Minors guide

Curriculum: 2024-2026Link to the minor's website

The Bioinformation Technology (BioIT) minor in English provides an introduction to various topics that are relevant in the field of bioinformatics and similar fields. Such topics include physiology and cell biology, biophysics, machine learning, statistical tests, electronic circuits, organic chemistry, and more. It should be noted that the minor in English is organized in a more hands-off fashion than other English minors, since some courses such as NBE-C2201 Physiology and ELEC-C8722 Molecular and Cell Biology are available in English, but only offer lectures in Finnish, thus requiring adequate time for self-learning.

Why should this minor be chosen and how does it support major studies?

The minor itself is fairly different from other ELEC curricula, but it serves as an interesting sidegrade from standard ELEC education and more common minors such as Computer Science. Courses from these fields are available in this minor, such as ELEC-C9600 Electronic Circuits and CS-C3240 Machine Learning, as well as the mathematics course MS-C1620 Statistical Inference. As such, the BioIT minor incorporates many concepts that should be familiar to most engineering students, while also introducing them to more minor-specific topics such as physiology, cell biology, and biophysics. If you’re considering a minor that blends familiar engineering topics with a unique focus on biology, then this minor might just be the one for you. I chose this minor for a few reasons: for one, I wanted a specific list of courses I could take for my remaining elective credits that would actively support each other, rather than choosing a bunch of random electives. This minor also serves as a nice pivot away from the curriculum of my major. There’s some overlap between the math courses I had to take and Statistical Inference, as well as some of the programming skills in my major and my other minor (Computer Science) being handy in Machine Learning and the R programming assignments in Statistical Inference. However, the biology, physiology, and biophysics courses in this minor are completely different from anything in my major or the CS minor, and I actually appreciate how different they are; I’m able to take courses on topics that are completely new to me, and which I find very interesting. Above all else, though, the Life Science Technologies master’s programmes look extremely interesting to me, and completing this minor is the only prerequisite for doing that master’s programme, so I at least have the option of doing that programme if I complete this minor.

What master's programs does the minor enable?

One of the biggest incentives for taking the BioIT minor is that it enables you to take the Life Science Technologies master’s programme, which contains six different study tracks. Most of these tracks contain several study paths of their own, and contain quite a bit of overlap in their first-year curricula. Certain tracks require certain courses to be taken in the minor during bachelor’s studies, with many of them requiring Machine Learning, for example.

• Bioinformatics & Digital Health (SCI) - focuses on data analytics, data science/CS, and machine learning in the context of working with biological data
• Biomedical Engineering (SCI) - focuses on physics, data science, and technology in the context of biological systems & medical technology
• Biosensing & Bioelectronics (ELEC) - focuses on electrical & material technologies used in biosensors and bioelectronics
• Biosystems & Biomaterials Engineering (CHEM) - adapts chemical engineering knowledge in the context of biological phenomena and material production
• Complex Systems (SCI) - focuses on mathematical computations and biological networks to concentrate on complex systems such as the human brain and various biological and social systems
• Human Neuroscience & Technology (SCI) - focuses on building a conceptual background for understanding the human brain and technologies associated with researching and analyzing it

What minor courses are recommended?

It should be noted that the English implementation of this minor requires the student to take NBE-C2103 Biophysics II: Light & Imaging, as opposed to NBE-C2101 Biophysics, which is only offered in Finnish. However, to my knowledge, the content of the two courses doesn’t overlap that much, and a baseline understanding of physics/mechanics should suffice as a prerequisite, along with first-year mathematics and programming skills. For the English-language implementation of the minor, I would recommend:

• CS-C3240 Machine learning - a prerequisite for several tracks of the Life Science Technologies master’s programme. Introduces ML programming in Python with Jupyter notebooks and offers practice with Pandas dataframes and other important packages. Only prerequisite is basic programming skills, and it only lasts one period.
• MS-C1620 Statistical Inference - a less math-heavy and more theory- and writing-heavy statistics course compared to the first-year probability and statistics course, less calculations and more programming and testing. Teaches students about various tests used in statistics, and assignments often consist of interpreting scenarios, running suitable tests and drawing conclusions from said scenarios. The first-year Introduction to probability and statistics course is a prerequisite, and basic programming knowledge helps as well when learning to use R.
• CHEM-C1220 Principles of General and Organic Chemistry - Haven’t taken this one, but it consists of basic laboratory work, writing and balancing chemical equations, and understanding reactions, bonds, and the periodic table. The only prerequisite is a lab safety course (either CHEM-A1010 or CHEM-E0140), and this course also only lasts one period.

