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Hello everyone, I recently got the chance to be a part of the prestigious MITACS Globalink Research Internship in my summer of third year. In this article I will outline some important pointers regarding cracking the internship and also tell you about my life-changing experience as a MITACS intern in Canada.

First let’s start with what is MITACS GRI?

So, MITACS is a Canada-based non-profit research organization that also works closely with the government of Canada to promote and improve research and education in the country. The GRI or the Globalink Research Internship program is among some of the most prestigious opportunities for students, of almost all branches, entering their pre-final year. From this year they have extended the eligibility to students in the 2nd year as well. The program opens pretty early, generally the second week of August and has a deadline around late-September.

The internship program requires a full-time commitment of 40 hours per week for 12 weeks, serving as a research intern at one of the partner universities in Canada. The entire duration of your stay, including airfare, accommodation, and living expenses, is fully funded by the program. Additionally, MITACS arranges various social programs to enhance your Canadian experience beyond research. The stipend for Indian students ranges from 8000 to 8500 CAD, depending on the duration of your stay, host province, and university in Canada.

By participating in this program, you have the opportunity to collaborate with leading researchers in Canada and immerse yourself in a multicultural research community. In the lab where I was placed, individuals from diverse backgrounds such as Iran, Lebanon, China, and Korea worked together. This experience provides valuable exposure to different perspectives and research approaches from around the world.

Some facts about me

I am a final-year student majoring in Electronics and Communication Engineering at IGDTUW, Delhi. My passion lies in the realms of Artificial Intelligence (AI) and Machine Learning (ML), particularly within Computer Vision (CV), medical image analysis, and robotics. In the summer of my third year, I had the privilege of interning at Western University, Canada, through the MITACS Globalink Research Internship (GRI).

My strong interest in research is reflected in my membership in MISAHUB, a research society at my college that focuses on medical image analysis and deep learning. The prospect of participating in MITACS first caught my attention during my second year when I learned about it from a senior who had been a scholar the previous year. Eager to seize this opportunity, I dedicated myself to thorough preparation.

How to crack MITACS

The procedure of applying to MITACS includes submitting some documents including your college transcripts and letters of recommendation along with an application form with your chosen projects.

Application:

The application form is pretty straight forward and requires you to fill out your general information about your degree, college and some essay questions regarding your research interests and research experience.

These have a small word limit of around 100 words so try and include all the relevant information for example I used bullet-points and small sentences to get my point across.

You are provided with a large number of research projects to choose from on the portal and you have to submit your top 7 choices, ranking them in order of your preference.

These projects, proposed by professors of various universities across Canada, have a vast variety. The domains range from software/hardware development, AI/ML, data science, Blockchain, AR/VR to subjects like environmental science and healthcare. You are given information about the professor, host university, deliverables of the proposed project and required skills for the project. It is one of the most important aspects of the whole application and it is advised to choose wisely, taking your time exploring your areas of interest and skills.

Consider the following factors when choosing projects:

1. Align the project with your tech stack or research interests. Avoid projects that are completely unrelated or unfamiliar to you.

2. Review the faculty's profile, focusing on recent work and research publications. While university reputation is important, maintain a balanced approach when shortlisting projects.

3. Carefully examine the project proposal, ensuring it aligns with your area or domain of interest. Bonus tip: Identify ways you can contribute to the project's ultimate goal.

4. Prioritize project rankings based on your confidence level. While highly reputed universities can be considered, maintain a balance between extremely and well-reputed colleges. Professorial profiles can also significantly impact the project and your working experience.

5. Consider diversifying project selections based on relevant research interests.

Regarding the need for strong research experience:

1. While beneficial, you don't necessarily require a substantial research background, such as publishing multiple papers in top-tier conferences.

2. Your selection is influenced by your experience with the project idea and basic research work. Highlight whether your work is under consideration or if you have any published research.

3. Showcase your potential to the professor, emphasizing your ability to adapt and work effectively with research problem statements.

Next are your resume and LORs:

Based on my experience, letters of recommendation (LORs) should focus on the prospective applicant's ability to contribute to a specific project. While it's not mandatory for the LOR to encompass all the skills outlined in the selected project's requirements, it should demonstrate the applicant's capacity to tackle diverse problem statements. The LOR can highlight the individual's foundational knowledge in the relevant domain and their potential to learn, work, and acquire new skills. MITACS requires utmost 3 LORs but in my experience, one good LOR from a research mentor, some professor with whom you have research experience with or who can highlight your academic capabilities is more than sufficient for a successful application.

When crafting your Resume/CV, emphasize your research experience extensively. Additionally, maintain a diversified portfolio that includes work experience, projects, and co-curricular skills. I used this overleaf template for creating my resume — https://www.overleaf.com/latex/templates/resume-template-by-anubhav/dhmkrwtksdgy 

This completes your application and the next step is to simply wait while your application is studied by MITACS people. In the first round, MITACS does an eligibility check and screens applicants for their academic merit. The first round of updates comes in around the first week of November which states whether MITACS found your application good enough to be sent out to the 7 professors you chose as potential supervisors. This status is called Candidate Under Consideration (CUC). Or you might get Waitlisted where you have passed to the next stage but your profile has not yet reached the professors yet and you’ll get updated as and when your profile is sent for consideration.

If the host professor expresses interest in your profile, they may reach out to you for an interview. This interview could be a standard verbal discussion or involve a task, such as analyzing a research paper and delivering a presentation. I recommend thoroughly examining the host professor's profile, including their past and current work, research focus, and any notable contributions. This knowledge can aid you in developing genuine interest during your initial discussion or interview. Typically, the assessment revolves around your understanding of the project domain and your ability to contribute effectively to the proposed project.

In my case, I was updated to the CUC stage and contacted by my host professor for an online interview in the last week of November. My interview was more of a discussion wherein the professor talked about the project idea, asked for my initial inputs and why I chose this project and university. We also talked about my technical skills - my proficiency in Python and frameworks like TensorFlow, Pytorch, OpenCV which were requirements of the project. We then went on to my previous research experiences and projects I had mentioned in my resume and were related to the project. It was a 30-45 minute interview and the professor was very welcoming and sweet.

This stage is solely dependent on the project mentors. The project mentor can either select or reject based on your profile itself, some call for different rounds of interview or assign some tasks related to the project. All this helps in shortlisting their candidates.

