Recap: Women In Data Tech Panel

On March 29th, McWiCS had the pleasure of hosting a Women in Data Panel where students got the chance to hear from data analysts and recruiters from top companies such as Ubisoft, CGI, Psycho Bunny, McKinsey & Company, Autodesk, Unito, OROHealth, and Le Wagon. Panelists shared their experiences as data analysts within their respective companies, and recruiters offered advice to students interested in immersing themselves in the field.

Here's what they had to say.

1) What does a day on the job look like?

A key task the panelists have to deal with everday is prioritization. Prioritizing tasks is key to supporting the team and helping the company as a whole. Weekly tasks are sorted and tackled according to urgency. There are also many questions on what the key performance indicators of data analysis should be and what the best metrics to evaluate this performance should include. The panelists' job entails coming up with metrics to relate qualitative and quantitative data and supporting other team members in analyzing their data. As such, some days are packed with attending several meetings with other team leads and project managers to process the data coming in, identify its source, and make it easy to work with using any kind of data analysis tool. Panelists expressed how fun it is to work with developers as well as the many different teams within the company. Interacting with diverse groups of people from many different fields was an unexpected part of the day-to-day job, and the ability to adapt quickly is key. Panelists advised students to consider whether or not they would enjoy this. Last but not least, free alcohol on Fridays was also cited as one of their favorite parts on the job :)

2) What was an important learning moment for you?

A significant lesson panelists learned from their job was the need to be detail-oriented and ask the right questions: Where is this data coming in from? What does it imply? How can we explore these questions deeply enough to not jump into conclusions and be as unbiased as possible in our analysis? A critical eye is especially important as these women are usually working alongside people from different teams who may not be specialized in data analysis.

Another thing they learned, and this is something no one tells you when you are in school, is that if you are aiming for something, you have to go get it. You must figure things out on your own because in the real world, things are not served to you like they are in school. Be proactive! Approach people and expand your network to learn from them and ask questions.

In addition, panelists urged students to follow the ever-changing trends in the market. Develop a growth mindset. In that regard, take the time to rewrite your resume yearly and ask yourself: What aspect of your skillset do you want to sell to the company? What have you learned? You need to develop close connections with your bosses and peers; you will not have a great career by doing everything on your own. (Answer is recruiter-approved).

On a different note, one piece of advice was to always check your own biases. If something feels off, speak up. Often, the panelists find themselves in big teams, so if they do not speak up about something, it will get overlooked. They way they use the data available to them and analyze it can have huge, far-reaching impacts on many people. This is why it is extra important to listen to their intuition when something feels wrong.

3) What are the soft skills you look for in a candidate, and how do you assess them?

Recruiters stressed the importance of soft skills even in a technical role. They already know that all candidates come in with a very good technical toolbox, so soft skills will set you apart. They are looking for people who can articulate their approach to how they work within a company. They want someone who can communicate clearly with many different people from many different teams (technical or not). In terms of how these skills are assessed, they indicated that the interview process helps them determine how good of a fit a candidate might be. Candidates are expected to come to the interview prepared and well-researched. Research must be done not only on the company but also on the job itself. Panelists advised students to ping people on LinkedIn to learn more about a specific role. A learner's mindset is also very important as candidates are expected to not be afraid to tackle challenging problems that have no ready-made solution. Demonstrating an ability to think on your feet is therefore a must.

Recruiters also like to hear feedback from candidates and have them show their true colors. They enjoy hearing about what candidates are passionate about in specific and what they truly think of the job/internship not just generic feedback that makes the candidate seem bland.

4) Are soft skills only measured during the interview process or via a candidate's resume as well?

The general consensus was that soft skills are a bit hard to measure just by looking at a resume, and the interview portion is usually where these skills should shine. Recruiters want candidates to not be afraid to sell themselves. They want to get to know the candidate and their side projects as much as possible. In addition to that, at CGI, candidates are usually placed in teams for recruiters to gauge how well they can take charge and act as the leaders of the group as well as what they can bring to the table, not in terms of technical knowledge, but in terms of leadership skills and enthusiasm.

A product manager pitched in and asserted that one can learn a lot about candidates from their CV. Have you participated in hackathons? Have you taken part in extracurricular activities beyond the classroom? The panelists agreed that they usually love to see well-roundedness and curiosity across many diverse fields, not just tech.

5) Students have so many options in terms of the courses they can take and the clubs they can join. What are the most important courses/clubs/extracurriculars for students to boost their resumes?

The panelists generally agreed that the answer varies depending on the role that the candidate is applying for. For data analysis specifically, recruiters generally assume basic knowledge in statistics and data visualization. The latter is important to be able to communicate results clearly and intuitively to non-specialists within the team. Summarizing the main ideas and condensing the details is necessary for effective communication. Panelists also recommended doing further, self-directed learning through online courses or books (O'Reilly books for example) and focus on skills that can be applied to the real world.

6) Based on your personal experiences, do the college classes students choose to take matter for what they work on later?

Panelists emphasized that projects were more significant than courses in helping them navigate their careers. They suggested that students explore different roles (managerial, technical…) within a project to see what they like best. One could be a business analyst and talk to stakeholders, or be the data analyst in the team, or be in charge of UI/UX design... From there, one can discover their strengths and passions and pick their courses accordingly. In addition, when applying for internships or jobs, candidates should highlight their side projects on their GitHub. If you are aiming to work for a specific company whose work interests you the most, you should complete projects relevant to the company's goals and mention these projects in your cover letters. This will set you apart from the average applicant.

7) What are the difficulties in searching for data analysis roles as a woman? How do you deal with microaggressions?

There is a certain hype around AI and ML, and there are great advantages to that. However, data analysis is seen as less technical. One panelist had colleagues who viewed themselves as superior because they were AI/ML specialists while she was not. In reality, though, every technical role is important and adds a lot of value to a company.