Curriculum: 2024-2026Link to the minor's website

The Computer Science minor offers students a broad and versatile foundation in programming, algorithms, software development, and theoretical computer science. This minor is highly popular among students due to its strong applicability across various engineering fields. The following insights are compiled from multiple students to provide a comprehensive overview of the minor's benefits and course experiences.

Why should this minor be chosen and how does it support major studies?

Computer Science is an extremely versatile field that applies to nearly every engineering discipline. For students majoring in Digital Systems and Design, this minor provides deeper theoretical knowledge that complements mandatory courses such as Basic Course in C Programming, Object-Oriented Programming with C++, and Data Structures and Algorithms. Understanding the theoretical foundation behind these courses enhances comprehension and application in various engineering projects. Additionally, courses like Web Software Development and Machine Learning D offer practical perspectives that can be useful in future coursework and projects. The minor allows students to build strong programming and analytical skills, which are valuable across multiple domains of engineering and technology. I chose this minor because of its flexible practical applications and its connection with my Digital Systems and Design degree. Since my major already requires programming, embedded electronics, and signal processing courses, it made sense to deepen my knowledge in these areas. This minor has given me confidence in my future prospects, knowing that my skills are diverse and applicable in various engineering fields.

What master's programs does the minor enable?

The Computer Science minor is required for transferring into various majors within the Master's Programme in Computer, Communication and Information Sciences (CCIS). There is some implicit requirement as to which courses could be included, so check with the responsible professor for more detail. Specifically, it is a prerequisite for the following master's majors:

• Computer Science SCI-3042
• Human-Computer Interaction SCI-3097
• Machine Learning, Data Science and Artificial Intelligence SCI-3044
• Security and Cloud Computing SCI-3084
• Software and Service Engineering SCI-3043

What minor courses are recommended?

All of the courses listed on the minor program are recommended, depending on who you ask. Here are some insights from students who have taken courses within the Computer Science minor:

