Metis

I chose to write my review one year into working as a data scientist to give an honest assessment of my experience with the program from the perspective of an actual data scientist, not an aspiring one. My honest assessment is this - you can go into Metis with literally no experience in data science and be employable by the time you graduate. I shopped around a lot for the boot camp that I believed would give me the best shot at getting a job by three criteria - hands on instruction, one on one availability, and curriculum. Metis did not disappoint in these areas; instructors always made themselves available to help with a project or a lecture that I couldn’t quite grasp. They also did a great job tailoring their instruction to the vast audiences present in the boot camp (fresh math PhDs vs those of us who hadn’t taken a math class in 8 years) and taking feedback when things weren't clicking.  As for the curriculum, I think Metis provides a great foundation for machine learning specifically. While it’s true that in my first role as a data scientist I’m doing little machine learning and mostly working in SQL, having an impressive portfolio filled with machine learning projects on my CV is what got me all of my job interviews. Another important part of Metis’s curriculum is how their lectures are rarely disambiguated; they teach every lecture within the context of a project meant to solve real world problems with data science. This was especially helpful for both remembering the content and applying techniques in my first job. In conclusion, I couldn’t recommend Metis enough. It will still probably be hard to land your first job, but choosing this boot camp will both prepare you and make employers look twice at your CV. 

Metis was overall an amazing experience. From the application through graduation the staff and instructors were supportive and responsive! The course content was well designed and mostly clear. The most valuable part of the Metis experience was the peer support and 1:1 instructor/TA meetings. My peers and I still keep in contact for job searching job and networking. Additionally, the 1:1 feedback from TAs and instructors was pivotal to my learning. I also really appreciated the post-bootcamp careers support. This was importance to get advice/feedback throughout the job search process. 

I had an incredible experience at Metis.  The program is a rewarding experience if you are up for the challenge.  

Admissions: It will require you to have a bit of python experience (Metis offers an Intro Course that is perfect for beginners) so be sure to practice coding on one of the many resources out there and to brush up on basic statistics and probability. And if you feel like you need more practice, Metis lays out pre work to cover any areas you may need a bit of reinforcement in.  The admissions team is extremely responsive and will work with you to make sure you are in the right program and have a great experience.

Program: The topics were broken up into digestible modules that start with exploratory data analysis and build into more complicated data science and machine learning content.  The teachers are world class.  Some with PHDs and others with elite educational and/or professional experience, many of the teachers having nearly a decade of data science background.  Each week includes pair programming challenges to continue to refine your python skills, engaging lectures with quizzes to reinforce learnings, office hours and time to work on module project deliverables.  Both the teachers and the teaching assistants are extremely helpful at working with you to instill concepts and help apply concepts to your personal projects.  In addition, your classmates, Metis faculty, the careers team and admin teams become your second family.  Make no doubt, the program is challenging and requires hard work, but you can be successful whether your fresh out of college or an experienced professional looking to pivot into a data science career.  The diversity in experience within my cohort and the teaching staff made for a well rounded experience that opened my mind to different view points, ideas and solutions both in programming and professional situations. 

Career Services: A+ ... Jen and Ashley are truly incredible as career advisers.  As part of your program we had nearly one speaker every two weeks, all former Metis alumni working in finance, sports, government, entertainment, consulting and information technology to name a few.  The careers teams also has a couple of introductory sessions to help plant the seed on how to begin working on your resume, networking and use the Metis network.  After the bootcamp, you have an entire week of workshops with career teams including mock interviews both technical and personal, resume polishing and advice on how to attack the job search.  The Metis Alumni community is truly incredible and almost always willing to lend you an ear whether it be for things like interview advice or looking for a role.  Many of my job leads came from Metis Alumni either posting or referring me to roles.  Jen was instrumental in helping me get more "cold call" resume submissions into interviews than I had ever had previous to Metis. Not to mention, there are firms where I knew what questions were coming from the preparation I had done with the careers team. There were even some places where I skipped a round of interviews because I went to Metis and the company knew the standards the program has for itself and its students abilities. Jen helped me negotiate multiple offers which resulted in higher pay and getting a fantastic role, all within two months of graduating the bootcamp. 