As a woman in general, in some companies, it is harder to find equal footing. There sadly still exist many employees who hold on to outdated stereotypes that can make women feel unwelcome within the companies they work for. Instead of immediately quitting a company because of a discriminatory experience, however, panelists encourage women to speak up to a trusted person within the company to raise awareness about the microaggression faced. More often than not, the company is very receptive to that. People nowadays are open to these issues when they are brought up from the right angle. Change can and does happen even though it may take a while.

Other panelists asserted that the easiest and best way to prove yourself is to simply be unafraid to do incredible work and show your abilities.

Another thing that helps when dealing with microaggressions is to count on each other as a community. Panelists often discuss these issues with women from several different fields and find that their experiences are quite the same across the board.

Furthermore, there is much talk about stereotypes that other people have, but how you view yourself is equally important. Women tend to hold themselves back. Imposter syndrome is more prevalent in women than in men. If you know something, show it. You don't have to be at the top of the top. Women don't put their foot in the door unless they have all the skills required for a job, but it's okay not to know everything and still put yourself out there. If you think you can acquire the skills and learn, show that.

Maxine from Mckinsey & Co relayed her experience of when she wanted to help out on a cool data project. When someone she approached told her that she did not have a certain skill she needed to be able to do the job, her immediate response was that she could just go ahead and learn it. “Have confidence. The worst case scenario is that you get rejected, but that is not end of the world.”

5 Women in AI you May not Have Heard of

Artificial intelligence is a booming field. Right now, more than ever, we need the participation of women to keep up with the field’s rapid advancements. Otherwise, we risk having bias seep into the algorithms we design and the products we sell. In North America, for instance, women accounted for 22 percent of all AI and computer science PhD programs in 2019, just 4 percent higher than in 2010. Progress is still slow globally, but tangible change can be seen already, especially here at McGill. Let’s get to know 5 more women (among so many others) who continue to make their mark on the field.

Bias in Machine Learning. Read more here

Rana el Kaliouby

Rana el Kaliouby is an Egyptian-American computer scientist and entrepreneur inspired by her mother who was one of the first female computer programmers in the Middle East.

El Kaliouby realized the “emotional blindness” of our virtual worlds and strove to create more human-centric technology. This propelled her to co-found Affectiva: pioneer in the field of Emotion AI which analyzes users’ facial expressions and interactions with the objects around them along with other contextual clues to make conclusions about the inner cognitive and emotional states of humans. Her products aim to harness the power of machine learning and computer vision to design more emotionally intelligent products, such as a perceptive smart phone capable of catching early warning signs of anxiety or depression, or automotive AI to catch a driver falling asleep at the wheel. Applications of Affectiva's AI include healthcare and mental health, robotics, conversational interfaces, education, gaming, and more.

Dr. Rana el Kaliouby: AI Thought leader. Machine Learning Scientist. Deputy CEO at Smart Eye. Former Co-Founder and CEO of Affectiva. Author of the book “Girl Decoded.” Disrupting industries and humanizing technology with Emotion AI

“You don't have to be a genius to be a scientist, but you do need to be persistent.”

/*Also, do check out this gem of a podcast between Rana and Lex in which they discuss everything from women in the MENA region to mangos to emotionally intelligent robotics.*/

Poppy Gustafsson

Poppy Gustafsson founded Darktrace at 30 years old in 2013. At the time, she and her colleagues were leading a research team of mathematicians from Cambridge as well as AI experts. From there, Darktrace was born. Her cyber-AI company leverages the power of mathematics to enable AI to autonomously defend organizations from cyber-attacks including ransomware, email phishing, and threats to cloud environments. The key insight that led to Darktrace’s inception was that efforts aimed at uncovering the ever-changing and evolving techniques that hackers use to breach an organization’s security was just not possible nor efficient. Instead, organizations should learn the ins and outs of their own normal, day-to-day network activity and from that, they can then spot unusual anomalies that may signal suspicious malicious activity. Today, Darktrace’s AI is capable of spotting sophisticated attacks as they happen in real-time and fight back instantaneously on behalf of humans. Darktrace’s R&D team have also made it possible for their AI to interrogate its own findings: instead of humans manually “checking its work,” AI is now taking care of this too.

“We are already used to the idea of AI recommending what to watch on Netflix based on our personal preferences — in security, it will become completely commonplace for AI to be recommending what action to take in response to its own investigations into a cyber-attack. In many cases, the action will be taken without the human in the loop. Time is rarely on your side when dealing with computer-driven attacks, and action usually needs to be instantaneous to prevent the breach or damage. For us this is just scratching the surface — we see a future where even higher-level thought processes like red teaming and cyber risk analysis could be executed by AI. The sky is the limit!”

Maha Achour

Co-founder and CEO, Maha Achour founded Metawave in 2017. Metawave develops long range and high resolution imaging (arguably the very hardest problem in automotive radar) SPEKTRA radar technology which can perform real-time object classification for the purposes of safer autonomous driving in all weather conditions. Armed with a Physics background, Achour leveraged the science of beamsteering technology: a technique that focuses a narrow, wireless signal towards a specific target receiver rather than have the signal spread in all directions as a usual, less precise broadcast antenna would. (This technique is also behind the success of 5G technology). In 2020, achieving this feat was the first of its kind. Metawave also has its own AI (AWARE) platform, making the company a fusion between AI/ML and their revolutionary sensing technology. They are able to use the latest advancements in deep learning in the hopes of making autonomous driving safer. Achour also holds over 450 pending and issued patents and has over 20 years of experience in the radio frequency, wireless, optics and networking industries.

“Don’t search for opportunities - instead observe, learn, and dare to ask the first simple question.”

