Year 3 Autumn EE Modules

Autumn Term

ELEC96003 – Analogue Integrated Circuits and Systems (Toumazou, Georgiou)

‘Badly taught, Exam questions are the same every year, Lectures not recorded, No slides shown on the board - uses a simple projector’ – 2019/20

Personally, a game changer for me in terms of analogue electronics. Used to hate analogue in year 1 and 2 but Toumazou provides a different outlook on analogue (which for me made it way easier to understand). The lectures were good, they were recorded and his scribbles on the pages were great too. Sure, the exam questions remain pretty similar every year but it means that I focused way more on the topics I wanted to learn more in depth about. Would recommend for anyone looking for a different, more practical outlook with analogue but just don’t expect like you’re going to understand as in depth as you’d imagine. - HH, 2020/21

ELEC96005 – Artificial Intelligence (Pitt)

I personally found the lecturer Jeremy Pitt to be brilliant at making the material engaging and helpful in any issues people had. The content is enjoyable to work through. The tutorials do not fully cover the knowledge needed for the exam but are very useful to do alongside past years papers. Unlike some modules, a genuine understanding of the course is needed for the exam specifically with things relating to Prolog. (2020/21).

Good lecturer, good handout - 2019/20

ELEC96006 – Biomedical Electronics (Georgiou, Constandinou)

This module pulls together parts from content in the first two years mainly analogue circuits, however a basic understanding is all that's needed. The content is enjoyable to learn about and feels rewarding. The lecturer is very slow with emails if they even bother to reply at all so hopefully you can go in person to their office to get a response. However, the exam is challenging and requires a good understanding to answer questions not directly taken from the notes. (2020/21)

Great module for engineers, it forces you to think about the practical aspect of engineering. Most modules prior, with the exception of analogue 2 are theoretical. What do I mean? Most modules tend to have one answer and one approach, which is not real engineering. This will be one of the modules that expect you to approximate and make assumptions to make your calculations easier. If you have no interest in biology then, it will not be a pleasant experience. Understand how to apply the knowledge and attend all gta hours, they are very useful. Content is a lot but not too hard to understand, do as many papers as you can, it will help you get used to the style of the exams. (2020/21)

This one has a good general overview, but I personally could recommend some practical work. If this module could also add another one in the Spring term for the coursework, that would be very nice. This is similar to Machine learning and deep learning. - 2019/20

ELEC96007 – Communication Networks (Barria)

I personally found the notes and slides provided very poor and the lecturer didn't hold my attention well. Any slide can come up in the exam even if brushed over in 30 seconds of a lecture. That said, the exam is very basic and can be done easily if you know the material well. (2020/21)

Did not enjoy this module, no experiment/practical work, just need to memorise notes and you can get high marks. Teaching is boring too as the lecturer just follows the notes – 2019/20

About OSI architecture, very dense, a lot of memory work, every slide could be tested in exams which is mainly a regurgitation exercise. I guess Comm net stuff is important for knowing basic stuff about how the internet works but it was really hard for me to understand and connect things learnt in lecture to the overall picture. Very steep learning curve for those who don't know anything about internet protocols or how the internet works, but worth learning if you're interested in this area. – ykw, 2019/20

Agree with most above, Barria is nice but bad at teaching. He just reads his notes and you can do just as well not attending lectures and learning all his slides. It’s a shame because OSI is such an interesting module. For EIE students who took Comms with DoC in 2nd year it might be worth it, less content to learn. - MG 2020/2021

ELEC96008 – Communication Systems (Manikas)

Exam is heavily based on the extensive problem sets so get to know them well! It's a very very long and varied course. It really does develop your intuition. Hassle Manikas when you have questions and you will get them answered. Really patient guy. Super passionate about his subject (2020/21)

Really liked the module all in all, and would recommend to anyone interested in Comms. Personally found the content very demanding, mainly due to the sheer volume. There is a lot of stuff. The exam is comparatively straightforward, and if you do and understand all the problem sheet questions, the exam wont be too bad. If you put in the effort, it will pay off. There is also a coursework element to the module over Christmas on MATLAB, which isn't easy but manageable over the break. Manikas is also very good, explaining content well and also answering questions effectively.(2020/21)

This module is highly recommended to anyone interested in Comms. The content is long and can become difficult to understand in the end. The exam is based on the problem sheet questions, so being able to solve these questions is key to scoring well in the exam. There is also a CW assignment over Christmas, which requires a solid understanding of the second part of the module, which has more demanding concepts. Manikas is a good lecturer, who wants to support students and is willing to answer questions, so it’s definitely worth asking him about concepts you do not understand (2020/2021).