Selection / Rejection

So, in the first round, a lot of folks end up on the waitlist, which means their applications haven't reached the professors just yet. Round 1 results usually roll out around mid-December. If a professor picks you, awesome! You're in. But if none of them shortlist you, you stay in the CUC stage. Now, if you were on the waitlist in round 1, there's a chance you might move up to CUC based on project availability at the end of the round.

Once you snag a spot, you get a few days to give it a thumbs up. If you're all in, MITACS will walk you through the next steps. Here's to hoping your internship turns out to be absolutely fantastic!

My experience as a MITACS Intern

I can vividly recall the day I woke up to an email announcing my selection for the MITACS Globalink Research Internship. The excitement surged as I learned I was matched with a project under the guidance of Professor Dr. Soodeh Nikan at the University of Western, Ontario. Landing an opportunity to explore Western University, one of my dream institutions, meant living the Canadian lifestyle.

Upon being selected and matched with a specific project, applicants are prompted to accept the terms, conditions, and the offered project on the MITACS intern logistics portal. This portal consists of various sections that need to be completed within specified deadlines, covering essential paperwork details like general contact information, terms and conditions, immigration, housing, flight details, and more.

Once matched with a project, you can reach out to the respective professor via email to discuss arrival dates, internship duration, prerequisites, and other relevant information. The MITACS GRI team will guide you to commence the VISA application process and book flights at the earliest. For a smoother VISA application process, consider the following tips:

1. Initiate the VISA process promptly to avoid delays caused by a high volume of applicants.

2. While you have the flexibility to choose any VFS center for biometrics and VISA paperwork, opting for the nearest center is recommended for hassle-free processing.

3. Ensure all supporting documents, such as academic transcripts, NOCs, and the MITACS Award letter, are prepared and ready for submission.

When booking flights, it's advisable to consider the in-travel connectivity, including the number of layovers in your itinerary. While flights with more layovers may be cost-effective, extended layovers can be exhausting. Opt for booking flights through official airline websites rather than third-party platforms for flexibility in rescheduling and modifying itineraries without additional costs.

Before departing, anticipate the initial costs to be covered personally, including VISA expenses, flight tickets, one month's accommodation in Canada (which may vary based on your booking), and some reserve cash for basic necessities.

Stipends are typically dispersed around the 20th of each month, contingent on your project's joining schedule. When it comes to cooking, consider bringing basic utensils like pans or crockery, though you can purchase them locally if luggage weight limits are a concern.

An essential tip: Learn how to cook! As an Indian vegetarian, finding affordable vegetarian options in Canada, especially on a student budget, can be challenging. Unlike friends who eat anything, cooking your own meals is not only cost-effective but also offers control over your diet. I strongly recommend acquiring cooking skills before your journey to Canada. While it may require some practice, the ability to whip up delicious vegetarian dishes will not only save money but also allow you to enjoy meals tailored to your preferences and dietary needs.

Flying to Canada:

I started my journey in Canada from India — a little excited and nervous since it was my first international journey, in fact it was my first time traveling anywhere alone. I had my flight from Delhi to Zurich to Toronto. It was a 25 hour journey and I was, unsurprisingly, very tired. But as soon as I landed in Toronto and got out of immigration and baggage claim, I was super excited to start my summer. Western University is situated in London, a city which is a 3 hour drive from Toronto so I finally reached my accommodation in the evening and was so exhausted that I just slept and unpacked the next day!

When it comes to studying and traveling abroad, there are a few things you need to keep in mind. First of all, the study atmosphere at the internship was really amazing. The mentors and faculties were super supportive and always willing to help you out, both on a personal and professional level. They made sure that I didn’t have any issues during my internship and that everything was going smoothly. MITACS also appointed us interns, mentors from the host university, which are students studying there. They help you in all aspects concerning living and working in the new atmosphere.

That being said, you do need to work at a certain pace and put in constant hard work. Your faculty will support you and give you some guidance if you get stuck, but ultimately, you’re the one who needs to figure out how to get the work done. It’s also important to do some background study on the selected project, including recent work and the latest developments, to make sure you’re up to speed and ready to contribute.

As for travel guidelines, it’s important to note that it can take up to 3 weeks for your visa to get approved. If you’re in the MITACS GRI category, it might get processed faster, but it all depends on the approval time and visa application traffic. I recommend using Skyscanner to check for flight options but make sure to book through official airline websites or reputable ones like Makemytrip or even airline specific websites like Qatar and Swiss. Avoid layovers in countries like the USA or Japan that require a transit visa, as it can incur extra costs, take a lot of time for visa approval and hinder your immigration processing.

For my flight itinerary, I flew from Delhi to Zurich to Toronto and to London via bus, and then from London to Toronto to Frankfurt and back to Delhi. As for accommodations, it really depends on which province you’ll be in. Sometimes on-campus accommodations are better, and sometimes off-campus options are cheaper. I went for an off-campus student accommodation which I found out through various Facebook groups of Western University itself. These groups are a good place for finding affordable and nearby accommodations as students from the university generally sublet their rooms for the summer. However, you should be careful and always double-check all the details and documents before finalizing and paying the advance.

Another important tip: try to learn how to cook before you leave for the internship, as it can help you save money on food. Preparing your food is much cheaper than opting to eat out everyday, especially in a province like Toronto. Moreover, it is more fun when you and your friends/roommates cook together. My rent covered wifi, water, heat and other amenities, but not meals.

Overall, working and traveling can be an amazing experience, but it does require some planning and preparation. Make sure to do your research, stay organized, and be open to new experiences — you never know what you might learn!

Internship experience

I'm genuinely thrilled to have had the opportunity to collaborate with an exceptional group of individuals engaged in groundbreaking work in the field of Autonomous driving at Western. To be honest, my understanding of applied research in computer vision, particularly in the domain of Autonomous driving, was quite basic before joining them. However, working alongside this talented group who shared my interests significantly enhanced my reasoning and problem-solving skills in dealing with new DL architectures, frameworks, and HPC systems. This experience provided me with a fresh perspective and approach to exploration and research, which I still apply whenever I have a new idea to experiment with.

