Metis

I have nothing but positives to speak of when it comes to Metis.

The instructors (John, Lara, and Alice) communicate clearly, are very approachable, and have a passion for teaching data science.  Even though the bootcamp is only 12 weeks, by the end of the program you will have a portfolio of projects that you will be confident in sharing with future employers.

One of the main reasons I chose Metis was due to the harder application process and intensity of the program relative to other bootcamps.  If I was going to commit to diving into this field, I wanted to make sure I was surrounding myself with others who were just as committed, and Metis delivered exactly that.

The support doesn't end at the bootcamp; our awesome career advisor Ashley Purdy will be with you every step of the job search even months after the official end of bootcamp.  She will help with tweaking your resume, give mock interviews should you need them, and connect you with Metis alum who are working at places you're applying to.  

The classroom space itself also exceeded my expectations.  In addition to a classroom where lectures are taught, there is a huge working space for both students and alumni to work on their projects or applications, with an abundance of monitors for everyone to use.

If you have any doubts about joining Metis, schedule a tour with our program manager Caroline Csernus, who will be more than happy to show you around and answer any questions you may have! 

Metis exceeded all of my expectations. The instructors were some of the best I have ever had, and were extremely encouraging whenever I had questions (a lot) or doubted my abilities (also a lot).

 

I loved that each student could focus on their interests and skills by choosing our own project ideas. It allowed everyone to better find their niche & inform on what we want in a job, since Data Science roles are so varied.

 

I felt really prepared entering the job application process after completing mutliple career-based workshops and 3 different mock interview sessions. And, I got a job from my Career Day presentation at the end of bootcamp. Can't ask for better than that!

 

I was looking for a program that would help me get to be doing interesting work quickly, and Metis was perfect for that. 

Feel free to reach out on LinkedIn if you have any questions. I had a bunch before I started, so I understand!

I came to Metis directly out of undergrad, having done a computer science and math minor, along with some econometrics. I knew that I wanted to be a data analyst or data scientist, but was disappointed with the responsibilities and salary of jobs that I was getting offered right out of college. I came to Metis looking to find a way to break into the data science industry (use machine learning rather than being an entry level data analyst),a nd to up my earning potential. One year later, I am working as a data scientist at a place I love to work, and can say that Metis has more than paid for itself within a year. Additionally, every single person associated with Metis from the instructors, to my colleagues at the bootcamp, to the career coaches, to the founder (who still personally checks in on students during your time there) was great at what they do, an absolute pleasure to be around, and really make Metis feel like a second home and somewhere that you enjoy coming in to work despite the intensity of the courses offered.

At Metis the main things I gained were: 
1. Knowledge of all the core Machine Learning algorithms and data science concepts. This is the minimum that every bootcamp you are looking at hopefully offers to you. Metis's instructors are exceptional, care deeply about the success of their students, and are experienced in the industry so you are getting the best instruction.
2. Access to a tightly-knit network of alumni. The alumni network is very active and its easy to get in touch with the vast majority of people. This is invaluable when it comes time to search for that job. My current job I landed due to a connection with another Metis graduate. I can confirm that our program has a very good reputation within the industry as well.
3. Something to put on my resume that separated me from the rest of applicants looking to get into the industry. Most people that are looking to break into that entry level position really only have experience in school, as I did when I was first looking for a role. Being able to provide proof that I did complete data science projects, talk about what I did, and how that can transfer over to a company, is invaluable in making yourself stand out from the crowd.
4. Interview preparedness, resume, and networking skills. This is perhaps the most undervalued part of a program like this. Like it or hate it, interviewing is basically a skill set unto itself that will highly determine your salary and whether or not you get offered roles in the first place. Interviewing is all about communication skills, which is the top thing that employers are looking for in the industry today (many data scientists are awful communicators), so it is a vital skill to your career.

So that is the main benefits of Metis. In my personal experience, I have found that people who opt for online bootcamps or ML courses are generally not nearly as successful in every aspect from learning the material, to lacking that oomph factor on a resume (as it is easy to claim doing something online), to being able to communicate what they've done in an interview, to lacking the network that a physical bootcamp brings you. For all those reasons I would never reccomend an online ML bootcamp to anyone.

In terms of physical bootcamps, I can definitely say that from my experience, Metis is the leader in the space right now. It's program is very, very intensive for all twelve weeks. Be prepared to work. Every morning, you will learn from your instructors about the ML algorithms and other data science concepts. In the afternoons, you will complete a data science project led by you that implements the algorithms you are learning. Every day you take what you learn and go and apply it immediately without hesitation. The cost is a hefty investment, but in my personal experience and in the experience of every person I have asked about it, the program pays for itself within two years, and often times within one. The interviewing skills alone are probably worth 10k if you have no experience with that like I had. Additionally, you will be working in the hottest industry on the planet right now, with AI and ML seeing hefty investments all across the globe, so there is no lack of opportunity in the field. 