• CS-C3130 Information Security [I] One of my favorite courses in the minor. If you register for the lecture version of the course, you get access to a virtual machine (VM) to experiment with and complete weekly security exercises. The weekly exercises are very practical, allowing you to try real-world "hacking" techniques, such as brute-forcing passwords, creating malicious links to steal user passwords, and attempting buffer overflows on IoT devices. The course material is generally quite good, providing a solid foundation in Information Security. That being said, one thing I don’t really like about this course is that it’s quite hard to get a 5 since the exam is highly theoretical, and you need a solid understanding of all the material to achieve a top grade. However, because the exercises are incredibly cool, I still highly recommend taking this course.
• CS-C3120 Human-Computer Interaction [I-II] Human-Computer Interaction (HCI) is an introductory course that looks into how we interact with digital interfaces. It discusses a lot about how choices made by designers affect our day-to-day lives, and how HCI can be more broadly researched, measured and incorporated into our own design processes for any project. I personally enjoyed the reading assignments and open-ended exercises, which encouraged creative thinking. However, the exam felt too open-ended, and the grading could be quite subjective. I also wasn’t a fan of the lecture attendance bonuses, especially since I didn’t find the lectures particularly engaging. [Disagree with the above student] The exams were really easy and predictable. The open ended tasks were a bit of a pain and took the most time. Mandatory lectures are always a bit negative. On the other hand, from a content perspective, the guest lectures hosted by experts in respective fields were good, considering who they brought in.
• CS-A1155 Databases for Data Science [IV-V] This course covers relational database systems, specifically SQL, an essential skill in many tech fields today. The mandatory lectures weren’t great as they were taught by the inexperienced teaching assistants rather than by the lecturer, so learning didn’t really happen there. Instead, I’d recommend watching Introduction to Databases by Jennifer Widom (Stanford) on YouTube — it covers all the lecture topics clearly and helps with the weekly exercises. Aside from the exercises, there’s also a group project that applies databases to a real-world scenario, which was interesting. Overall, I’d recommend the course for the skills it teaches, but I wouldn’t rely on the lectures — using outside material is a must.
• CS-C2160 Theory of Computation [III-IV] This course covers fundamental mathematical models of computation, including finite automata, regular languages, context-free grammars, and Turing machines. These topics could be particularly interesting for those who enjoy logical problem solving. Every week, there is an opportunity to earn some bonus points by solving a few problems. While these exercises are of moderate difficulty and help reinforce your understanding of the material, you must attend the exercise sessions in person and be ready to present your solution to receive the bonus.
• CS-C3240 Machine Learning [I] This course introduces key machine learning topics, including supervised and unsupervised learning, feature engineering (PCA), deep learning, reinforcement learning, and language models. A strong math foundation (linear algebra, probability) is highly recommended before taking it. While some topics are covered too briefly, it serves as a solid introduction to ML. Taking Python for Engineers beforehand is also a good idea. The course consists of a group project (teams of two), peer review, and a short exam with 20 multiple-choice questions. The tricky part? The exam questions are randomized, with some highly specific, obscure details mixed in. Depending on your luck, you might have to retake the exam to get the grade you want.
• CS-C3140 Operating Systems [I-II] This course was revamped last year to use Scala instead of C. To be honest, I didn’t put much effort into it—I attended only one lecture and skipped the exercises. The course is highly theoretical, and the slides are overloaded with concepts, making it difficult to follow. Most coding assignments involve simple memory management, similar to the Basic Course in C Programming, but given that it’s only a 5-credit course, you shouldn’t expect to build a full operating system—that’s more of a final project-level task. The worst part for me was using Jupyter Lab, which was frustrating. As for the theoretical content, the slides cover a massive amount of concepts and terminology, making it hard to extract a clear structure just by reading them. I ended up learning by picking out keywords from the slides and assignments and searching for explanations on YouTube. I can’t comment much about the lecture quality since I barely attended, but from what I saw in the first session, it was mostly PowerPoint reading. If you’re just looking for general OS knowledge and don’t need this course on your transcript to prove anything, you can probably skip it.
• CS-E4580 Programming Parallel Computers D [V] This is one of the most challenging courses in the minor, requiring you to deeply understand how the CPU and memory interact with your data and how to apply clever optimizations to speed up computations. You’ll work with high-performance C and C++ code, optimize memory layouts, and even get your first hands-on experience with CUDA programming. The course features a leaderboard, where top performers receive a recommendation letter from the professor, exclusive patches, an excursion, and other perks. Personally, I didn’t make it to the top, but it was incredibly rewarding to optimize a program from 30 seconds down to 0.1s. It’s a master’s level course, highly demanding but completely fair—there’s no exam, and the grading is entirely transparent. If you enjoy C++ and are willing to put in the effort, a top grade is guaranteed.
• CS-C3100 Computer Graphics [I-II] Another very challenging but rewarding course I took during my studies. This course introduced me to 3D graphics from scratch, covering a wide array of essential topics, including modeling techniques, hierarchical modeling, physical simulation, ray-tracing, and real-time shading. A significant part of the course focused on modeling, such as curves and surfaces with splines and meshes, which gave me the tools to create complex 3D structures. Additionally, hierarchical modeling and physically-based simulations helped me understand how objects interact in dynamic environments. The course also covered ray-tracing and real-time shading, giving me valuable skills for creating realistic lighting and shadows in 3D scenes. However, it’s important to note that you need to be comfortable with C++ programming to succeed in this course. The assignments require a solid understanding of C++, and if you’re not already familiar with it, expect to spend extra time getting up to speed. Additionally, depending on your development environment, you may need to tweak CMake to get everything working properly before you can start the assignments. The course provides plenty of starter code and detailed instructions, but getting your setup right can sometimes be a bit tricky. One of the best parts of the course is the abundance of extra credit opportunities (could go way more than 200%). These points can actually be converted to cover your exam scores, so if you’re willing to go above and beyond, you can significantly boost your overall grade. However, keep in mind that there is still a minimum passing threshold required for both the assignments and the exams. On average, you’ll need around 10 hours of work per week, but the experience is totally worth it if you’re ready to dive into computer graphics and sharpen your programming skills.
• CS-C3150 Software Engineering [I-II] This course covers some of the most important general concepts in software development, but the workload is very high with weekly essays.