In a nutshell, over the next three months, I delved into a project that seamlessly combined software development and research. This period was instrumental in not only refining my technical skills required for research in AI/ML but also instilling the mindset and attitude essential for success in this field. A key lesson learned was the paramount importance of collaboration and teamwork—working with individuals possessing different perspectives and strengths proves invaluable when tackling complex problems. Apart from weely 1:1 with my project mentor, our lab also used to have bi-weekly meetings where we used to talk about our progress updates, discussing and giving each other our inputs and working together as a team.

Conducting literature reviews and staying abreast of the latest research in the field became second nature during this project. This knowledge was crucial in devising new solutions or enhancing existing ones, offering insights into what had been attempted in the past and its success or failure.

This experience has undeniably shaped my thinking and problem-solving abilities, not just in the research domain but also in other facets of my life. It taught me to approach challenges with patience and persistence, fostering openness to new ideas and perspectives. I'm grateful for the opportunity to have worked on this project and to have gained such profound insights from it.

Furthermore, I had the privilege of attending networking events and exploring career options at the university. Interacting with professionals from diverse industries provided valuable insights into their career paths and accomplishments. Conversations with current master’s and Ph.D. students shed light on their daily routines, time management strategies, and motivations as research students. Learning about their research aligning with career aspirations and how they plan to leverage their experience for future success was particularly enlightening.

These enriching conversations provided a clearer understanding of the life of a research student and valuable insights into what to expect if I pursue a research-based master’s program in AI. It also illuminated how to prepare for a successful career in this field—a path I eagerly anticipate pursuing, combining software development and research in AI.

In conclusion, my internship experience in London was not only fulfilling and rewarding in terms of technical skills but also provided valuable insights into Canadian work culture and lifestyle. I wholeheartedly recommend Western as a destination for those interested in a career in AI or computer vision, whether for research or internships.

Living Experience:

Beyond the realm of work, my Canadian experience is etched in my memory for the invaluable lessons learned while living independently. Simple tasks like grocery shopping, navigating transportation, and exploring a new city solo became unique and enriching experiences. Every aspect of daily life held its own significance and contributed to my personal growth.

Adding to the richness of my time in Canada, I had the opportunity to travel to Toronto and Niagara Falls, an experience that stands out as truly amazing. The majestic falls and the breathtaking view from the SN Tower rank among my all-time favorite memories.

At Western, a host of social events brought together students from around the globe, fostering new friendships and cultural exchanges. Contrary to my initial skepticism about handling solo living in a foreign place, I had a delightful time. Not only did I advance my skills and gain valuable research experience, but I also underwent personal growth, emerging more self-assured and confident in my abilities.

End of Internship - Media interviews about project, saying goodbye

Concluding my incredible experience, I bid farewell to Canada with a firm promise to return soon. Departing from Canada was undoubtedly emotionally challenging after such a transformative experience. I made a personal commitment to revisit and perhaps even pursue my Master's through the MITACS program. It's fascinating that being selected for the MITACS GRI program makes you eligible to apply for MITACS Accelerate, which offers 15,000 CAD to support admission to top Canadian universities for Master's studies. This presents a fantastic opportunity for students aiming to further their education in Canada, and I definitely intend to explore it in the future.

Spending three months in a foreign country, living independently in Canada, was genuinely life-changing for me. It instilled a sense of responsibility and self-reliance, unveiling a more mature side of myself that I hadn't recognized before. It felt like a glimpse into what my life could be like if I chose to pursue my Master's degree in Canada.

Throughout my stay, I had the privilege of working on research projects aligned with my passions, earning income to sustain myself, and learning the art of cooking. These were all novel experiences that contributed significantly to my personal growth. At the ending of my internship, I also got the chance to be interviewed by the local media for our project this summer. It was truly thrilling talking about my work I did these past 3 months, in a microphone, in front of a camera, making it one of the standout aspects of my journey! Our news article was also published here: https://london.ctvnews.ca/researchers-use-ai-to-determine-drivers-health-and-mental-state-in-self-driving-cars-1.6514170 

Concluding Remarks!

In conclusion, I must emphasize that being a MITACS intern was truly a life-changing experience for me. For anyone with a keen interest in research, a desire to explore and engage with like-minded individuals, and a passion for working on cutting-edge projects across Canada, MITACS stands out as the optimal opportunity. I hope this information proves valuable to those aspiring to become MITACS interns in the upcoming year. Wishing you all the very best!

Feel free to reach out to me if you have any questions or just want to chat: https://www.linkedin.com/in/harshita-mangotra-4b6b751ba/

It feels as if it were just yesterday when seniors shared an email about the Microsoft Engage Mentorship Program—a program where Microsoft engineers guide college students. It was an enriching experience, providing us with the opportunity to learn from exceptionally talented engineers.

During the mentorship period, we were tasked with building a project. I chose to create a mood detector project using face recognition. Juggling this project alongside my end-of-semester exams and an internship proved to be a challenging yet amazing experience. I acquired valuable skills in time management, learning to give equal priority to all three responsibilities. All these efforts proved worthwhile when I received an email from the recruitment team, stating that I had been shortlisted for the interview process.

The interview, lasting 45 minutes, was remarkably smooth. I was presented with a medium-level Data Structures and Algorithms question, and we engaged in a fruitful discussion about my past projects. To my astonishment, in less than 24 hours after the interview, I received another email from the recruitment team confirming my selection as an intern. The feeling was surreal—it was the first time when I truly believed that dreams do come true!

My experience at Microsoft differed significantly from my previous internships. It was my initial experience away from my family, navigating life in a new city. Adjusting to this new environment presented challenges, but my Microsoft team quickly became my second family in this unfamiliar city. I am grateful to all my teammates who were consistently supportive, guiding me throughout my internship. Interning there made me realize how fascinating the corporate world is and how people collaborate as a team.

Lastly, I would like to emphasize that all the hard work I put in to secure the internship was a 100% worth it. If given the opportunity, I would love to go back in time and relive each and every day once more!

Written by Nikita Garg

This summer I got the chance to be a part of Uber as a Software Engineering Intern. It was an experience filled with learnings that will last a lifetime!

The selection process:

I got hired on campus. The first step involved the coding round. The level of questions was medium to hard and 3 questions were to be solved in the time limit of 1.5 hours. At this step around 17 students were selected from our batch after the coding round. Moving further, there were 3 rounds of interviews: 2 Technical and 1 Managerial. All three rounds were eliminatory. 

After tedious and long interviews spanning a full day 3 students were finally selected for the Software Engineering Internship at Uber. 