Joumana Ghosn

Ghosn was a master’s student in computer science at the University of Montreal when she met Yoshua Bengio. She dabbled with computer vision and machine learning and eventually ended up pursuing a PhD program back in 2002 under Bengio’s supervision as one of only 3 women on the team. She is now a researcher in applied machine learning at Mila. She has developed an expertise in natural language understanding, specifically at Nuance Communications, where she worked with a team of deep learning researchers to create virtual assistants and computer-assisted clinical documentation improvements.

“I believe that women must have confidence in their abilities to advance within an organization. When I look back on my career, I have been fortunate enough to hold management positions that interested me and suited my abilities. I realize, however, that I never sought my promotions. They came my way and I was happy with them, but I realize that I could have been more assertive. I believe that many women have the same reflex as me and are reluctant to talk about their ambitions and wait for opportunities to be offered to them. We need to teach women to take more calculated risks, to put themselves forward professionally. Fighting for the best job opportunities and conditions is a value that is instilled in men very early on. We should do the same for women.”

Fei Fei Li

Li is a Chinese-American computer scientist and professor at Stanford University who is well-known for her work in establishing ImageNet: an object classification dataset that enabled the revolutionary advancements in computer vision of the past decade. Her research interests include cognitively inspired AI, machine learning, deep learning, computer vision and AI in healthcare especially ambient intelligent systems for healthcare delivery. In the past she has also worked on cognitive and computational neuroscience. She is also cofounder of AI4ALL, a nonprofit that aims to increase diversity and inclusion in AI education, research, development and policy.

“The real existential challenge is to live up to your fullest potential, along with living up to your intense sense of responsibility and to be honest to yourself about what you want.”

F is for Failure (but also for Fantastic)

No one likes to see it on their transcript. It’s the F word: Failure.

In her 2016 TED Talk Teach girls bravery, not perfection, founder of Girls Who Code Reshma Saujani calls us out on how we raise our girls to fear failure and risk.

It’s that time of the year again: midterm season. With it comes a resurgence of a crippling fear we all have: the fear of failure. For one reason or another, we have been programmed to always hold ourselves to impossible, almost superhuman standards of success and productivity (I blame capitalism). We have been conditioned to squirm at even just the thought of failing an exam or experiencing any other abstract sense of failure. And the scariest (no pun intended) part of it all, is that we do not see any problem in our aversion to failure. We have internalized the idea that failure is inherently a bad thing to the point where we do not even stop to question this perception. So, I’m here to do just that: I urge you to pause and reflect on whether failure can be a good thing. Not only that, I challenge you to start celebrating your failures just like you do your successes. Here’s why.

In what follows, I attempt to mathematically “prove” that failure = success.

Lemma 1: Failure is inevitable.

The fact of the matter is that failure is inevitable. No matter how much you think you can escape it, and no matter how many unhealthy habits (consuming insane amounts of caffeine to stay awake long enough to get your assignment in on time, sacrificing sleep to cram for next day’s midterm, procrastinating as a form of coping…) you adopt to avoid it, you can never outrun it. Let’s face it: university is TOUGH. McGill is TOUGH. CS programs are TOUGH.

But you too are tough. (OK no I would never say something cheesy like that).

You will inevitably fall behind. You will inevitably fail a midterm. You will inevitably fail at landing that internship or research position you so wanted. It’s just the way it is. It’s by design. Failure is inevitable because we take ambitious risks and try new and unfamiliar things for the very first time; we challenge ourselves beyond our current ability level and do difficult things we never did before. What happens when we try to ride a bike for the first time after having only ever ridden a tricycle? We fall flat on our faces. Or our bums. Analogously, what happens when you try to do something you haven’t done before? You fail. And that is simply because you couldn’t have possibly succeeded.

What we fail (I swear no pun intended) to realize is that failure is a necessary stepping stone to success. You cannot reach the other side if you do not go through it. It is such a natural and necessary part of the process that leads to success. I know it may not seem like that to you considering how everyone nowadays tries so hard to present themselves as perfect, accomplished people who never struggled to get to where they are or to earn that 4.0 GPA. You might think there are people who just never fail and always seem to succeed at whatever they try. But that is not reality.

When successful people look back on their time at university, they too find a journey fraught with failure, tears, sleepless nights, imposter syndrome… At that point in their lives, none of them could imagine themselves as successful people in the future. Do you see where I’m going with this? You might be struggling now to see any light at the end of the tunnel. But it’s precisely because you haven’t yet reached the end of the tunnel.

Lemma 2: The more frequently you fail, the higher the rate of approaching success, the more probable success becomes.

Now that we’re convinced that failure is inevitable (see Lemma 1), we note that failing multiple times is even better than failing once.

Each time you fail, you get infinitesimally closer to success. It goes without saying that you get considerably close to success if you fail a considerable number of times. Every time you fail you learn what does NOT work. Failing is valuable because it provides insight into what you’re doing wrong. Once you learn what does not work, you pinpoint your mistakes, work on how to rectify them, and figure out what DOES work. The best way to succeed is to fail lots and lots of times. Linus Pauling’s got my back on this one:

Now we are ready to confidently state our conclusion:

Theorem: Failure leads to success.

No like, seriously - I proved it.

Totally NOT what I just did in this blog post.

In conclusion, failure is fantastic. Viewing failure in a positive light requires a major paradigm shift. You must acknowledge that while the feeling of failure is fleetingly painful or unpleasant in the present moment, it will be instrumental in your eventual success. Trust the process! Also, remember to transparently and shamelessly share your failures with others. Due to embarrassment, we tend to hide the fact that we fail at ten times the rate we succeed. This will only create a vicious feedback loop whereby everyone lives their life thinking they are the only ones who are failing and that everyone else succeeds effortlessly. As a result, people abandon their pursuits thinking that their failures are a sign that they will never succeed. It is only when we all dare to share our failures that we may all attain the success we strive for.