Overall, Metis was an amazing experience. The people there are incredible, and it a hyper focused and collaborative learning environment unlike any i have ever been in. I would sincerely recommend Metis to everyone who wants to become a data scientist but doesn't have a pathway based on their current situation

Pros:

I was looking for an intense, well-run program that would help me get a job as a data scientist, and Metis absolutely delivered. I left my previous career in a completely unrelated field, 3D animation, in March, started the Metis bootcamp in April, and accepted a job offer as a data scientist in September. I chose Metis because its lengthy track record, stringent admissions process, and overall professionalism gave me confidence that the course woud be worthwhile. The bootcamp was organized and efficient: rarely if ever was there any unnecessary downtime or logistical snafu. Lessons and assignments were well-formulated and tested without being stale or filled with obsolete information. My instructors were knowledgeable, experienced, and good at simplifying and communicating complicated ideas. Teaching Assistants, all Metis alumni, were capable and accessible enough that I frequently went to them with questions or for advice. The Metis Admissions team did a great job of assembling the group of motivated and interesting students who made up my close-knit cohort. After the bootcamp, career advisors were available for consultation and interview practice, both in-person and online. I loved my time at Metis and got exactly what I wanted out of the program.

Cons:

I have no substantial complaints about Metis so I'm mostly nitpicking or mentioning general bootcamp issues here. Twelve weeks is a really short time to turn someone into a data scientist, so don't expect to acquire a deep understanding of every topic covered. Some lessons are merely a cursory introduction to a topic that you can choose to explore in-depth outside of lecture time. Metis has a job board to connect alumni with hiring partners, but I didn't find many posts for jobs in NYC. This isn't really a negative, but bootcamps can only do so much to help you get a job; you'll have to do most of the work of finding appropriate job posts and networking on your own. Career advisors are there to help you along the way but they can't just gift you a job.

Additional Advice:

Do your research before committing to a specific bootcamp or the immersive course route in general as it may not be the right fit for you. Reading alumni reviews is a good start but I recommend going to an open house or private tour of each prospective bootcamp if you're able to do so to make sure you like both the instructors and the classroom environment. Finally, read a diversity of opinions as any one reviewer's situation may not closely resemble yours. If you'd like to read more about my experience at Metis, check out my blog posts on the subject: https://wadya.com/blog/2019/05/21/metis-pre-bootcamp-and-week-1/.

I came to Metis with a strong existing background in artificial intelligence, but having been in one job for a number of years, feeling the need to upgrade my skills and rebrand a bit as a data scientist. The 12 week course was intense and with just the right balance of theory and practice. A great deal of emphasis is placed on learning current tools in data science and on a series of five data science projects. Much of the course was structured around these projects, many of which had a particular focus such as classification or natural language. Doing the projects provided an opportunity to learn both practical skills and presentation skills. Most of the projects had practice presentations before the final presentation, giving the opportunity to get feedback on presentations of varying formality. All three instructors--Jonathan, Kelly, and Adam--did a great job both in formal lectures and in making time available for more informal feedback. In addition, considerable support was provided both during the bootcamp and afterwards in the job search. Technically, the work focused on Python with instruction in related technologies such as NumPy, Scikit-learn, TensorFlow, Seaborn, Matplotlib, VGG16, Keras, and many others. Despite the intensity of the coursework, this was not an "all work and no play" environment. For example, my cohort celebrated the completion of the bootcamp with a weekend at a cabin on Lake Tahoe, which most of us were able to get to. If you'd like to discuss Metis in more detail I'm available at https://www.linkedin.com/in/david-w-ash/ .

If you are considering a bootcamp option for your career trainsition into data science, some will tell you not to waste your money since there are many free courses online. And yes, this is true if what you are looking for is just learning data science/machine learning concepts and become one of big pile of lackluster data scientice practitioners. 

However, what you WILL get out of data science bootcamp is not just learning about concepts, but being a true data scientist who thinks and acts like one. Through rigorous and well-structured curriculum, you will be comfortable breathing data science and be employable upon your graduation. You will learn how to complete end-to-end projects that employers love to talk to you about.

For me, career support and giant network of Metis alumni was what sold me to Metis. You will work with career advisors throughout the bootcamp and after bootcamp until you land a job, and their support has been best in class and superb. Career advisors showed true passion and interest in my success. Also, because all graduates from Metis are phenomenal and employed in top companies, they are essentially branding for you. 

To be honest, I was a little skeptical of how much I will get out of bootcamp, but now I can tell you with confidence that you will get so much out of it.