Thoughts:

During the selection process, there were many instances when I doubted myself. But at this stage, it becomes more imperative that one should just focus on giving their best and not be intimidated by others. This is the step that requires the most confidence and shows the interviewers what you are capable of. Who knows the interviewer might see a unique spark in you!

My experience:

Now came the big part. The actual test of survival and grit. Performing well in the corporate surroundings on top of staying alone in Bangalore away from family was a real challenge. My joining was from 5th June so I went a couple of days early to settle in better and become accustomed to the new environment. Normally people doing internships take up accommodations in a PG and I too took up the same and stayed with a friend. The first day was the orientation and onboarding where we were given a proper introduction, our laptops, and access credentials for our coding work. This day was fun-filled, the HR organized fun little activities and games, and we got introduced to the Uber leadership team too. It was mostly ice-breaking sessions, I got to meet other interns and made some friends too! The day ended with us meeting our mentors in the office. My mentor assigned some learning tasks that each intern has to go through known as “Uber Engucation”. These tasks or short courses involved learning about the codebase, the services, and how to create PRs (called diffs in Uber). Alongside these courses, my mentor assigned a few tasks study tasks as well and we started discussing my project towards the first weekend. We had weekly feedback sessions wherein my mentor gave feedback to me about my consistency and performance. I also had weekly one-on-one meetings with my manager regarding my project and how I am finding the work here at Uber. My mentor encouraged me to do research well for the given task and only ask for help when one has tried out all possible options. Along with this, my team members were very supportive and often discussed my project and had some informal talks too. 

I had daily standup meetings with the whole team where each of us had to update our work progress and any issues we might currently be facing. Everyone was welcome to share their thoughts and alternatives to problems. The food there was great and all types of amenities were available to us. The first few weeks were stress-free as I explored the office, and the games and enjoyed the food. Then again, that doesn't mean that the learning stopped! I got to meet so many new people, talk about various topics at lunch, and take relaxing walks in the tech park. During the last few weeks, the focus moved completely towards the project and the only aim was to prepare well for the final presentation. I had my final presentation on my last day after which my team organized a farewell party for me. Overall it was an amazing experience and I’ll remember it my whole life.

Written by Charvi Bansal

MSFT Engage Mentorship Program

My journey with Microsoft began with the MSFT Engage mentorship program, where I had the chance to be mentored by Microsoft engineers while working on a project. It is an exceptional mentorship initiative that bridges the gap between aspiring students and seasoned Microsoft Software Engineers. This unique program offers mentorship, project collaboration, and insightful sessions about Microsoft's culture and values. What's even more incredible is its inclusivity, welcoming students from diverse branches, even those outside computer science. 

After a month of working on my movie recommendation system (https://share.streamlit.io/manika137/microsoft-engage-recommendation-system/main/main.py) project and managing it simultaneously with my end-semester exams,  an exciting opportunity arose—an interview for a summer internship at Microsoft. The interview, involved a DSA question- later optimising it and further questions on different data structures (trees, hashmaps) and operating systems that lasted 45 minutes. A week later, the golden email arrived—I had secured internship at my dream company!

The Internship Journey

I was assigned a team under Azure Storage's umbrella, the ABFS Hadoop Driver team. My internship unfolded in the vibrant city of Bangalore. This was my first time living away from my family, a testament to the unique experience Microsoft was offering. 

Thankfully, I was able to ramp up in the first week itself and with the second week, the real work commenced.

My internship comprised of two intriguing projects:

• Analyzing scale runs for network error handling 

• Automating the workload runs

With the support of my amazing team, I quickly acclimated to the projects. I found myself setting realistic targets collaboratively with my mentors and working towards them daily. I made sure to update them every morning on what I was working on for the day and provided them with an end-of-the-day update on the progress I had made. 

While working on Java, KQL, data engineering, and performance optimization, I had countless learning experiences. Regular stand-up meetings with my mentors and weekly updates with my manager kept the communication flowing smoothly. The learning curve was steep, but the team's encouragement and guidance helped me grow both professionally and personally. I never hesitated to ask them doubts- even if they seemed silly to me and tried to provide my inputs in every team meeting. 

Being the only intern in my team didn't make me feel like an outsider; instead, I was welcomed warmly. Networking with engineers from different teams became a rewarding aspect of my internship. The team's camaraderie was evident during team outings, making the entire journey memorable. The cherry on top was a team outing to celebrate my birthday, turning the second-last day of my internship into a no-work day for everyone! 

My Microsoft internship was not just a dream come true but a transformative experience. I miss the collaborative atmosphere, the mentorship, and the incredible opportunities for growth. I strangely even miss Bangalore's traffic, the "signal nahi aa raha yaar", the after-lunch walks with my team and what not. Microsoft not only provided a platform to contribute meaningfully but also fostered an environment where every day was a step forward in my career and life's journey. 

Some Advice

Here is some advice for students preparing for interviews/ starting with their internships:

Preparing for Interviews

1. PRACTICE DSA- no need for explanation

2. If you feel you're not able to explain your approaches properly during interviews or get anxious, give mock interviews. There are platforms for the same and you can even reach out to your seniors.

3. Be prepared to answer questions on projects you mentioned in your resume. You should have a basic idea of all the tech-stacks and skills you mentioned.

4. Revise the previously asked interview questions for the company you'll be interviewing for.

5. Have a proper grip on computer science fundamentals- especially Operating Systems and OOPs.

Starting with Internship

1. Interact with EVERYONE- even the senior most managers. With people from diverse groups and cities coming together- there's so much they'd want to know. Building connections at all levels not only enriches your internship experience but also lays the foundation for a broader network that can be beneficial throughout your career. 

2. Do not hesitate to ask questions! No one expects you to know everything and they'll always appreciate if you show your curiosity. 

3. Update your managers and mentors and regularly ask for feedback.

4. Take help of other interns (most likely they'll be in the same boat as you) and always help if you can.

5. Don't stay bottled up; talk to your friends and make new connections in a new place. The best thing you can do is stick together, and even the toughest phases will pass quickly. Reflecting on my journey, I realize the pivotal role my friends played in making my internship experience memorable. 