I chose Metis because of the career support, network, and job portal. The curriculum is good but because every module is 2 weeks some of the modules felt rushed and some felt dragged out. The instructional and career support are great. There are 2 instructors and 2 TA's for each module. They all have multiple time slots for one-on-one office hours. If you don't understand something or need help with your project, there is always someone available to support you. The instructors are familiar with the subject matter but it depends on their teaching style. I had one instructor that I really understood and learned a lot from. There were a few instructors that was easy to talk to. I did find that towards the end of the track, the slides had less text and the instructors would lecture on a topic using only one picture for 30 minutes. For my personal learning style, I find this a bit more difficult to understand the concept. 

The Metis DS bootcamp was life-transforming, in the best sense. Perhaps no other three-month period in my life was so distinctive. It was tons of hard work, which I always felt glad to do, all day, late into the night, and most of the weekends too. (If there were more than 7 days in the week or more than 24 hours in the day, I would have spent the additional ones on the bootcamp work.) Ok, so I’m already unusually inclined and motivated to learn (I had a PhD already) and I’ve been keenly focused on learning situations for years (taught college for a decade) but I believe my perspective is relevant to anyone contemplating diving into a Data Science bootcamp. 
I carefully chose Metis because of its curriculum, standards, and reputation, as well as the fact it has a careers team (to help with the job search). I was not disappointed in the least. First of all, the best thing about bootcamp generally—which probably can’t be replicated any other way—is the variety of events, activities, and tasks that center around and circle around the subject (actually each subtopic). This was ideal for learning. For instance, often in the morning there would be a relatively small-scale one-on-one problem to work on for 45-minutes or so to build up a toy version of an algorithm from scratch (these “pair-programming” exercises nearly every day were _great_—so much so that some of us continued doing it a few times a week even after bootcamp was over); then a couple of hours later the same day (or sometimes the day before) there would be a one- or two- hour lecture on that same Machine Learning approach, and then later a workshop-ish lecture to get your hands dirty using the scaled-up industrial-strength pre-packaged (not from scratch) version of that algorithm. This meant that we learned how the engine under the hood actually worked so we would become skilled enough to tune it.
The lectures themselves were of various styles by various instructors, which again was bonus. (A uniform or cookie-cutter approach, or having only one instructor, would have been disastrous.) Although doing a bootcamp online (via zoom) might seem like a disadvantage, we turned it into an advantage. by intermittently having on-topic side chats, sometimes with apropos hyperlinks and diagrams posted, questions asked and answered (by the instructor, the TA, or other boot-campers) and the occasional witty nonsequitur for levity to keep the mood light—given the intensity of the material! There were many times when it was surprisingly thrilling. One of the reasons for this also is that people are coming into the bootcamp with such varied backgrounds, so the kinds of questions asked were all over the map; and some bootcampers came with their own expertise (in math, stats, comp-sci, probability, etc.) so they could sometimes contribute added nuances to the instructor’s already expert explanations. The mood and tone was always respectful and collegial—which can’t be taken for granted.
The project-based structure of the course was also ideal because we were grasping to master the lecture/workshop material in order to be able to implement it right away in the individual project we were working on for the given two-three week period, with that deadline looming. I got a taste of all the steps, from locating data, to wrangling/cleaning it, modeling, testing, interpreting, and building up a presentation that would be scrutinized by my instructors and peers. The day-to-day flow of the Metis bootcamp meant becoming fairly fluent with professional tools like git and fluent in installing and learning unfamiliar python packages needed to complete your own particular project.
Learning DS and ML is complex enough that it entails the potential for obstacles at nearly every step. (You better be brave. LOL !) Nevertheless, it was completely possible to always push forward because of the Metis setup: an incredibly active Slack channel (for posing and answering questions and sharing code and hyperlinks), the availability of TAs (for help via screen sharing), and an increasing sense, as the bootcamp progressed, of where and how one could seek and find (or build) solutions on one’s own.
One of the highlights of bootcamp was when the architect of Metis’s curriculum (the Metis mastermind herself) Sophie Searcy came in to guest-teach us on the topic of Singular Value Decomposition (a subtle topic of Linear Algebra that happens to be important for certain aspects of Data Science/Machine Learning). Another highlight was when Kimberly Fessel (who was _not_ one of my cohort’s instructors) came in at the end to give us (four at a time) a mock-technical interview, gently quizzing us on how to create from scratch a classification algorithm we had learned two months prior.