Meet the Profs

It can be hard to build meaningful rapport with your professors when you’re in huge, crowded computer science lectures. Or maybe you’d like to conduct interesting research alongside an inspirational professor in the department yet don’t know how to approach them. McWiCS has got you covered! On Tuesday, January 31st, 2023, McWiCS held its biannual Meet the Profs event! This is a great opportunity for you to meet other students, get to know your professors one-on-one, ask them about available research opportunities they know of, receive insider tips on how to do well in their courses, or just chat!

Here are the professors who were at this semester’s Meet & Greet:

Prof. Brigitte Pientka

Courses Taught: COMP 302 Programming Languages and Paradigms (Past), COMP 523 Language-Based Security (Past), COMP 527 Logic and Computation
Research Interests: Logic and computation, programming language theory, safe and reliable software systems
Website

Prof. Bettina Kemme

Courses Taught: COMP 512 Distributed Systems, COMP 421 Database Systems
Research Interests: Design and development of distributed information systems, in-database analytics, performance monitoring in the cloud, and software design for micro-architecture. Detailed information can be found at the webpage of the Distributed Information Systems Group

Prof. Giulia Alberini

Courses Taught: COMP 202 Foundations of Programming (Past), COMP 250 Introduction to Computer Science, COMP 251 Algorithms and Data Structures
Research Interests: Cryptography

Prof. Faten M’hiri

Courses Taught: Comp 202 Foundations of Programming, COMP 208 Computer Programming for Physical Sciences and Engineering, COMP 396 Undergraduate Research Project, COMP 400 Project in Computer Science, COMP 480 Independent Studies in Computer Science
Research Interests: Machine learning, medical imaging, healthcare technologies, image analysis, teaching and learning methodologies

Prof. Lili Wei

Courses Taught: ECSE 688 Recent Advances in Electrical Engineering 1 (Past)
Research Interests: Software analysis, testing, and mining code repositories with a focus on Android applications, smart contracts and IoT software
Website

Prof. Mona Elsaadawy

Courses Taught: COMP 273 Introduction to Computer Systems, COMP 421 Database Systems
Research Interests: Database systems, field intelligent networks, software-defined networking (SDN), network function virtualization (NFV), cloud computing, clustering techniques and network security

We hope to see you at future iterations of our Meet & Greet 😊

How to Hack your First Hackathon

As you all should know by now, McWiCS is organizing a hybrid hackathon on the weekend of February 4-5, 2023 at Mila – Quebec AI Institute (yes, you read that right!!!). Mila is one of the leading research hubs for advancing Artificial Intelligence technologies. In other words: super cool place. If you haven’t signed up yet, what are you waiting for? Here is the form to apply.

“But I’m busy that weekend.” “I don’t know anyone who’s participating.” “I am inexperienced and will therefore have no idea what the hell I’m doing.” Ah, yes. Excuses, excuses.

Below, I lay out the most common fears that participants (especially first-time hackers) have surrounding hackathons and how best to address them.

1. “I am still a beginner coder/don’t even know how to code/have never been to a hackathon before.”

With hackathons - as with everything in life - there has to be a scary first time. If I can't convince you, might Leo?

Congratulations! You fit the requirements to participate. While it may seem counterintuitive, inexperienced coders are the target demographic for hackathons. If you’re just starting out your degree or computer science journey, you’ve come to the right place. A cool thing about hackathons is that anyone who partakes in them will be able to walk away having learnt something. And if you think about it, the less you already know the more you will be able to learn! Small coding workshops as well as enthusiastic mentors will be present at the event to assist you in getting started. Besides, if I may fill you in on a little secret, you’d be surprised how many hackathon projects have very little code in them. It is simply inconceivable to create the next PayPal or Facebook in the span of 24 hours. So, how do hackathon projects seem so professional and ingenious if very little coding goes into producing them? The answer is a whole bunch of APIs, libraries, frameworks, open-source code, among others. The very best hackers find prewritten chunks of code that they can reuse and implement them into their projects to save time rather than code all these up from scratch. This is not cheating! It is the very thing that has kept hackathons alive and well for years. Just make sure to give credit where credit it due.

2. “None of my friends or people I know are participating.”

That’s completely okay! It may seem intimidating going to an event not knowing anyone and having to team up with strangers to ideate and create a huge project in just 24 hours. But don’t forget that McWiCS will help in handling team formation and matching you with other solo hackers. That said, don’t be afraid of reaching out to people and asking them if they’d like to team up. You’d be surprised how many of them are in the exact same position as you and are also anxious about going. In addition, hackathons are much more than a competition: hackathons are a social event (I know; who knew programmers were social beings?!). They exist for people with a shared love of tech to get to know one another, form connections, and network. They are a great way to play around with code, meet interesting people, and make new friends. If you think about it, it’s pretty cool to watch friendships blossom out of collective, panic-ridden experiences: just like hackathons. In fact, there’s a whole science behind how oxytocin - a social bonding hormone - is released during times of stress and panic. So even if you lose the hackathon, you’re almost guaranteed to win a friend!

3. “I’m not creative enough/have no new idea for a project.”

Have you tried looking here for inspiration from the projects created by last year’s Hack McWiCS participants? What about here? You could also look at other hackathons’ Devpost pages (HackTheNorth, McHacks…)  for even more inspiration and ideas. Brainstorming with your team prior to the hackathon is also a great way to gain a head start. Moreover, at the end of the day, creativity is a team effort. Having multiple people from diverse backgrounds, fields of study, and coding abilities on your team is a sure-fire way to come up with a “creative” idea. I would also suggest not getting so caught up in finding that one unique “WOW” idea for a project because chances are that the big app idea you came up with in the shower already exists. Instead, you must realize that the projects that end up winning hackathons are really simple and trivial and will make you think “How come I didn’t think of that?!”. What sets them apart is their usefulness, functionality, and polished execution.