Lastly, don't take yourself too seriously and enjoy every experience:)

Written by Manika Joshi

Artificial Intelligence (AI) is getting increasingly sophisticated at doing what humans do, but more efficiently, rapidly, and at a much lower expense. The potential for AI in healthcare is vast. It can resolve many significant strides in the healthcare industry like offering a wide range of tools and increasing efficiency. AI is most efficiently being used in the field of diagnosis and can be trained to diagnose conditions such as cancer and strokes. Tech firms and start-ups are also working assiduously on similar grounds. Google, for example, is collaborating with health delivery networks to build models from big data to warn clinicians of alarming conditions, such as heart failure. The following are some ways in which AI is being used in healthcare, also few potential benefits and challenges that it brings along:

Clinical Methodology:

Pathological analysis of cells is considered to be a premium standard of diagnosis and allows microscopy slides to be scanned and analyzed. AI-led tools have contributed to diagnosing a number of diseases like breast cancer, gastric cancer, etc. Several models including neural networks have shown accuracy similar to human pathologists, and in some cases even better than humans alone. AI can be used to highlight areas of concern along with identifying histological findings at levels beyond human visibility. Thus, AI is used to assist doctors to make decisions and provides them with vast amounts of medical data and analysis. AI can analyze records, genetic data, and endoscopy reports to a good extent which can help doctors diagnose, and treat those diseases more accurately. The greatest challenge is not whether it is useful enough but rather ensuring its adoption in daily clinical practice.

Patient Monitoring:

Patient monitoring has expanded the reach of practices that were earlier thought to be available in urban areas only. The continuous advancement of technology and capability has affected healthcare and has led to a boost in deliveries of medicines to homes and more pockets. Thus, AI can help by capturing vital signs, well-being metrics, and background data. Such an atmosphere can help us in real-time monitoring and pre-emptive interactions between proficient and the needful to prevent atrocities. These can also improve the quality of decisions and can be of great help to the longitudinal metrics. AI can provide doctors with some real-time data on patient health and allows a passage for early intervention if required. This can reduce the need for hospitalization, improve the outcomes to a greater extent, and can reduce healthcare costs.

Drug Discovery:

Drug development has a crucial spot in the industry as it involves bringing a new drug molecule into clinical practice. It encompasses all steps from basic research of finding a suitable molecular target to supporting the launch. However, it is being limited due to a lack of advanced technologies which in turn makes it an expensive and time-consuming process.AI can be used to recognize certain compounds and can provide validation for the drug structure design. Models can also be used to implement safe and efficient evaluations of drug molecules based on data modelling and analysis. In addition to drug discovery and development, data analysis and broader data sets could help professionals assess risks and predict disease at a safer stage. Currently, AI algorithms are being trained to an extent that they can predict the efficacy of new drugs and identify potential side effects, reducing the risk, and cost associated with drug development.

Potential Benefits:

AI has enough potential to revolutionize the industry by providing personalized and efficient care to patients, reducing costs, and also improving outcomes. It has reduced healthcare costs by allowing organizations to use more sophisticated technology that’s accurate and efficient which has also led to better outcomes. It comes with a set of tools designed to scan for errors, optimization, and provide timely access to results. It takes care of the fact, that no critical information goes unnoticed because it might lead to biased results and inaccuracies.

After being this efficient and a do-it-all tool for the medical industry, AI still has a lot of challenges to deal with like privacy concerns, biased results, and dependency on data provided. Thus it still cannot be relied upon for complete analysis without any human intervention.

Conclusion:

AI is transforming various medical methods and is providing doctors with new tools to treat ailments. While the benefits are numerous, there are also certain drawbacks. As it continues to develop, we can expect more applications and personalized care with more efficiency. It will be able to enhance preventive care and quality of living, cheaper and better diagnoses along with treatment plans. It can also predict and track the spread of infectious diseases by analyzing data from government, healthcare, and other sources. Thus, it can act as a powerful tool for combating epidemics and pandemics on the same grounds.

Written by Shanaya

Medical imaging has changed the face of the modern healthcare sector by precisely imaging the human body and treating chronic diseases. According to EMC Digital Universe, hospitals are generating 50 Peta-bytes of data every year across the globe. A staggering 90% of all the healthcare data comes from medical imaging where more than 97% of it goes un-analyzed or un-used. Such heavy database generation, storage, and accurate interpretation represent an enormous challenge for healthcare organizations. It is even more challenging for developing countries like India where every year 5.2 million deaths are reported due to incorrect or late diagnosis, improper team coordination, and shortage of medical staff and devices in the hospital. Computerized medical imaging analysis is an essential current need to reduce error, costs, and processing time, and accelerate medical prognosis.

Recent progresses in deep learning have shed new light on medical image analysis by finding meaningful associations and patterns which are present time–consuming or repetitive, and difficult to analyze by skilled healthcare professionals. Deep learning algorithm-based machines try to interpret, classify and quantify imaging data in the form of complex patterns and structures by building multi–layer artificial neural networks. These neural networks consist of interconnected neurons grouped into three different types of layers namely input, hidden, and output layer(s). 

The word ‘deep’ refers to multiple numbers of hidden layers (sometimes, more than 1000). Each neuron connection is associated with a random weight. They can be set according to the importance of the input value. After receiving the raw data at the input layer, complex mathematical associations and patterns are made and tested in the hidden layers. Such a network now learns these patterns and may predict new data and or identify similar data. It is very similar to the learning process that occurs in our brain’s neocortex. 

The power of deep learning algorithms is not limited to the identification of unhealthy tissues, performing repetitive segmentation tasks, and automation of imaging processes but also the detection and prediction (years before) of chronic disorders like epilepsy, Alzheimer’s, different types of cancers, depression, etc. According to Signify Research – a market intelligence and consultancy to the global healthcare technology industry, deep learning-based healthcare solutions will become a $300 million industry by 2021. There are already a number of FDA-approved life-saving AI diagnostic devices such as IDX – DR for detecting retinopathy, QauntX for evaluating breast abnormalities, Aidoc for identifying intracranial haemorrhages in head CT scans and etc in the market.

Written by Palak 

WHY MACHINE LEARNING

Machine learning is one of the fields that is growing rapidly in computer science because of several factors like the advancement of technology, availability of datasets, growth of automation, increased investment in machine learning, increased awareness of machine learning benefits and much more. AI and machine learning jobs have jumped by almost 75% over the past four years and are poised to keep growing. IT analyst firm, Info-Tech Research Group reports that 44% of private sector companies plan to invest in AI systems in 2023. 63% of companies surveyed plan to increase or maintain AI and machine learning spending in 2023. That is partly why machine learning is important and why we should start learning it.