The variety of instructors had different emphases, different strengths, and sometimes didn’t completely agree, which is realistic, and gives a better sense of the actual kinds of divergence you’ll encounter out there in the DS world.
The instructors were great:: intense and serious about the subject matter, but also capable of being light-hearted at the right times. My main instructors were Vinny Sanguttuvan and Leon Johnson.  Leon’s lectures were clear, with a definite sense of priorities distinguishing the overarching point from the supporting detail.  Leon also provided excellent practical critique on bootcampers’ presentations, things that I still contemplate and consider vividly five months after bootcamp ended. Based on the particulars I had achieved with/through a given project, Leon was unique in suggesting next steps built on these and directions I could take that would further burnish my portfolio. Leon obviously has a firm overview of the DS landscape, is clear communicator, and encouraging mentor. Vinnie Sanguttuvan is one of the most dynamic and insightful teachers I’ve ever had (comparing to dozens of other great teachers I’ve had in college, grad school, as well as tech training courses). His teaching kept me and other bootcampers on our toes from start to finish. Nothing was ever routine or rote, but rather presented us challenges we had to carefully consider. Sometimes Vinny did this through Socratic-method, where he would pose a series of questions (or mini-problems) that would interactively lead to an insight, which therefore would stick. Other times he would relate mathematical/algorithmic/statistical principles to observations he had personally made about well-known tech industry products and services.  When Vinny was teaching, often you really had to think through mathematical or algorithmic concepts, and problem-solve on the fly. He is also very open minded about what types of problems might be tackled with algorithmic methods.  Vinny’s teaching presents a distinctive synthesis of creativity and precision that epitomizes what is most exciting about the Data Science field. 
I want to emphasize that while Metis’s excellent curriculum is one of the reason’s I’m glad I chose it, the most important learning events for me were the moments when the instructor cooked up his/her own problems or reflections for us to consider; these complemented the pre-cooked curricular material. That is to say, there was a mixture of very carefully planned out lessons and more spontaneous ones originating from the instructor’s creativity. It made for an exciting and engaging bootcamp, when you could sense that what and how you were learning was unique to that moment and context. (This was especially true with approaches to the pair-programming problems). I hope that Metis continues to allow seasoned instructors latitude in how they teach, including creating their own material from time to time.
Another instructor I want to mention is Dimitri Theoharatos, who taught python-and-math course I took a year before the bootcamp.  Dimitri moved quickly and efficiently, while also overflowing with a wealth of practical tips and laser-like precision. He peppered his teaching with astonishingly apropos industry insights of his own, giving me perspectives that sill condition my thinking a year later. I learned as much from carefully observing how Dimitri navigated the nuts-and-bolts of the python programming interface (jupyter notebook) as from what he verbally articulated. 
All the Metis instructors listened carefully to students’ questions.  They seemed to appreciate they were dealing with many intelligent and motivated bootcampers, so they calibrated their responses accordingly, never resorting to generalized rote answers (as sensitive teachers might be prone to do).
The camaraderie among bootcampers was inspiring and encouraging.  One thing that was incredibly clear after bootcamp ended:  Metis alumni help other Metis alumni, especially Metis alumni from prior cohorts. In the brutally frigid world out there of cold applications to jobs, the Metis alumni network is indispensable; it’s how I got most of my interviews, including the ones that led to me landing two simultaneous job offers.
Especially if you’re coming from an academic career, or this is your first job search, the Metis careers team (I worked mostly with Ashley) can be helpful in steering you what might be unfamiliar terrain of the corporate career landscape.
Before bootcamp: To make the most out of this experience, I recommend you prepare extensively.  Try to use Codecademy and Dataquest to learn Python and SQL before the bootcamp. Use Brilliant.org to learn basics of linear algebra, probability, stats, and calculus. (If you’re going to splurge on the bootcamp you might as well purchase memberships to these so that you begin the bootcamp with your best self. I used these further _after_ bootcamp as well.)  As many others mention in their reviews (of Metis and other bootcamps) the amount of material coming at you in the bootcamp is like a firehose to your mind, which you can absorb better to the extent you prepare in advance. If you get your feet wet with Brilliang.org, Codecademy, DataQuest, and the Metis python-and-math, you will be ready even if you don’t come from a thoroughly STEM background. During bootcamp, expect to spend all evening every weekday as well as a large chunk of weekends working on your bootcamp projects. Metis DS bootcamp is not a side activity; it’s a life-changing process. 