I recently graduated from Data Science full-time Bootcamp. The Bootcamp opened my eyes to learning what is state of the art of Machine Learning and Deep Learning. I had a great experience with career coaches and instructors. Everyone deeply cares about the student's learning experience. I gained a good understanding of stats and all the machine learning models. I graduated two weeks ago and I got three requests for on-site interviews. Definitely open a lot of doors for me. It is sad that they are closing Seattle Metis office. Everyone there did a tremendious job. 

The Decision

Deciding to transition my career from mechanical engineering and robotics to pursue data science was one of the hardest decisions I've ever made. Attending Metis made that process worlds easier than it could have been, however, and I haven't regretted it for a second.

Research

Before enrolling in Metis, I spent months considering all of the options available to me. I researched other local data science bootcamps like Galvanize and General Assembly, as well as online platforms like DataCamp, Dataquest, Udemy, Udacity, and others. I studied, I toured campuses and talked with instructors, career advisors, current and former data science students. I did my best to weigh all the options and make an informed decision, and the process led me to select Metis as the best option available to me to help me successfully transition from where I'd been to where I wanted to be.

Preparation

For personal reasons, I actually deferred starting at Metis by about 6 months after I applied, and in the grand scheme I'm glad that I did. Metis allows students enrolled in the full time data science immersive program to also take a part time online course of their choice for free, so during those 6 months I also took their Statistics for Data Scientists course, which was a great warm up for the challenges to come. I also used this time to complete the Data Scientist curriculum offered by dataquest.io, which I found to be an overall well designed and nicely presented overview of just about every topic that's covered by the Metis DS immersive (this took me about 5 months to complete, dedicating ~10 hours a week to the study on nights and weekends). This was a lot of upfront work, but quitting my job to move off in an uncertain direction seemed like a big risk so I took it seriously. This allowed me to gain a nice foundation of knowledge to build off of while still saving up for an extended period of unemployment, and definitely paid dividends once the bootcamp started.

To anybody thinking about enrolling in a DS bootcamp down the line, I strongly recommend completing an online course first, both to make sure you actually like the work and also to familiarize yourself with the content so you'll be even more successful in the bootcamp experience.

The Bootcamp

The Metis Data Science Immersive was great. My cohort had a particularly small class size, only 6 students with 2 full time instructors, 2 occasional visiting instructors, and a very talented and dedicated career advisor. The staff exceeded my expectations on a regular basis. They're knowledgeable about a wide range of material and are passionate about teaching their students the skills they'll need to succeed. The program is specific to data science, but designed to be flexible enough to approachable and valuable to students coming from a wide range of backgrounds and abilities. The material is taught with a nice combination of theoretical background and practical application, and the project-based nature of the course really makes the level of challenge a function of the student's appetite and ambition. Each project is as hard as you want it to be, you get out what you put in, and your peers and the instructors are there to help and support you every step of the way.

In terms of the level of challenge--everybody's experience and background are different, so I can only speak for myself--for me, it was challenging, but manageable. More than anything, it was intense. For the 12 weeks that the course lasted, I largely put the rest of my life on hold and worked ~80 hours/week on my projects and the curriculum. I was still able to maintain at least 6 hours of sleep most nights, but I was definitely dreaming about my work. The bootcamp was an endurance marathon, for sure. Not quite as bad as the worst parts of college, but close.

But then it ended and I was on the other side. Not only had I shored up my working knowledge of supervised and unsupervised learning, Pandas and scikit-learn, the difference between CNNs and RNNs and LSTMs and more, how to detect overfitting or design a metric or select a model, how to scrape data from the web or deploy a model in a web app--I'd actually done all of these things, and had full projects complete with code, presentations, and blog posts forming a highly visible portfolio that I could use to demonstrate to future employers that I actually know how to do the things on my resume.

What Comes After

The bootcamp is only 12 weeks, and much as it's all you can focus on while you're there, it's the means, not the end. I still had to get a job. While I'd saved up enough beforehand to survive an extended job search, I didn't actually want to drain my savings, so I jumped right in. I set a goal of starting a new job within 3 months of finishing the bootcamp and thought about what it would take to get there. I'd heard it was common for it to take 4-6 weeks or more from application to offer, and the common impression I got from talking to bootcamp grads is that you may well end up submitting dozens or even hundreds of applications before you actually get an offer. In short, finding the right fit is a full time job, and even getting your foot in the door enough to have a conversation with a potential employer takes intention, persistence, and a bit of creativity.