LEARNING FROM BOOKS

Choosing the right book is an important part of any learner. The best part? We have curated a list of all popular and useful books that are “freely” available on the internet.

Beginner-level books: 

If you're new to machine learning and feel overwhelmed by the number of books available, you're not alone. With so many options, it can be difficult to know where to start. To save you time and help you get straight into the learning process, we've compiled a list of popular ML books for beginners.

1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 

Author: Aurelien Geron

This book is specially designed for beginners and is highly recommended. It covers the fundamentals of Machine Learning techniques including supervised, unsupervised, reinforcement, and deep learning. Basic algorithms like linear regression, logistic regression, tree-based, support vector machines, and random forest. It basically starts from the initial to the final so highly recommended for beginners.

https://github.com/EvanLi/programming-book-3/blob/master/Machine-Learning/Hands%20on%20Machine%20Learning%20with%20Scikit%20Learn%20and%20TensorFlow.pdf

2. The Hundred-Page Machine Learning 

Author: Andriy Burkov

This book provides a concise and practical introduction to machine learning and covers a wide range of topics. The author focuses on providing practical examples to help learners understand how things work in machine learning. Covers all the fundamentals in a very brief so you can use this book as a reference too.

https://github.com/tirthajyoti/Papers-Literature-ML-DL-RL-AI/blob/master/General-Machine-Learning/The%20Hundred-Page%20Machine%20Learning%20Book%20by%20Andriy%20Burkov/Links%20to%20read%20the%20chapters%20online.md

3. Machine Learning for Dummies

Author: John Paul and Luca Massaron

This book includes real-world examples to help readers understand, it includes tips and tricks for implementing machine learning algorithms. Because of these features, it is also suitable for non-technical readers who want to understand the basics of Machine Learning. 

https://github.com/mr-ubik/machine-learning-for-dummies

4. Machine Learning for absolute beginners

Author: Oliver Theobald

This book provides an overview of Machine Learning, especially for absolute beginners who do not have any prior knowledge of the technical terms which is why the name “absolute beginners”. Narrative is engaging and can be understood easily.

Intermediate-Level Books:

If you already have basic knowledge about Machine Learning and are fascinated about how these things work and want to know about it you must refer to this list of books we have got a list of highly recommended books that are easily and freely available.

1. Python Machine Learning

Author: Sebastian Raschka

This book is a comprehensive guide to learning Machine Learning and Deep Learning with Python. This book is good for learners who have prior knowledge of Python. The author also included additional learning resources like her own course notes, research papers, textbooks, articles, etc in the sidebar  

https://github.com/rasbt/python-machine-learning-book 

https://github.com/rasbt/python-machine-learning-book-2nd-edition

2. Machine Learning for hackers

Author: Drew Conway and John Myles White

This book provides you with hands-on learning case studies instead of traditional mathematics. In this, you will be able to understand how data needs to be explored, manipulated and understood. The R language is used in this book to analyse the data. It helps you to understand Machine Learning and statistics through hands-on case studies.

https://github.com/wuhujun/git/blob/master/R/Machine%20Learning%20for%20Hackers.pdf

3. Deep Learning

Author: Ian Goodfellow, Yoshua Bengio, and Aaron Courville

This book provides you with depth, clarity, and practicality. The author does very good work in explaining concepts that are easy to understand and it covers a wide range of topics. The examples are drawn from real-world problems. The highlighting part is that the authors are known experts in this field and the insights provided by them are helpful.

https://github.com/janishar/mit-deep-learning-book-pdf/blob/master/complete-book-pdf/Ian%20Goodfellow%2C%20Yoshua%20Bengio%2C%20Aaron%20Courville%20-%20Deep%20Learning%20(2017%2C%20MIT).pdf

4. Neural Networks and Deep Learning

Author: Michael Nielsen

This book provides you with the best explanation of Neural Networks and Deep Learning. It is easy to read and can help you make neural nets from scratch as it has provided codes as a tutorial. It helps you understand everything about Neural Networks and focused on the whys of NN for curious readers.

https://github.com/Monikarana27/Neural-networks-and-deep-learning-by-michael-nielsen/upload

Advanced-level books:

If you are well versed in the basics of Machine Learning and want to deepen your knowledge in it, there are some open-sourced books out there which are helpful. The list that I have curated in each of these books covers a different aspect of advanced Machine learning whether it is reinforcement learning, pattern recognition, graphical models and much more.

1. The Elements of Statistical Learning

Author: Hastie, Tibshirani, and Friedman

This book provides you with a wide range of topics like linear regression, logistic regression, tree-based, neural networks, and much more. The author knows very well what he is trying to explain. Every chapter contains a good amount of practice questions after the end of each chapter.

https://github.com/tpn/pdfs/blob/master/The%20Elements%20of%20Statistical%20Learning%20-%20Data%20Mining%2C%20Inference%20and%20Prediction%20-%202nd%20Edition%20(ESLII_print4).pdf

2. Neural Networks and Deep learning

Author: Charu Aggarwal

This book is new compared to other books but it has a new perspective on the topics. It explains you well. The author is presenting her deep knowledge about each model that she gained through experience. Good for those who want to delve into Deep Learning.

https://github.com/tpn/pdfs/blob/master/The%20Elements%20of%20Statistical%20Le

3. Pattern Recognition and Machine Learning

Author: Christopher Bishop

This book provides a comprehensive introduction to machine learning. It covers a wide range of topics like supervised, and unsupervised, neural networks, graphical models, bayesian learning and more. This book is highly recommended for researchers and graduates who want to deepen their knowledge of Machine Learning and its application. It mainly focuses on Bayesian learning and statistical models which helps to understand other algorithms.

https://github.com/Monikarana27/pattern-recognition-and-machine-learning-by-christopher-bishop/upload

4. Bayesian Reasoning and Machine Learning

Author: David Barber

The book is divided into three parts first is the introduction of Bayesian probability theory and its application, and the second is about algorithms of Machine Learning, like decision trees, neural networks, and support vector machines. The third part includes the advanced part of Bayesian inference and machine learning, such as Bayesian networks, Markov Chain Monte Carlo methods, and Bayesian model selection.

https://github.com/tpn/pdfs/blob/master/Bayesian%20Reasoning%20and%20Machine%20Learning%20(181115).pdf

In summary, whether you're just starting or looking to take your skills to the next level, there are plenty of great books on machine learning. As beginner-level books start with the foundation of Machine Learning make you friendly with the technical terms and application of various algorithms, their applications. Intermediate-level books deep diver into models explaining how they work their application and how to make them from scratch. Advanced-level books list that we have curated are popularly recommended and good for graduates and researchers.  By exploring these resources, you can build a solid foundation in the field and stay current with the latest trends and techniques.