# Preparation

Before you apply I recommend you do as much of the following as you can:

* Take a college-level intro to matrix algebra course (and any pre-req's required to pass that course)
* Acquire introductory level python programming skills, but if you want to build web applications then learn OOP with Python and get some Flask under your belt. There are alternatives you'll learn in the class.
* If you can take a class on machine learning and deep learning before you enter the bootcamp, please do so. 
* Basic statistics and probability theory
* Basics of how to use git and github
* Basic paired programming skills

You can make it through with not all of this in place, but you may experience a lot of stress making up for any areas where you lack basic knowledge in any of the above areas. 

I wouldn't join this bootcamp if I had 0 python or 0 linear algebra knowledge even if admitted. The others maybe you can make do without them going in as you will get exposure during the bootcamp.

Metis provides a scholarship for traditionally under-represented people who are accepted into the bootcamp.

If you are admitted into the bootcamp you will be provided intro material. The more of that material you complete before the bootcamp the better your experience will be during bootcamp.

# While in Bootcamp

Our bootcamp was 100% online over Zoom. This was great, as I was in the bootcamp when shelter-in-place orders were in effect. Glad they were flexible! The bootcamp was only 3 months long. Even though it was really tough, it beat a 2 year $50,000 full-time masters program from a time/money perspective. 

Time is of the essence. This bootcamp requires at least 12 hours per day of effort (6 of it is mandatory lecture the rest is the time you'll need to execute your projects). It's not a good idea to do this bootcamp and hold a full-time job. Working on Metis material during weekends is a good idea, especially if you have a project that goes sideways and you need time to recover it.

The instructors are very patient. They're willing to repeat concepts in lecture, hold extra lectures, along with once-per week scheduled office hours. Instructors also do technical interview prep and offer quizzes at the end of bootcamp to help gear you up for job interviews, which will be technical. 

The course material is really good: It gives you the gist of a lot of very large complex libraries (like matplotlib) which are good introductions to these things which can serve as a jumping-off points when you want to do more complex stuff with them. Also weaves knowledge of effective  ways to use these libraries to do data science that may otherwise may be hard to discover.

There is career development material provided to help you to effectively network and traverse the interview process. The career development personnel will meet with you 1-2 during bootcamp for career development training.

Projects involve delivering strictly time-bound presentations. If you go 1 second over you can lose points. So prepare,prepare, prepare for your presentations.

There are plenty of extra lectures like how to setup a GCP instance for data science, and introduction to complex machine learning models like BERT and GPT-X. 

They are open to feedback and are willing to adjust the program when students experience excessive pain due to a "bug" in the program and are willing to provide honest feedback in one-on-one conversations. They're not here to grab tuition money and socially-promote you, they're serious about making you into a competent data scientist.

# After bootcamp

You will continue to receive support from career development folks. They will help you write your first resume that includes your bootcamp experience, and directions on how to update your LinkedIn profile.

Guest speakers who work in data science drop in to talk about work, offer career advice, and may be pathways to a job.

There are a lot of companies that recruit graduates out of this program, and that's how I got my first data science job. You can apply through a Metis alumni web site to opportunities from these companies or you may just get a referral.

My cohort was very cohesive, which really helps take the edge off this challenging program. Be in the mode of giving and not just getting and you will grow from the experience, IMHO. 

# Places Where the Program Could Improve

They should incorporate code review into the program as you will have to go through that in the real world and it may be a big learning curve to jump over on first exposure. Udacity MLND had code review which was helpful in improving my python programming skills. I understand this may make the program longer, and may be a trade-off.

An introduction to causality would be helpful. A lot of companies are looking for that skillset.

I hope they can regain accreditation (If this hasn't already happened). 

Metis was a great experience. The instructors are wonderful and you’ll make great connections and friends with the other students. You’ll have to work a lot over the 3 or so months of the course but you’ll learn a ton along the way. Metis’ career support is also fantastic. That with access to the alumni network can go a long way to helping you find a job. With that being said though you should plan on spending several months after the completion of Metis searching for jobs before realistically expecting to land one. It’s competitive out there and while Metis will give you a leg up it’s not a replacement for either some previous technical background or domain knowledge/experience in your industry of interest (technical or not). If you have one of those two things, are willing to put in the work during and after the program, and you can afford going 6+ months without a job, then I would definitely recommend it.