4. “What if I don’t finish my hack/don’t want to present my project?”

Not finishing a hackathon project is much more common than you think. Just focus on getting an MVP (minimum viable product) to showcase to the hackathon organizers as they stop by to hear your pitch. It is also completely fine if you do not even end up with a working project due to some major bugs in your code or any other hurdles. Everyone will still be interested in hearing about your idea, the challenges you faced, what you learned, what you tried…etc. There is no reason to be intimidated by the presentation portion: no one is expecting you to be an expert.

In conclusion, while attending your first hackathon can be daunting and anxiety-inducing, rest assured that feeling this way is by design and that countless others have been in your shoes. In addition to all the “hacks” above - and this is not some cliché advice - make sure to make having fun and learning your top priorities. The unpleasant reality is that most hackers (beginner or not) do not win. It sucks to think about it, but you are inevitably (at least from a statistical perspective) doomed to lose before you even begin. This is not meant to crush spirits, but what I am trying to convey is that if you make winning your motivator, you are, ironically, setting yourself up for failure. If, however, you make learning your motivator, you will not walk away disappointed. You really will gain more practical skills in one hackathon than in a semester’s worth of lectures. Lastly, pause for a moment and reflect on how ridiculous it is to be afraid of hackathons. Out of all the terrifying things in this world: spiders, bears, the possibility that we humans may be alone (or NOT!) in the universe, the first people to walk out of the exam room…etc., you chose to be afraid of social coding events filled with free food and fun activities? *Eye roll*

So, if you were hesitant about signing up for Hack McWiCS or any other hackathon, remember that you have nothing to lose and everything to gain! Best of luck to all our hackers!

TL; DR: APPLY NOW TO HACK McWiCS!

Harsh Truths About Majoring in Computer Science

Alright, moment of truth.

We're all aware on how computer science is gaining popularity as a college major, and especially in the tech industry. It seems like everyone’s in CS programs nowadays: whether people are passionate about it, have built the next Uber before even being born or are just in it for the money, there are some things about being in Computer Science that not a lot of outsiders are aware of.

Now, the semester’s just started, and this blog post by no means aims to discourage you or scare you away from CS, for it is truly a beautiful subject to dive deep into. However, here are some things you should keep in mind.

1. Math: there’s a lot of it

You read that right, brace yourself for the heavy math course load. Computer Science is built upon logical thinking and computation so it makes perfect sense that you’ll have to take quite a bit of math classes, such as calculus (1 to 3), probability, linear algebra and - drum roll - discrete mathematics. Now, just because you don’t see yourself as a ‘mathy’ person doesn’t mean that CS isn’t for you. So don’t let that discourage you in trying it out and seeing it for yourself.

2. It’s a HUGE time commitment

I’m pretty sure you know how the classic computer science student stereotype goes: a sleep deprived, caffeinated nerd who’ s been locked in their room for days debugging their code. Well, I hate to break it to you but sometimes, despite having excellent time management skills, that scenario does happen in real life. Note that college-level computer science assignments are designed to be very time-consuming, so that means staying in during weekends and griding on your code if necessary.

But forget about the notorious assignments for a moment. If you’re pursuing a career in Software Engineering, you know how important it is to network, network and network while in school and get as many good internships as you can. And that alone means doing personal side projects, constantly applying for internships and learning new tools and technologies on your own. That is why juggling all of those will being a full time student can be quite draining. This brings us to our next point

“This has happened to me quite a lot of times” - Gali (Blog Writer)

3. It’s extremely competitive

This makes perfect sense, considering how popular and in-demand the area of study is.

While it’s true that companies are hiring Computer Science grads everywhere, when you ask actual grads, it almost seems like the job hunt is the most gruelling stage of their career. Even for students it is extremely demanding to land internships as the demand (hence competition) keeps increasing.

This has pros and cons

Pro: you’re almost guaranteed a job after gradutation

Con: getting into your dream company might cost you a lot: lots of time, energy, sweat, tears, you name it. You have a lot of competitors, so be prepared to outwork and outsmart them.

4. Time management is key in the field

As mentioned above, CS is tough. Point blank period. Takes huge chunks of your time and energy, so you have to be careful on how you plan your days and especially study sessions. Trust me, you don’t want to get stuck trying to debug a piece of code for 9 hours (like I did during my first year), or spending more than an hour on a math problem, it’s simply not worth all that time. I know I mentioned earlier that sometimes you’ll get stuck, because it just happens sometimes no matter how well you manage your time.

Keep in mind that in case you get stuck, taking a step back from your computer screen can sometimes do wonders to your productivity, so don’t underestimate the power of short breaks! Just make sure they’re actually short though 😳… Because we know how a quick 10-minute break can easily turn into a 4-hour long getting stuck in a Tiktok-scrolling rabbit hole.

There’s so much I can add on regarding the importance of time management, for instance mainting a part time job, eating well, working out consistently, taking proper care of your face, skin, face and body in general (which are, in turn important time investments), all while keeping up with your studies, because at some point I was the struggling student, who barely had time for herself, constantly running deadline after deadline, shift after shift.

I can wrap up this brief blog post in a sentence I think, and not only it applies to studying CS, but also in general. Here goes the inspirational quote of the day: life’s tough, but so are you.

Like no, I’m serious. CS is hard, but if you have a vision for what you want out of your career, you have to believe that you HAVE what it takes and you’ll DO what it takes to achieve your goals.

Cheers to a new successful academic year! 🥂

Next post is gonna be a more uplifting one, just trust me 😎

What REALLY Makes Your Resume ✨Shine✨? Recruiter Tells It All

If you’re a Computer Science student, or perhaps any student majoring in a more “technical” field, you certainly know how crucial it is to secure those internships in order to land THAT one post grad full-time offer. We’ve all been through the hectic job hunt process - well, at least some of us! That’s right, it’s a whole process that requires energy, consistency , and most importantly, lots time! Submitting your resume is the first step, what will either make or break your application, so you really need to be smart about it.

