercise facility and some time to exercise.If the city can afford to pay firefighters to sleep for eight hours, then they can afford to pay police officers to exercise for one!Author of the 2020 book “One Cop’s Life” available on amazon