The course structure was great. I had some data science exposure in university (~40 hours total, 1 project).  The Metis bootcamp was around ~400 hours over the 10- weeks with 5 2-week sections and one project for each section.  The instructors were really great and had high expectations of students (we graduated with about 50-60% of the original program participants, although the ones that didn't pass got to retake sections).  I would recommend taking the Data Science and Engineering bootcamp instead of the Data science bootcamp (four of the five sections are the same but the one section that they don't share seemed more relevant with Data Science Engineering based on talking to other students).  Really would recommend this program, but I would caution those of you with very little python exposure or technical backgrounds.

I found my time in Metis to be challenging but incredibly rewarding. Prior to Metis, I worked in management consulting so I had very little background in data science. The skills I gained through the programme enabled me to get a data science role a month after graduating from the bootcamp. 

ADMISSIONS: Rigorous process but the Admissions team was supportive throughout the process. They provide guidance on what to expect for the testing / interview process as well as materials to help you prepare. 

PROGRAMME: The curriculum was robust and well structured. Each module built on top of skills learned in the previous module to deliver a strong, incremental learning process. The instructors were amazing - I thoroughly enjoyed learning from and engaging with Vinny and Leon. Fortunately, you were able to book 1:1 time with instructors for as much as you needed, which really helps the learning process. The Teaching Assistants were also incredibly engaged and supportive. The peer element in the programme is also so important! Because of the programme's focus on skill level and cultural fit (collaborative, not competitive), you really feel like you are a part of an awesome community of smart, kind and supportive people! 

CAREERS / POST BOOTCAMP: Engaging with Careers for input on my CV, interviews, and negotiating process was so helpful! Ashley provided a lot of advice and insight on what to expect as I progressed through my job search until I received the offer.

After several years in finance, I wanted to pivot my career towards data and decided a bootcamp would be the fastest and most direct path to that goal. I think the core benefits of a program like this are (a) outsourcing the time and decision-making of curating a curriculum, (b) cultivating a data science community, and (c) making a commitment in terms of time and finance to learning the material, getting hands on practice, and finding that next job. While evaluating different programs, Metis really stood out from the others. Here's an unordered list of things I learned throughout my experience that may help you decide if this program is right for you: 
- Admissions process was the most rigorous, which means you'll spend more time in the program learning and implementing advanced concepts.
- Similarly, your cohort will be filled with highly intelligent, driven students to collaborate with. Metis is highly selective and prefers collaborative over competitive. I found my fellow students to be extremely generous with their time and ideas - we formed study groups outside of class hours, and supported each other in any way we could during the job search after. 
- The faculty is truly amazing - the teachers, program managers, and career advisors are all invested in your progress. 
- The capstone projects really stood out to me when I was comparing different programs. There are some really exceptional projects all around, but those from Metis students were on average more captivating .
- You'll get access to a large network of alumni and hiring partners. I found alumni to be very supportive -- reach out to folks on slack or linkedin, have a conversation, they'll often make referrals. Again, it's a very collaborative community!
- While I was evaluating different programs, I reached out to alumni from each. Look at their career progression, ask about their experiences. I found Metis folks on average to be more enthusiastic about their bootcamp experiences than those at other programs. 

There's plenty more I could say, but I think this captures the main ideas. I found Metis to be an integral part of my career transition and would highly recommend it to those with the means. Please feel free to reach out via linkedin if you want to chat more or have any questions!
 