We hosted a resume event with Beste Karli as our guest/recruiter, McGill Alumn and HR Professional at Tempo, where we got to know the nitty gritty details on your resume that could make you stand out among other candidates! Here’s what she had to say.

1. Proof read, proof read, proof read!!!

We can’t stress this enough. Make sure your resume doesn’t contain ANY spelling mistakes, that it’s written in clear, correct English. The last thing recruiters want to see are spelling mistakes or typos on a candidate’s application, so make sure you get rid of those.

2. Keep it short and simple

Look, we all want to highlight our best achievements, but sometimes that would make a resume pages long, which we don’t want. Recruiters will most probably not care about the awards you’ve won at MUN 4 years ago in high school, so make sure you declutter your resume and only state what’s relevant, and this brings us to our third point.

3. Tailor your resume for the role you’re applying for

What role is it that you’re applying for? Have you done more projects? Or do you have more work experience? You really have to think about the type of job that you’re applying for and highlight only the skills relevant to that position. Don’t include things you’ve achieved that you know for sure won’t be of use for the role, unless it’s clear that they’re valuable (i.e interpersonal skills and important leadership positions.

4. Formatting is key

First of all, there’s a bunch of things we have to take into account when formatting your resume:

• The chronological order of your achievements

• Your strongest suit and your ‘meh’ suit (i.e what to highlight first/last)

• The keywords used in the job descriptions

• Your use of bold, italic and caps

• Lastly, the “mise en page”

OK, starting from the last one, which is the probably the easiest, format your resume in the simplest way possible, don’t use any fancy templates, fancy fonts, or colors. If you’re after a strictly technical job, it’s best to use a good old plain Harvard format. There are also a lot of good templates that you can look at here. Note: submit it in PDF, so you don’t run into issues with formatting

Now onto the good stuff!

How to order your achievements?

“What should I put first ?”, you might be thinking.

For students, it’s best to keep the education section at the very top. Don’t focus too much on this section. If you’re a recipient of any big scholarships or awards, include them. Also include your relevant coursework if you’re looking at internships as a first or second year, but don’t make it take more than a fifth of the page.

Once you’re done with that, take a moment and think: do I have more relevant work experience or does my experience just mostly projects (whether personal, group, hackathon or competition projects). Whichever option that comes to your mind first, that’s what gets highlighted first.

Once you’ve got that one figured out, list the achievements starting from most recent. You have to keep in mind that the resume world is all about grabbing attention and making the readers ‘hooked’ to your resume. First impressions not only matter in this case, they're GAME CHANGERS. And this brings us to our next point.

“Know thyself”

Ah yes, the classic quote from Socrates, pretty sure you’ve heard or read this somewhere. It is crucial to know your strongest link when creating your resume, as you want to put the most important things first when describing the jobs you’ve done previously, or are still doing.

Since you’ll be using bullet points for the job descriptions, it’s easy to partition the work you’ve done into 1-2 liners, from most important (as ‘hooks’) to least important. Here again, don’t make long and wordy sentences, keep them straightforward.

Use your keywords wisely

Recruiters love seeing candidates who know the true value of their contribution. Use the “buzz words”, i.e action verbs that actually fit the job description (and this is where tailoring your resume come into play). Try to use more specific words than “helped”, “planned”, “planned”, etc.

Bold, italic, caps, none?

Be smart about the way you format your text.

Use all caps for the subheadings, italic for the roles you’ve worked, and bold for, well, a bunch of stuff!

There’s more than one way of making a shiny resume that grabs the attention of recruiters at the right places. You could perhaps bold the years of experience you have in a programming language, or you could highlight an action verb that you deem as very crucial to the description. It’s really up to you. The point is to market yourself the right way

5. Believe in yourself

Yes, yes, I know, this might sound a bit cliché. You’ve probably heard this millions of times, but it’s really important to stay confident throughout the process, to be able to face the challenges without giving up. Going into the tech industry surely isn’t a linear path, but if you trust yourself enough and you put in the work, you will make it.

Believing in yourself also means taking leaps of faith, and quite often, actually. I’m talking about applying to jobs even when you feel like you don’t meet all of the qualifications.

Most of the time recruiters put all of those points, but end up hiring someone who probably has half of the requirements, because let’s face it, they can be pretty unrealistic sometimes. So why not give it a try and take a small leap of faith? you’ve done all the tedious work at this point, you might as well take the chance and click that “Submit” button!

Recap: Women In Tech Consulting Panel

Last month, we had the privilege of hosting a Women In Tech Consulting Panel. Taking part in the panel were representatives from BCG, EY, Deloitte, Accenture, and IBM, each of which shared personal stories and valuable experiences in field of consulting. In today’s article, we briefly recap some points explored during the event.

1.     What is the difference between tech consulting and other tech positions?

The general consensus was that tech companies usually offer one or few products, while consulting companies involve a diverse range of industries; work rotations are thus more diverse. For instance, during her time with Accenture, Sarra has worked on a solution for an aerospace company and a global cosmetic company, two starkly different fields. 

Another point which many agreed on was that tech consulting does not involve as much hands-on coding as other tech positions. A career in consulting is therefore far different to one in Software Development, which is more so concerned with pure programming. If you are a Computer Science student who dreads the thought of coding up to 8 hours a day, then tech consulting may be for you.

2.     What’s a day on the job like?

Daily tasks involved in tech consulting are varied, as they are dependent on the current client and project. Projects range from months to years and can sometimes involve hundreds of people. For example, Ingrid from IBM mentioned that she has been working on the same project with over 1000 people for the past 7 months. Though projects and daily tasks differ, the one consistent responsibility is to develop a strong relationship and communication with the client.  