All round an interesting course. If you are at all interested in Comms I would recommend, but don’t expect it to be easy. The concepts are difficult to get your head round and the CW and exam are both difficult, however the content is enjoyable. – Hamish, 2019/20

ELEC96009 – Control Engineering (Astolfi)

I agree with the other comments, the examples at the back of the book are brilliant. The book itself feels overwhelming so glance through it every once in a while and definitely use it for revision. There are some things explained in the book not explicitly covered in the lectures but are still examinable. For example: Dead beat controller/observer. Really useful module overall if picked with maths for signals and systems as they both complement each other a lot! You might have a tough time if you don't pick maths.(2020/21)

The book is quite remarkable, but unless you are a comfortable first class student it's very hard going. However, the 30 exercises at the back are brilliant and able practice. This year's exam was exceptionally difficult. Actually, the previous year's was very difficult too. Only take this module if you are ready to commit to it.(2020/21)

The book itself is quite daunting however for the content you definitely need Maths or do it in your ownste time. The exam is quite difficult hence only take it if you are committed to the module. The module is generally quite abstract and theoretical however covers a lot of content. So only take the module if you are ready to commit to it hardcore and actually interested in control.(2020/21)

Most people here tend to read the book, I prefer watching youtube lectures. Here are some useful channels: John Rossiter, megr438, Matthew Wright, Jonathan Sprinkle(more about self driving cars with control), MathDoctorBob, MATLAB (for filters), Steve Brunton (best one).(2020/21)

I wish someone had warned me that this course is about as far from second year control as you can imagine. That’s not to say it isn’t a good course but it’s very different. In contrast to second year control which is more about theoretical concepts that are interesting and hard to get your head round, the 3rd year course has very very little high level understanding element to it. You are simply required to process matrices effectively with very little understanding of why you are

actually doing it. Lecturer also speaks extremely quick and the notes I found were very irrelevant to the lectures and rarely used them. If you like exams that you can do well by doing papers and not having to understand what you are doing this is the one for you. – Hamish, 2019/20

Fantastic teaching! However, the textbook is a bit confusing, maybe some too theoretical proof can be ignored. - 2019/20

Scoring module - not sure how much practical knowledge you will gain, but it’s a safe bet to pull up your marks. Not exactly an easy module, but the notes and revision materials are good enough to pull you through. – 2019/20

If you like matrices then just straightforward bookwork – Tarik, 2019/20

Great lecturer, I found the combo of (actually) watching his lectures + reading the notes working. If you like the ‘understanding’ part more than the tons of theoritical knowledge you might like this course. However if you’re looking for a module where you can just learn stuff by heart maybe pick another one. - MG 2020/2

ELEC96010 – Digital Signal Processing (Stathaki)

Previously run by Patrick Naylor

Dr. Stathaki's slides are example rich and the exam draws entirely from the maths demonstrated in the slides. However, it's fair to say that this course is more theoretical and mathematical than in previous years.(2020/21)

The slides are quite detailed and extensive however the pace of the explanations can sometimes be long winded during the lectures however Dr Stathaki is always happy to help and explain anything if you didn't understand it. The modules is quite theoretical but gives you a good basis of DSP however be ready to commit to doing a lot of theoretical maths to be good at this module. The exam was entirely based on the lecture slides with some extension of concepts.(2020/21)

Dr Stathaki’s slides are detailed and contain loads of examples and thorough explanations. The lecturers can be boring because she sometimes devotes too much time to easier concepts, which leads to a slow pace. That said, she always happy to answer questions either in the lecture or via email (she’ll get back to

you in 24 hours usually). The exam was quite heavy mathematically, which means you need to practice effectively the math concepts she teaches. You should try to get access to the 2020 exam and to the sample exams she gave us because her style significantly differs from Naylor (2020/2021).