Metis delivered on all my expectations. I decided to explore making a career transition to Data Science after working as a postdoc for 3 years after completing my PhD in Political Science at Cornell and feeling less than satisfied with my academic career prospects. After teaching myself some basic Python and brushing up on my linear algebra, probability and statistics (I had done a minor in Math in undergrad just for fun but that was over a decade ago and all my Poli Sci research was super qualitative) I decided to enroll in the Intro to Data Science course in June 2020 to get a better sense of my aptitude and whether or not I would like this kind of work. The Intro to DS course provided me with a nice overview of the field and the opportunity to complete an end to end project which gave me the confidence to apply to the full-time 12 week bootcamp starting September 2020. 
Metis was the only program I applied to as I was most impressed by the fact that they are the only accredited DS bootcamp, have very high quality instructors, a robust alumni network, and career support until you land your first job-and even after!
I found the program both incredibly rigorous and wonderfully supportive. Honestly, the coursework was as demanding as my busiest times in grad school, however, two things were really different about bootcamp. One was the number of opportunities I had for 1:1 support. I had at least one weekly meeting with an instructor (often twice a week!) plus another with a TA. This definitely exceeded my expectations and left me reassured that even if I felt in over my head at the deep end of the swimming pool, there was always someone there to help me refine my project ideas, better understand a new library or just reassure me that I was on the right track. The second was that the breakneck pace actually protected my from going into perfectionist mode. Metis really drives home the concept of the MVP (minimum viable product) which was something I had not previously been familiar with and totally revolutionized the way I thought about my work. Yes, I still spent many a late night and weekend trying to make each of my projects the best it could be, but with only two weeks to complete each one, I was so focused on making sure that I had something complete that there was no time to waste worrying about the ways that it wasn’t perfect and in the end I am incredibly proud of the portfolio I built. 
I would absolutely recommend this program to anyone interested in transitioning to Data Science but you absolutely must be ready to put in the work and take ownership over your own success. Enrolling in Metis makes an incredible breadth of resources available to you, but its up to you to actually use them, sign up for 1:1’s, ask for help etc. Trust in the program! Also, the time investment is no joke, I worked about 3-4 additional hours a day after the day formally ended and put in time on the weekends too so do make sure that you have a good support system in place to keep on top of ‘life stuff’, making dinner etc. That said, after the 12 weeks are over you do get your life back :)    
In my cohort I was among a small handful of people who hadn’t previously worked in *some* form of data/analytics role or STEM background. However, given Metis’s rigorous admissions standards, I knew that I had what it would take to succeed. To be sure, there was a steep learning curve, moments of imposter syndrome and being so new to coding I never felt totally comfortable with pair programming (which is something Metis could do better to manage in the online format tbh) but I did come to better appreciate strengths of mine that I had previously taken for granted like knowing how to give a good presentation or not being afraid to ask a question during lecture. Bootcamp is often described as ‘drinking from a fire hose’ and this is apt, but, the great thing about Metis is that you still have access lecture recordings for 6 months after bootcamp if you want to review material that you didn’t fully grasp the first time around (which has been super helpful while gearing up for technical interviews) as well as lifetime access to all the course material that is on GitHub. The instructors provide such a wealth of required and supplemental materials that I have had the opportunity to further dive into as needed in the months since bootcamp and feel like I am continuing to get extra bang for my buck! 
My fellow students were also an incredible asset. Despite doing everything virtually, we still had the chance to really bond and after bootcamp ended I’ve stayed in touch with a number of classmates to give each other support on the job search. Likewise, I have found Metis alum to be incredibly generous, willing to take informational interviews and provide referrals for a number of job leads.
I also want to give a *big* shout out to the careers team. In my first meeting with my advisor, she asked me what I wanted to get out of working with her and I said, honestly, I’m committed to doing whatever work I need to do to get a job but I’ve never applied to a non-academic job, I feel so out of my comfort zone and really just need someone to hold my hand through the process. And boy did she ever! After graduating in December and taking a little time off, once I was ready to begin searching for jobs full time we had weekly checkins over Zoom where I could ask all of my questions about reaching out to recruiters, talking to hiring managers, preparing for technical interviews and felt so supported and encouraged through the inevitable ups and downs. Additionally the other careers counselor was also available to for guidance while my assigned counselor was away and she would even periodically check in to see how I was doing. Big, big gold star to the careers team! 
Now I can proudly report that only 12 months after I first started learning Python and about 4 months of job searching post-bootcamp I landed an incredible job as a Senior Data Analyst making a salary 3 times higher that I did as a postdoc. There is no way that I could achieved these results on my own, and probably not at another bootcamp program either. The investment I made in myself enrolling in the Metis bootcamp has paid for itself many times over. If you're ready to do the work, I cannot recommend this program enough! 

If you're not sure which review to trust because you're not sure which shoes you fill out, hear me out for just a moment. I'm a bioengineering student. Coding, let alone data science, was a world away for me. I barely knew there was a science to data. But with the continuous support of the instructors, and then the diligent career advisors even well after the bootcamp had ended, I went from mean, median, mode, to creating full-fledged end-to-end projects, even in my own time. Metis is a revolutionary experience, but you'll have to put in the hard work to make the most of it.