Daily tasks also change depending on how long you have been with the company. María from BCG commented that 70% of a new hire’s day will be filled with coding while the remaining time is for meetings and/or reviews. Senior roles, on the other hand, focus on tasks that involve more supervision and less low-level implementation.  

3.     How would you deal with comments or stereotypes about being a woman?

Given the gender disparity in computer science, we asked if any representatives have felt discriminated against. While most shared positive stories regarding offices in Montreal, some expressed countries outside of North America were not as welcoming.

Ultimately, they agreed that, while gender discrimination exists, the hardest part is usually the fact that you are the most inexperienced on the team, as a new hire. The process of breaking through that barrier and proving yourself can be challenging but demonstrating a willingness to learn is a key ingredient to success. Maria wrapped up this discussion up by stating that we should not give anyone the opportunity to treat us differently.

4.     What skills are unique to tech consulting?

The skill of being a fast learner, or at least having a willingness to learn, was brought up by almost every woman on the panel as a unique attribute to tech consulting. Sarra from Accenture mentioned that this is because technology is constantly evolving, thus solutions today employ vastly different tools compared to those that will be used in 5 years’ time. Tech consultants must adapt to this progression by exercising a desire to learn. The ability to pick up new skills is also crucial to excelling since tech consultants work on different projects over a range of industries throughout their careers, entailing a diverse skillset.  

To perform well in your interviews for tech consulting positions, make sure to highlight your capability as a fast learner and other adaptive qualities.

For more details on the panel, see the Facebook event. Thank you to everyone who attended!

Tips and Tricks for Surviving Midterm Season

As Fall ends, we slowly enter Midterm Season, one of the most hectic times of the semester. You’ll think you’re doing fine and then, suddenly, there’s 20 unwatched lectures on MyCourses and a closed-book midterm tomorrow.  It’s happened to all of us. Here’s some pointers and coping mechanisms to prepare yourself for the wave of deadlines ahead.

1.     Go Over Assignments

If you’re in a coding-based COMP class, like COMP202 or COMP250, you should be familiar with the grueling assignments. Professors will likely use concepts from those assignments in the midterm, so it’s important to go over each solution. Make sure you understand both the syntax, i.e how to write the code independently, as well as the theory behind it.

This technique is consistent with doing well in Math exams too, as often Professors will reuse assignment questions with different plug-in values. If you’re already used to the general structure of most questions and approaches, you’ll feel much more confident going into the midterm.

2.     Take Time to De-Stress

Long coffee-fueled nights at McLennan may work for the first leg of the midterm marathon, but it’s bound to fail without some self-care. Try to allocate one hour each day to non-work-related activities; for example, doing your nails and watching reality TV, possibly both at the same time. This will help you de-stress and keep your work schedule sustainable.

You should also remember to get a full night’s sleep. There’s no use in a 1 hour relax session when it’s 4am and your midterm is in 5 hours!

3.     Find a Way to Memorize

The past year and a half have gifted us open-book exams. The obvious positive of this is being able to look at notes during midterms and not needing to memorize complex equations and concepts. Since most of us no longer have the luxury, we need to remind ourselves of how to drill this content into our heads.

We suggest writing out equations or complex statements to remember them while studying. Otherwise, if you’re more of an auditory learner, you can also record yourself saying them and listen on repeat! The key takeaway here is simply not to forget the importance of memorization during exam season.

4.     What’s Your Best Work Environment?

With a reduction in pandemic restrictions, we are given the choice to work in environments other than our homes. It’s important we take advantage of this and cultivate learning habits that encourage focus. Staying in bed and reading lecture slides may feel less strenuous than going to the library, for example, but you’re also absorbing less content and preventing yourself from fully concentrating.

Try to find study locations that are both comfortable and productive. Luckily, there is no shortage of nice cafes around Montreal. If you prefer something quieter, McGill libraries are also a staple go-to.  

5.     Look at Past Exams 

The best place to seek out pointers for your midterm is through past exams. This will tell you your professor’s examination and grading style, in particular what format they use, how they write questions, and the difficulty level. These aspects will inform how you study for the exam and, more importantly, give you the practice to boost your confidence with the course material.

Finally, good luck to everyone with their coursework and exams! Let’s get through this midterm season together.

Women Who Pioneered Computer Science

Despite making up only 20% of the Computer Science industry, women have historically contributed to its development in insurmountable ways.[1] From winning Turing Awards to writing the world’s first ever computer program, it is undeniable that Computer Science would not be where it is today without the help of these female pioneers. So, let’s get into who these powerful icons are and how they have defined Computer Science as we know it.

1.     Ada Lovelace

Sourced from: https://www.historyrevealed.com/eras/19th-century/ada-lovelace-the-computing-pioneer/

Born in 1815, Ada Lovelace is considered the first computer programmer in the world. She accompanied Charles Babbage, the “father of computers,” on his work of The Analytical Machine, where she developed the first computer algorithm ever to be written. We can therefore say that she single-handedly planted the seed of Computer Science.[2]  

Although she is recognized as a visionary today, Lovelace and her accomplishments were generally overlooked during the 1800s. Only now is she being acknowledged, with organizations and events such as Ada Initiative and Ada day shedding light on her impacts on the field.[3]

2.     Frances E. Allen

Sourced from: https://www.ibm.com/blogs/research/2020/08/remembering-frances-allen/

 Frances E. Allen pioneered the industry of optimizing compilers. She worked with IBM for around 45 years and, early on in her career, developed a new code breaking language, Alpha, with the National Security Agency. It is therefore no surprise that she is the recipient of countless awards; the Turing Award, Computer Pioneer Award, and the Ada Lovelace Award to name a few.[4]

Having her name plastered all over a male dominated industry isn’t all, however, as Allen also actively advocates for minority representation in STEM and has used her platform to spread awareness.