Very good module, one of the best lecturer in 3rd year, good teaching (2019/20: lecturer was Patrick Naylor)

Very charismatic lecturer, DSP is essentially an extension of signals, with fast fourier transform windowing etc. Lectures are understandable and exams manageable (ykw, 2019/20; lecturer was Patrick Naylor)

Super like Mr. Patrick who is a warm-hearted and enthusiastic professor. Your courses are perfect and no advice could be given to courses. If anything I have to say would be the exam. It may be better to add some concept understanding, rather than just mathematics, in the exam. (2019/20: lecturer was Patrick Naylor)

Interesting module, quite broad knowledge Exam is pretty challenging – 2019/20, lecturer: Naylor

Good lecturer – 2019/2020

Very well taught. Enjoyed it! – Kunal, 2019/20

Taught well, examiner can screw you over with unexpected questions – Tarik, 2019/20

ELEC96023 – Mathematics for Signals and Systems (Dragotti)

Get watching those Gil Strang YouTube vids early! That really made all the difference come exam time. There are a lot of shortcuts and tricks with linear algebra. If you try and use the slides alone you will fill a lot more pages and be prone to error.(2020/21)

The lectures don't cover much content compared to any other modules so do practice examples a lot. Hence I also suggest to get a linear algebra book to get more detail and learn the tricks of how to do things. The exam was allright in my opinion covers mostly what has been covered and there are quite a few past exam papers. This module is essential to quite a few others.(2020/21)

Do watch Gil Strang's lectures before the start of the term. He covers the course quite quickly, so it doesn't leave too much room to understand the material. In addition he tend to be more focused on the application of linear algebra, rather then the math. But this is third year, so there is the expectation that your math is pretty good. In sum do yourself a favour and spend two weeks prior to term watching Gil Strangs, so you can understand his lectures. Also for tls(not covered by Gil strangs) you might consider watching this video on youtube: Pillai "Ax= b, Least Squares (LS) & Total Least Squares (TLS)"(2020/21).

As everyone else has probably mentioned, start watching Gilbert Strang’s lecturers before the start of term and get the textbook (borrow it from the library- it has at least 10 copies). Dragotti’s slides do not help you pick up the techniques you need to solve linear algebra problems, because they focus more on applications. The way to do well is to study the techniques on your own using GIlbert’s resources, or anything else you may find useful, and then go over Dragotti’s slides to check understanding and learn how to tackle more application-oriented problems. Dragotti is quite happy to answer questions, so it is worth asking him if you’re stuck with anything (2020/21).

Please give him a bottle of champagne – 2019/20

Really good lecturer, excellent notes and very manageable content. I would say this subject required the least effort in terms of throughout the year and in exam period but is extremely useful for other subjects especially control. – Hamish, 2019/20

Awsome lecturer and splendid courses! One advice of the course could be related to the regression line. The regression line essentially is caegorised to full-column rank case. However in your orginal

teaching in 2019, it was used as a case study, which might be confusing as we learn more. The whole mathematics course esstially deals with the four types of matrices: invertible matrix, full-column rank matrix, full-row rank matrix and neither full-column nor full-row matrix. If you could have a general overview of them, it may be more clear to understand detailed mathematical technique under these four categories. Otherwise, sometimes if we focus too much on detail, we may lose ourselves – 2019/20

Awesome mod and lecturer! Essentially linear algebra and its applications, quite a bit of theorems to prove and understand, but everything is derived from each other so not much memory work involved. Prof Dragotti is very engaging and brings in a lot of applications for matrices like Google's page ranking algorithm, and DFTs. – ykw, 2019/20

General maths module - not too difficult but you need to keep up with the course material. – 2019/20

Very clear about the content. Helpful for learning matrix mathematics, worth taking. 2019/20

If you like matrices then just straightforward bookwork (alot of it though) – Tarik, 2019/20

ELEC96024 – Microwave Technology (Lucyszyn)

I personally didn't find the teaching too bad, it's just the exam expects you to be 100% and beyond in the subject and the preparation for the exam is just doing exam papers, there are no problem sheets or anything to ease you into the course. While they did try and help toy with the questions, the support wasn't that great to be honest. It's just an advanced course with too little time and little support. I would choose it if you covered it slightly beforehand or you would need to put a bit of work in during the term to get a decent grade out of the exam. If you prepare well enough it's not that bad. You just need to study elsewhere, as the lecture notes are not enough but unfortunately microwaves is one of those niche areas in EE. - 2020/21

ELEC96026 – Optoelectronics (Syms)

Slides are a bit heavy, a lot of maths and wave theory. Personally found it interesting. Exam is generally quite heavily based off of slides – 2020/21