Curriculum: 2024-2026Link to the minor's website

The Mathematics minor offers great flexibility, where you are open to dive into either proof-based pure mathematics or more practical applications, depending on your interests. The math department provides a diverse selection of courses, which cover the three main areas of modern mathematics: algebra, analysis, and topology. If you find some of these courses appealing, the minor might be a perfect fit for you.

Why should this minor be chosen and how does it support major studies?

While many mandatory mathematics courses in our Digital Systems and Design program are computational, there’s often a gap in abstract understanding when certain concepts appear in major studies. For instance, topics like the Fourier Transform in Signals and Systems, Complex Variables in Electronics, and Advanced Linear Algebra in Photonics could benefit from a deeper mathematical foundation. Gaining a clearer understanding of these topics certainly helps build a solid foundation of the subject matter. I’ve always been interested in mathematics under the hood of many fields, especially in areas like Control Theory, Computer Graphics and Cryptography. Taking a course like Metric Spaces in the first year was definitely challenging, but I felt like I was discovering key pieces of a larger puzzle. Ultimately, strengthening my mathematical maturity has proven to be valuable, and it’s an experience that will only benefit me moving forward.

What master's programs does the minor enable?

While this minor doesn’t directly enable any specific master’s programs, it provides a strong foundation for those interested in pursuing the Master's Programme in Mathematics and Operations Research. Aalto students from the field of technology are all eligible for this program without additional prerequisites. However, having a more mathematical background will undoubtedly be beneficial for this advanced study.

• Master's Programme in Mathematics and Operations Research'

What minor courses are recommended?

• MS-C1541 Metric Spaces [III] This is an essential course for anyone wanting to get a true feel for what "real math" is like. Metric spaces give you a solid foundation in abstract mathematical thinking and help you understand more complex concepts in analysis. It’s a challenging course but incredibly rewarding for developing mathematical maturity.
• MS-A0311 Differential and Integral Calculus 3 [IV] While this course covers important topics, it hasn’t proven to be particularly useful for me just yet. However, it’s still a necessary step in building your mathematical knowledge and serves as a solid foundation for future studies in calculus and analysis.
• MS-A0402 Foundations of Discrete Mathematics [IV] This is a great course for anyone interested in studying algorithms or computer science. It covers fundamental topics like logic, sets, combinatorics, and graph theory, which are directly applicable to algorithm design and analysis.
• MS-C1342 Linear Algebra [V] Linear algebra is invaluable, especially for anyone interested in statistics, optimization, or control theory. It’s essential for many applications in engineering, machine learning, and data analysis. If you plan on diving into these areas, this course will provide a critical mathematical foundation.
• MS-C1300 Complex Analysis [II] Complex analysis is helpful for gaining a deeper understanding of complex numbers, but the course is very theoretical, with a lot of proofs that might be overwhelming for engineers. The exams can be quite challenging, and achieving a grade of 5 requires significant effort. However, it’s still a great subject if you’re looking for a deeper theoretical perspective.
• MS-C1081 Abstract Algebra [III] Abstract algebra serves as a gentle introduction to group theory, with a bit of ring and field theory. It’s an interesting course that helps you build the foundations of abstract thinking and is a great stepping stone for anyone planning to explore more advanced topics in mathematics.
• MS-C1650 Numerical Analysis [V] This course uses MATLAB and includes a learning diary instead of an exam, which makes it a bit less stressful. It’s best taken after completing a numerical methods course in engineering, as that provides useful context for the material. It’s a solid course to familiarize yourself with numerical techniques, though not particularly challenging in terms of exams.
• MS-C2105 Introduction to Optimization [IV] Optimization is a hit or miss depending on your interests. It was once an award-winning course with minimal prerequisites, but it’s been completely revamped and is now more advanced, requiring a solid understanding of linear algebra from the very beginning. The pace is very fast, so be prepared for a steep learning curve.
• MS-C1420 Fourier Analysis [I] This course is taught in Finnish, which made it difficult for me to follow without English materials. If future offerings include English resources, it would be a great complement to courses like Signals and Systems, which is already quite overwhelming on its own. The topic itself is interesting, especially for signal processing, but the language barrier can be a challenge.
• MS-E1542 General Topology D [IV] General topology is a good follow-up to Metric Spaces. It’s a fascinating exploration of abstract mathematical concepts, with all the materials available online. The exercise sessions are intensive, with a strong focus on 1-1 mentoring, which is great for personalized learning. However, the course can be quite demanding, so it’s not the easiest one to complete.