3.     Carol Shaw

Sourced from: https://info.umkc.edu/unews/celebrating-women-in-stem-carol-shaw/

 Carol Shaw is one of the first professional female game designers in the industry, paving the way for women of tech for generations after. In 1978, she worked at Atari as a Microprocessor Software Engineer, developing games for their 2600 VCS console. Then, moving to Activision, she built River Raid, a critically acclaimed game that received numerous awards. In 2017, she was even awarded the Industry Icon Award by The Game Awards.[5]

Shaw’s career shows us that we can still excel in the face of adversity and play a pivotal role in building the foundations of our industry’s future.

4.     Evelyn Boyd Granville

Sourced from: https://undark.org/2016/06/13/unsung-african-american-contributions-mathematics/

 Evelyn Boyd Granville was one of the first African-American women to obtain a PhD in Mathematics in America. She graduated from Yale University and pursued her vision at IBM where she worked as a programmer. Granville then worked for the U.S Space Technology Laboratories, contributing to the celestial mechanics and trajectory calculations involved in their Apollo Project. [6]

Although retired now, she contributed almost 30 years of her life to academia, writing a textbook and teaching Mathematics at various institutions.[7] Granville’s influence on the world of aerospace computing and insights on academia are undeniable and certainly break new grounds for minorities in tech.



Bibliography

[1] Get an Education the World Needs | ComputerScience.org. ‘Women in Computer Science | ComputerScience.Org’, 15 October 2020. https://www.computerscience.org/resources/women-in-computer-science/. 

[2] ‘Ada Lovelace | Babbage Engine | Computer History Museum’. Accessed 28 September 2021. https://www.computerhistory.org/babbage/adalovelace/.

[3] ‘Ada Lovelace, the First Tech Visionary | The New Yorker’. Accessed 28 September 2021. https://www.newyorker.com/tech/annals-of-technology/ada-lovelace-the-first-tech-visionary.

[4] ‘Frances E. Allen | IEEE Computer Society’. Accessed 28 September 2021. https://www.computer.org/profiles/frances-allen/.

[5] atariwomen. ‘Carol Shaw’, 13 March 2019. https://www.atariwomen.org/stories/carol-shaw/. 

[6] Encyclopedia Britannica. ‘Evelyn Granville | Biography & Facts’. Accessed 28 September 2021. https://www.britannica.com/biography/Evelyn-Granville.

[7] Encyclopedia Britannica. ‘Evelyn Granville | Biography & Facts’. Accessed 28 September 2021. https://www.britannica.com/biography/Evelyn-Granville.

 

What I Wish I Knew As a First Year Computer Science Student

Being a First Year at McGill isn’t easy. Between recovering from Frosh and figuring out what the significance of samosas are around this place, there’s a lot to unpack. So, whether you’re just debating a Computer Science degree, or are already set on it as your academic path, here are a few things that might help you.

1.     Your Professor Matters 

Because the majority of courses you will take in your first year are absolutely huge, I mean 300 students huge, the way in which the professor communicates and teaches the course content is crucial. This does not necessitate that one professor is better than the other, but simply that different students have different learning styles.

If you aren’t compatible with a professors grading scheme, for example, it may be best to take the course next semester when there’s a different prof leading the course. If you know that final exams that count for 75% of your grade are overwhelming for you, then try to find professors who weigh class projects more.

One way to figure out if a professors teaching style is for you is by going on ratemyprof and reading through reviews. Remember, though, that reviewers are usually motivated to write by extreme perspectives – either very positive or negative – and therefore the reviews may not be the most accurate. Otherwise, you can peep the syllabus of the course during add/drop and confirm how intense the workload is by speaking to other upper years about their experience with the prof. 

2.     Not All CS Courses Are Like COMP202 

If you love problem solving, chances are you will thrive in COMP202. The projects are stimulating and, dare I say, fun. It’s therefore easy to get carried away and assume that the rest of CS will pretty much be an extension of the content you learn in the course. 

COMP202, however, is more so centred on the syntax of Python and general logic of programming. Contrasted with the theory-heavy, Math-involved upper level courses, it truly does not compare. In fact, some CS courses do not contain any programming at all and rely mostly on non-language specific code (i.e pseudocode). COMP250 might be a better way to judge whether or not completing a full CS degree is for you. This is due to the class’ emphasis on algorithms, which you will use for almost every course to follow.

 3.     Most CS Projects Cannot Be Finished In A Day!

We all have success stories of defeating our procrastination and pulling an assignment together last minute. Starting CS projects right before deadlines and completing them on time, however, is a whole other beast. Depending on the professor and the class, assignments can take a few days (or more) to finish. My personal method is to start the project exactly one week before the due date. If I finish it early then, great, I can move onto other things and be stress-free. 

4.     If You Can’t Resolve a Bug, Leave it and Come Back Later

Here’s two deadly words: “Runtime Error.” That glaring red message will have you rolling in bed at night, staring out the window, or even calling your Mom, desperately, to get some words of affirmation. Not really (actually, yes).

When that happens, it’s best to put the coding aside and do something else. Programming tunnel-vision is a very real thing and taking a step back to gain perspective will uncover different angles of approaching the issue. You might also realise that the solution you’ve been working on is harder than it needs to be. So, when you think you’ve hit a dead end, go get a coffee, start work for another class, or maybe even take a long, well-deserved break.

5.     Take Advantage of CS Resources

While CS may appear intimidating, always remember that there are resources out there to help you. Here are a few you should take note of:

·      CSUS and their Helpdesk in particular

·      Math Burnside Helpdesk

·      McGill SubReddit has some good information, for example this thread

 And feel free to ask us questions on our Facebook page, where you can also find events to get involved with the CS community at McGill!