Fields-2 in essence - though exam questions are admittedly harder – 2019/20

ELEC96017 – Electrical Energy Systems (Teng, Chaudhuri)

Well taught module. Dr. Chaudhuri really knows the ins and outs of Power Systems and explains it really well. Always ask questions after lectures if you have any doubts. Exam was easy because it was open-book this year.... if it wasn’t I probably would have done terribly because of the amount of formulas there are. - Z 2020/21

The material for us was split into two parts taught by separate lecturers. Both were brilliant at explaining everything and providing plenty of examples to practice and understand. Very equation and calculation heavy topics which can be beneficial or detrimental to you individually depending on if you a good with that. (2020/21)

Taught by two different lecturers, generally focused on power generation and transmission as well as some stuff on generators. Fairly tough but not too bad. Exams can vary – 2020/21

ELEC96031 – Machine Learning (Mikolajczyk, Gunduz)

Watch the Caltech lectures, they help a lot! The exam this year was quite challenging, but the module is interesting. I won't say it is taught in the best way possible and a lot of times, solutions given can be wrong, but this module has improved over previous years and hopefully it will improve even more. The phrasing of questions in exams is very weird sometimes and there is a chance you might not understand it. Overall, due to the lack of practice material, I will say this was one of my most underprepared exams! (2020/21)

Read through the Caltech lectures or any ML learning groups. Being remote asynchronous this term watching lectures on you own time with not the best explanations. The lecture does seem to be improved compared to the last years lectures. Get your linear algebra together because it will really help your understanding. The exam had weird phrasing and only having 2 past papers and some other examples which are not representative in terms of what they ask is though. The module content is interesting though. Get your report writing skills together because it takes long to type it into overleaf. (2020/21)

Caltech lectures will cover about 80% of the course (watch it before the term starts), they have started adding new content, good for the long run not for the exams. Again, here are some resources. Recomended channels: Ahmet Sacan, statquest(best), Victor Lavrenko, Naveen Kumar. Also, you don't really need to learn python, Matlab is good enough. Coursework requires minimal coding, you only need it to run routines so you can plot graphs, else you will need to do it by hand. (2020/21)

Cannot recommend the Caltech lectures enough, Abu-Mostafa is excellent at explaining content in an understandable way. The same cannot be said for the Imperial lecturers, though they do try. Course is mathematically very rigorous (doing Maths course will help), and to my disappointment there is essentially no practical element (very little coding) to it. The exam is also quite tough, more so due to the vagueness of the questions and the phrasing rather than the actual solution itself. Coursework is useful for the exam, for our year it was essentially the 2019 paper. (2020/21)

I’d say if you want to do well in this module, you cannot rely on lectures/lecture notes alone. The module is centred around ML theory and the maths behind it. It takes some effort to understand the topics discussed in the lectures. In the end, you need to figure out what additional resources work for you to help you understand. I found the Caltech lectures intriguing (although not adequately covering certain topics), as well as online articles (just googling specific ML topics). The GTA hours and the forum were a great help too. - Aaman 2020-21

Lectures were poorly delivered. Exam questions are weirdly worded and is easily misunderstood. Ultimately, you would have to go through a ML course if you are interested in working in any ML/DL field in the future so if this is your only choice, pick it. Supplement it with Caltech/MIT lectures if you find the lectures boring. - Z 2020/2021

Lecture notes is too hard to read some times, lots of maths symbol but lack of elaboration – 2019/20

Took this course for 3 weeks but hated it so much that I dropped it then. The lecture notes are awful and the lecturers are very poor. I am still interested in ML but will be coming at it from other directions like signal processing not this course. – Hamish, 2019/20

Based on Caltech MOOC Learning From Data, very mathematical, don't expect to do much coding. I think useful to learn to understand the statisical basis for why ML works and also how certain ML techniques like SVM, kmeans clustering work. Lectures might be a bit obscure at first but

referring to the MOOC helps a lot because the lecturer in the MOOC explains stuff more clearly and in a simpler way. Worth taking I feel. Exams are manageable, we had an interim coursework which was very useful for reinforcing what we have learnt. The RL part taught by Dr Gunduz was quite dense and difficult and not covered by the MOOC, so might take more effort. – ykw, 2019/20

Very theoretical - but a good precursor to deep learning. – 2019/20

good lecturers, nice instructions, very patient – 2019/20