Written by Monika Rana

Hackathon

48 hours of your daily routine where you just forget the world. These 48 hours are filled with nervousness, excitement, overflow of ideas, blank brains, sleepless nights, coffee the bff, and just a lot of memories/experience with learning.

Is a Hackathon is Really necessary????

I am not going to answer this question. You can figure it out automatically after the end of this section.

1. Connections - Hackathons are one of the best platforms where you meet different tech geeks who are in this ocean for years. Effective networking leads to different opportunities. 

2. Innovation -  “People who are crazy enough to think they can change the world are the ones who do.” — Steve Jobs. 48 hours where you have to put your whole soul to a single task and make it alive. Thinking of new ideas, and shaping it accordingly is a dream come true. Doing this in a competitive environment keeps your enthusiasm at peak. 

3. Determination - Working on a single topic for just 10-15 hours is overwhelming. But here all the participants are working on a single problem statement for about 48 hours. This determination not just ends after the hackathon but it also affects your routine and you are ready to take up any project or goal.

4. New skills - Provides an opportunity for participants to learn new skills and technologies. One can improve their coding skills, design, teamwork and this list never ends.

5. Teamwork - Condition to participate in hackathons is to work in team. This helps in developing social life and teamwork skills such as communication, leadership quality, and way to represent your thoughts.

6. Exposure - Hackathons provide a platform where participants can showcase their creativity, skills to a wider audience. This helps them to gain recognition and even attract potential investors.

I am sure that you are determined now to take part in hackathons.

So, here are some famous, fascinating list of hackathons where you can unleash your potential.

1. Smart India Hackathon : This is a national level hackathon organized by the Ministry of Education and the Ministry of Electronics And Information Technology.

• Eligibility - Student from class 6 to 12 or students pursuing undergraduate ,    postgraduate , PhD.

•  Registration process - Students cannot register themselves directly. Only those           students are allowed to register who are selected in the internal hackathon. College SPOC will be responsible for selection of top 15 teams. 

•  Team Formation - 

1. All team members should be of same college inter-college students cannot   participate as a single team. However, members from different branches of same college can form a team.

2. Each team must have 6 team members including team leader.

3. Each team must have at least one female team member

• Timeline - April 1st week.

2. HackWithInfy - Hackathon conducted by infosys.

• Eligibility - 1. Students of 2nd, 3rd and 4th year from B.E/B.Tech/M.E/M.Tech  graduates in computer science and IT.. 

                           2. You should be of age 18 or older.

                           3. Percentage should be above 60% or 6.5 CGPA in all over education (10th ,       12th, UG, PG)

• Rounds -

Round 1 - Individual Online Test 

Round 2 - Selected teams have to attend the final round in Infosys campus.

Technical Interview - Based on the performance you will get jobs on different  profiles.

• Timeline - Between april end and may first week

3. Microsoft Imagine Cup : Global competition where students can use different technologies like artificial intelligence, machine learning, and more to build different products.

• Eligibility -He/she must be of at least 16 years old.

• Rounds - 

Epic Challenge - This an optional round. In this round teams have to show their project plan and how they are going to accomplish that. The project proposal should be of 3 minute long  presentation video.

Round 1(Semifinals/local events) - In round 1 teams should have to choose from  4 competition categories (earth, education, health, lifestyle) to build the project. 

Round 2 (World Finals) - Selected teams are eligible for round 2. In this round selected teams have to represent their project to a panel of judges. 12 teams will qualify for the next round.

Round 3 (World Championship) - All teams have to submit working proof of their developed software and need to give a live presentation to the judges.

• Timeline - October first week

 4. Hack the mountains - Hackathon organized by IIT Mandi in collaboration with several other organizations. This is a virtual hackathon.

5.  Google Girl Hackathon - Hackathon conducted by google specially for girls.

• Eligibility - Girls of 2nd and above year.

• Rounds - 

Round 1 - Google Online Challenge (GOC) - This is an online coding challenge of 60 minutes. All team members are required to participate. Team will be judged on group average and proceed to the next round.

Round 2 - Design document - In this round each team have to design a document  sample with the theme shared by google. 

Round 3 - Virtual Hackathon - Final teams have to represent their final solutions to a panel of judges. Team will need to share a working demo of code.

•    Price - 1. Cash prize for entire team

                      2. Pre-placement interview opportunity

• Timeline - March 1st week.

6. Microsoft Azure Hackathon - Hackathon conducted by Microsoft. The key point of this hackathon is to develop solutions using Microsoft Azure.

• Eligibility - at least the age of majority where they reside as of the time of entry

• Rounds 

Round 1 - Idea phase - This is an online phase in which participants have to submit their ideas on the given problem statements.

Round 2 - Prototype Phase - Online phase in which participants have to build their project based on the solution provided by them in the first phase.

• Price - Cash prices up to 2 lakhs.

• Timeline - January end and February

7. Amazon ML challenge - Amazon ML is a hackathon conducted by Amazon on the topics related to machine learning. Participants have to build their project using machine learning. 

• Eligibility - Degree - PhD/M.E./M.Tech/M.S./B.E./B.Tech.

            Open for third and fourth year students.

            Each team must have minimum three members.

• Timeline - April 1st week 

8. Solve for Tomorrow - Conducted by Samsung for Gen Z. Students between 16 - 22 years are eligible to take part and solve global issues with game - changing tech solutions.

• Eligibility - Individuals of age between 16 to 22.

• Price - Top 3 teams win prize money worth 1.5 crores. Top 30 teams get to attend a 5 day bootcamp at FIIT , IIT Delhi and visit Samsung offices and R&D Centres.