Curriculum: 2024-2026Link to the minor's website

If you are interested in antenna design, radars, satellites, space technology, or wireless communication—just a few of the many applications of microwave engineering—then this minor might interest you. The minor consists of various courses that cover electromagnetic phenomena and the fundamentals of transmission lines. Later on, the courses become more practical, allowing you to build your own radar and antenna.

Why should this minor be chosen and how does it support major studies?

I chose this minor because I was interested in learning more about antennas and their applications. I didn’t mind that most of the courses are master’s level or D courses. If anything, the professors teaching these courses are so good at what they do that I did not feel I struggled too much to learn and understand the concepts. After starting the courses, I discovered the realm of microwave engineering and its applications and became very interested in it. I am particularly eager to learn about space science and technology, as these fields have been an interest of mine for a long time. There, RF engineering has multiple applications, so it only made sense that I focus on this path.

What master's programs does the minor enable?

The minor is not a prerequisite for any master’s program. In fact, it is one of the study paths within the Electronics and Nanotechnology Master’s Program. However, the knowledge gained from this minor can benefit any of the other study paths in the Electronics and Nanotechnology Master’s Program or the Automation and Electrical Engineering Master’s Program.

What minor courses are recommended?

These are all the courses that I have completed, am currently completing, or have attempted at the time of writing. The remaining courses can be found through the minor’s link and SISU, as I cannot provide additional information beyond what is available there. This minor information will be updated again next year when I have completed more courses. However, I can confidently say that the workshop courses will likely remain among the best.

• ELEC-D9420 Basics of RF Technology [I-II] This course is mandatory and provides an introduction to transmission lines and antenna theory. You also learn to use AWR Microwave Office software and design impedance matching circuits. The course has a very long list of prerequisites, but I managed just fine with the math courses from the DSD major, an electronics circuit course, and some electromagnetic field knowledge I studied on my own. In my opinion, the course does not focus much on these topics. The professors are also very clear and knowledgeable in all respects. I enjoyed the lectures and understood a lot just from being there.
• ELEC-E9430 Microwave Engineering D [IV-V] This is the next course, in which you learn how to design passive and active components. In the first six weeks of the course, you learn about these components. In the last six, you design a Doppler radar and can use the designs from the first six weeks to accomplish this task. This course feels less demanding in terms of workload compared to the Basics of RF Technology course.
• ELEC-E9450 Antennas and Wave Propagation D [IV-V] The name accurately describes the contents of the course. Most of the course covers different types of antennas. The first two lectures focus on electromagnetic radiation, while the last three cover propagation. The electromagnetic radiation part is somewhat heavier on math, requiring vector calculus (Differential and Integral Calculus 3). Compared to Basics of RF Technology, this course includes some mathematical calculations, but nothing too challenging. The professors explain the concepts and mathematics in great detail, which is helpful if you have not taken Calculus 3 (like me) and only have a basic understanding of electromagnetic field theory. The main point is not to be intimidated by the math—you will spend much more time in AWR adjusting capacitor and inductor values than working on mathematical calculations.
• ELEC-E4410 Electromagnetic and circuit simulations [III] This course is highly interesting and practical. You will gain more experience with AWR and learn to use COMSOL and CST. These tools are essential if you plan to pursue a career in microwave engineering. However, the course is quite demanding, and the assignments are time-consuming. It is a 5-credit course in period 3, so if you are very busy with other courses, it may be better to take this one in a later year or at another time. The assignments require significant time and effort, and you may need assistance since the software can sometimes be uncooperative. Still, mastering these tools is essential.
• ELEC-D9130 Electromagnetic fields [I-II] Interesting but very difficult. I highly recommend taking Calculus 3 before this course, as it heavily relies on mathematics and is highly theoretical. I also suggest checking SISU and MyCourses for past implementations of the course to assess whether it aligns with your interests and whether it is manageable, as it is quite challenging, and the homework assignments can be demanding. When we took it, the TAs had some problems in setting the right difficulty for the final exams. However, Calculus 3 is not strictly required, even if it is listed as a prerequisite.
• ELEC-E3120 Analysis and Design of Electronic Circuits [I-II] This course was also among the more challenging ones. There were several lab sessions that were engaging and provided valuable practical knowledge. Prior knowledge of circuit theory is not required, but keep in mind that the course moves at a fast pace. Even though it is listed as a prerequisite, it is not essential for taking any of the first four courses mentioned earlier.