Here, however, is where Metis shines as well. The career counselor, Marybeth, as well as the instructors, were involved and supportive every step of the way, constantly checking in and offering help with everything from resume and cover letter reviews to practice interviews to job referrals and facilitating introductions. As long as you're willing to work, they're willing to help. I took advantage of all of these things and I think they paid off. I aimed to apply to 10 new jobs per week, and though I fell short of that goal, aiming high kept me active. It was slow getting traction, but eventually the pace picked up and I found myself juggling calls with recruiters, scheduling interviews, and having to meticulously track each job application in a spreadsheet to keep it all in order.

I feel fortunate to say that, somehow, my job hunt went pretty much exactly according to plan. 7 weeks after finishing at Metis, I accepted a job offer as a data scientist with a focus in computer vision. I'm genuinely excited about both the work and the company, and the skills and support I got from Metis were instrumental in getting me here. Huge thanks to everybody at Metis for all of the help, and best of luck to everybody out there considering a path like this for yourself!

Last year I felt totally stuck in my job, sitting at my computer reading review after review of data science bootcamps. I had a math and stats background, but no real programming knowledge/experience and really needed a sign that this was the right path for me. If this is you, LET ME BE YOUR SIGN. 

Metis was truly one of the best decisions I have made for myself and my career. Sure, I could have learned all of the material on my own outside of a bootcamp, but I am the type of person who needs structure, deadlines, and accountability and Metis gave me exactly that. But they didn't stop there! They brought me a huge network of like-minded people with varying backgrounds in a collaborative and supportive learning environment. 

The bootcamp was by no means easy, I definitely spent some late nights/weekends working on projects and reviewing material, but if you put in the effort you will learn a ton. I spent several months before the bootcamp not sure if I was ready/qualified to apply. I think the most valuable prep for me was the part time Intro to Data Science course offered by Metis which not only gave a good glimpse into the bootcamp material, but also gave me the confidence to apply right after (and the class is basically free because the cost gets applied to the bootcamp!)

The projects at Metis totally revamped my resume and the career support was extremely helpful. After bootcamp, they connected me with several interview leads specific to my interestes and qualifications.

Overall, if you're looking to get familiar with different ML algorithms and gain lots of Data Science job applicable skills quickly, I definitely recommend applying to Metis!

Metis was life-changing and worth every penny. Great course materials on everything from absolute basics to current state-of-the-art machine learning. Committed Instructors who really care about teaching and helping you succeed. Super smart classmates to collaborate and learn with. Tons of presentation practice opportunities which helps boost confidence. Career support from a million different angles, like networking events, technical mock interviews, resume workshops, and guest speakers. At the end of the day you get out of it what you put in, but if you're willing to work hard, and you have the aptitude for the topics on their entrance exam, Metis gives you everything you need and more to land your first job as a Data Scientist. It's certainly possible to achieve this in other cheaper ways, but with Metis you can be confident you're staying on track, staying motivated, and covering all your bases in one intense, neatly packaged 12-week sprint.

I had a great experience with Metis. I was looking for a fast-paced, in-person way to transition from a job in survey research and data analysis to a more coding- and ML-focused data science career, and it absolutely delivered. It was also a ton of fun!

Pros: 

• Amazing instructors. They know both the theory and the practice of the material they're teaching, and they were always happy to help me work through some weird problem or just figure out what to do next. 
• I loved the project-based curriculum, where I had to do everything yourself: pick a topic, find the data, plan everything out, build a model, make it better, figure out how to present it. I could work on stuff that actually interested me and I had real ownership of the product. At the end of the program I had a real portfolio of stuff I was proud of, not just a list of skills. 
• Focus on presenting. Two to three weeks of project work needs to be condensed into a four-minute presentation, which is tough! At the beginning of the program I thought I hated presenting slide decks, but after five chances to get better at it, I actually really enjoy it. 
• Excellent career support - LinkedIn and resume workshops, mock interviews and whiteboarding practice, great alumni network, and unlimited post-graduation support. They really, really want you to get a job. (I received and accepted a great offer exactly a month after graduating, from a company that saw me present at Career Night.) 
• The challenging application process means that all of my peers were very smart cookies. I learned a lot just from finding out what other students were doing. 
• Tons of extra material available if you want to dive deeper into any particular topic that interests you.

​Cons: 

• The rapid pace means that all of my projects felt (to me, at least) a little unfinished - there was always some more I wanted to do, but the presentation deadline always hit so fast! I feel like I could have done one less project if it meant more time to work on the others. 
• The focus on preparing for a job means that some interesting topics aren't covered in as much depth. For example, you'll learn the basic theory of deep learning and neural networks, but they don't spend that much time on it, because companies don't really hire boot camp grads to build deep learning systems. 
• The curriculum is constantly under development (which is good!), but that meant that there were occasional inconsistencies, like programming challenges that didn't always exactly relate to what we were covering that week.