• Timeline - April to May

9.  Solution challenge - Build a solution to a local problem using google technologies.

• Eligibility - 

1. Should be a part of Google Developer Student Club(GDSC)

2. Students of all years can participate.

• Price - Top 3 winners will get cash prize of $3000 and feature in Google Developers Blog, global demo day live stream , mentorship with google expert , swag and certificate. Top 10 Finalists will get a cash prize of $1000 and a feature in the Google Developers Blog and global Demo Day livestream, plus mentorship with a Google expert, swag, and a certificate. Top 100 teams will get a T-shirt , certificate and mentorship from Google experts.

10. Hack4Health : Hack4Health is a healthcare hackathon organized by Apollo Hospitals, one of India's largest hospital chains. It invites participants to develop innovative solutions that can improve healthcare delivery and patient outcomes. 

• Eligibility - It’s open for everyone. 

• TImeline - May and September 

11. HealthHacks India : HealthHacks India is a healthcare hackathon organized by Health Innovators, a healthcare innovation community. It invites participants to develop innovative solutions that can improve healthcare delivery and patient outcomes.

• Eligibility - Age limit = 18 to 35 . Minimum qualification for applicants is that students should be in third year or above.

• Timeline - January 

12. Tata Trusts Social Alpha Hackathon - The Tata Trust Social Alpha Hackathon is a healthcare hackathon that focuses on developing solutions for social impact. The hackathon is organized by the Tata Trusts and the Social Alpha Foundation.

• Rounds - 

Round 1 : Online solution submission - Teams have to share solutions of the given problem statements.

Round 2 : Evaluation and announcement - Based on judging criteria, top  teams      get qualified for the next round.

Round 3 : Preparation period - Selected teams have to work on the solution of the  problem statements that are submitted in the first round.

Round 4 : Zonal Finals - There will be 4 zonal finals. Prototypes of all the teams  are judged by the jury. There will be 2 winning teams from each zone.

Round 5 : National Finals - Zonal winning teams compete in the National Final.  There will be one winning team from each zonal.

• Price - Cash price of 1.5 lakhs.

• Timeline - In mid of october.

13.  Hacker cup - Organized by meta verse. Anyone can compete in the contest if they qualify for the qualification round. Although you have to be 18 years or more for getting interview calls from Facebook.

• Eligibility - Anyone can participate if the qualify the qualification round. However, age should be 18 or above.

• Rounds - 

Qualification round - In this round participants have to solve one problem to  qualify for the next round or to take part in the hackathon.

Round 1 - In this round participants have to solve problems. Each problem has  some weightage. Based on the marks an individual scores he/she will qualify for the next round.

Round 2 - 3 hour contest and the top 200 teams qualify for the next round. Top 500 are provided Meta hacker cup t-shirts.

Round 3 - 3 hour round in which top 25 team will qualify for final round

Final round - Top 5 participants will get prizes.

• Timeline - August

14. Girls wanna code - Online challenge conducted by flipkart for girl candidates only every year.

• Eligibility - Only for 3rd and 4th year students of B.Tech/B.E./M.Tech./M.E.

• Rounds - 

Round 1 - Online coding challenge : Online coding test of basic coding contest.

Round 2 - Final Evaluation 

• Timeline - February 

15. Flipkart Grid - Campus challenge by flipkart. It gives chance to work on real world challenges of e-commerce industry. 

• Eligibility Criteria - Students of all years can take part in it.

• Rounds -

Round 1 : E-commerce and tech quiz.

Round 2 : Submission of idea and code : In this round participants have to submit their project with a video demo.

Round 3 : National Final : Finalists have to showcase their project to the panel of   domain experts.

• Timeline - June to july

16. Codegoda - Online hackathon of single round competition. Here, programmers got some fun challenges/problem statements. And can easily take home prizes worth 10,000 USD. 

• Eligibility - Coders of all levels and nationality are eligible to participate.

• Timeline - March - April

17. Swiss Re Relmagine Challenge - 

• Eligibility - B.Tech/B.E. students of pre final and final year.

                           M.Tech/M.E. students of first and final year.

• Rounds - 

Round 1 : Online assessment : All registered teams need to participate in this 30  min quiz. Based on this quiz you are evaluated for the next round.

Round 2 : Summary submission : Shortlisted teams have to submit 1 slider ppt  describing their idea in 60-90 seconds.

Round 3 : Detailed presentation submission : Selected team will have to submit a ppt of 6-7 slides describing their ideas in a little detailed manner.

Round 4 : Final submission : Submission of code and a demo video.

Round 5 : Grand final : Shortlisted teams will showcase their project to the juries.

• Timeline - August mid

These are the hackathons conducted once or twice in a week. But this is definitely not sufficient. So, here are some websites where hackathon conducts approx every week. This is the best place to dive in the ocean of creativity.

1. Dev Folio - Platform that connects developers to show their skills, build a portfolio. It acts as a bridge between developers and opportunities. It hosts different hackathons conducted by different organizations. Devfolio hosts it own hackathon and events also.

2. Devpost -  Devpost is also similar to devfolio. It allows developers, designers, and creators to showcase their project, connect with professionals, and find new opportunities. Platform for hackathons and other coding events too. In addition companies also hire people having good unique ideas.

3. Hackearth -  It’s an all in one website. Offers a range of services including hackathons, coding challenges, ans assessments, assess and hire top technical talent. 

How to Make Most Out of Your Participation??

1. Plan beforehand - Before the hackathon, research the themes, rules, guidance, judging criteria, necessary resources, tools, and expectations of the company from your project. 

2. Build a team - Teamwork is the major aspect of a hackathon so find individuals with complementary skills. Try to build a diverse team with members from different tech sides, experience and perspectives.

3. Communicate effectively - Just having an idea is not the end but it’s the starting point. Properly deliver your ideas to your teammate. Follow basic communication ethics, communicate regularly with your team, mentors.

4. Divide work - Make sure everyone is working on different topics. No work should be done twice. It will save a lot of time.

5. Focus on problem - Hackathons are all about finding solutions to specific problems. Therefore stick to the topic and try to find a unique solution.

6. Open to feedback - Hackathons are opportunities to learn and grow, so be open to feedback from team members, mentors, and judges. Work on the points where you lack this time.

7. Enjoy - Hackathons are intense, but they are also a source of joy. Remember to enjoy the journey, experience, make new connections, and learn from your fellow mates.

Enjoy the journey. All the best for your next hackathon.

Written by Shubha Prasad