Curriculum: 2024-2026Link to the minor's website

I'm taking the Space Science and Technology Minor. So far it has been amazing, the courses from this minor have been my favorite courses out of all including my major.

Why should this minor be chosen and how does it support major studies?

I really recommend doing this minor and being more involved in space in general. There is a satellite group working on a cubesat, there's me doing an actual association, and there's many events in general and possibilities.

What master's programs does the minor enable?

What minor courses are recommended?

As soon as one can, take the ELEC-A4930 Astronomical View of the World [III-IV]. It's a wonderful elective that gives a great perspective on how to look at space in general. I've done basically that course and half the minor now and still Astronomical View of the World is my favorite course. Then, don't be afraid to take the other courses as well very soon, in order as presented. I chose these because they seemed most interesting. They are usually a bit challenging, but not if you like what you are doing. I found them to be pretty easy courses (only done AVoW, Intro to Space and Space Instrumentation so far) and I am generally not a smart person. The course quality is the best I have seen. I don't think any of my normal courses come as close to the quality and structure.

• ELEC-E4210 Intro to Space [I-II] This course is, as suggested by the title, an Introduction to Space. Not in the same sense as the AVoW, but goes in more deep into the details and the physics of space. It still covers a wide range of topics though: Orbits, Plasma Physics, Observation time calculations and the coordinate system of the earth, Blackbody radiation (what brightness means, flux density, etc.). It is overall a course with a very balanced workload and a pretty easy exam. During the course you have a few homework assignments and pre work for them. It is very fun in my opinion and it also helps a lot with future courses, however it is NOT necessary to do before the next courses (the ones below this one).
• ELEC-E4220 Space Instrumentation [I-II] This course is a doctoral level course (apparently) where you take a deep dive into the physics behind the instruments on famous satellites. The first part of the course, you will examine lots of instruments and have homework about explaining how they work. The second part you will take a look into space missions and how they are designed, and you will work on designing your own space mission! This is a big part of the grade in this course and requires you to be in teams. There is no exam, and the workload I think is fairly easy.
• ELEC-E4530 Radio Astronomy [III-IV] Radio Astronomy my beloved. This course is an insanely cool course. You will examine how Radio Astronomy in general is carried out, what you observe, how you observe it, and how to calculate when to observe. Introduction to Space will help you a lot here, but they do take into account people who have not done that course and give you good resources. The whole course you go very deeply into what types of observation techniques exist, how Metsähovi works and how they observe, what instruments and receivers they use, etc. Then you also get to go to Metsähovi! They prepare very cool exercises for that trip, and afterwards you have some practice sessions on Fridays (approx every 2 weeks) which are similar very fun exercises. The grading is a bit different, since you do not have homework per say, but you have to write reports about the practice sessions and do some calculations there. There are a total of 3 reports to be written. Then, in my opinion the coolest exercise session is actually going to Metsähovi and doing a 12 hour observing session in groups. You actually get to do what the professors do when they do observation, it is amazing that they can let us do this! There is an exam at the end of the course but it is very easy.
• ELEC-E4520 Space Physics [IV-V] As the name suggests, this is purely a physics course going into space physics. I have just started this one so I cannot say much about it. From first glance it seems pretty in depth and hence more difficult. It does have a great structure though. It has weekly homeworks and an end exam.
• ELEC-E4240 Satellite Systems [IV-V] This is a super interesting, more hands-on course held by an amazing professor called Jaan Praks. It teaches you about the whole process of creating the satellite, from the initial mission concept and goal, to the launch. It also has weekly different topics like moon instrumentation techniques and how to think about space science missions. It has simple weekly (or sometimes 2 weeks) assignments and the main grade is on the projects of the course, which is making your own in depth cubesat mission for the moon (the topic for my year). It has no exams because of this, but the documentation for the project is pretty long and in-depth, so you have to put in quite a few hours. Luckily it is teamwork, with 4 person teams.
• and others that you may choose