Metis

I would highly recommend this course to individuals who, like myself, come from a traditional science background. I can say without doubt that this program helped me kickstart my career and provide a level of credibility--which is important when recruiters are questioning your lack of a computer science degree. I would think of Metis as an internship, dedicated learning environment for all things data related, and an opportunity to feel part of the bigger San Francisco big data community.

Please feel free to connect with me on LinkedIn if you would like a deeper dive on the program. I don't bite!

Before attending Metis I'd done a one week bootcamp and tried learning more data science by myself but struggled to know who to turn to when I get stuck and also didn't really know how to approach the plethora of resources on the internet. Metis gave me:

a) the skills across a fairly broad base of topics;

b) the confidence and 'knowing how to learn' to go away and learn by myself;

c) access to a brilliant careers team;

d) a community of people to ask for help and support!

You complete 4-5 projects to practice a range of skills and can tailor those according to your interest. This approach really suited me from the perspective of being able to explore something of interest for a limited period of time.

 

I am an architect and a Transportation Planner turned Data Scientist(may be junior) through Metis. That statement itself should say a lot about the bootcamp, but let me go into details. Although I had worked on statistics and modeling techniques for analyzing travel patterns in cities, I was not equipped with the tools and techniques needed in the industry of Data Science and I was very nascent with the coding skills. I was very excited about learning all these, given the kind of change Data Science was  bringing to the Transportation industry (basically, I knew the application of the skills that I would acquire). Just now, I work as a Senior Data Analyst(using technologies like Pyspark and Hive) at Apple Maps through Wipro.

Metis has been instrumental in providing me with Data-Science related concepts as well as hands on experience on those skills in quite a short amount of time. The mix nature of every cohort with some similarly passionate, hard working and fun people also helps a lot with growing and learning. I got admitted into other Data Science bootcamps also, but the curriculum of 5 hands on projects really made me more interested in Metis. Although, I had my doubts of not being able to learn so much just in 3 months, Metis has actually shown me that it's possible ! I was learning coding as well as data-science courses online but it would have taken me a lot more time to be able to reach where I am, without Metis. Being gone through those projects in Metis, sometimes I still go through my projects/lectures to help myself in the work.

Paul and Joe as instructors were technically equipped to answer all my questions and help me out through the challenges that I went through in my projects. The way they used to engage with us on Fridays, with all the games and fun made the bootcamp kind of a course easier to go through. One more interesting part, is the alumni network offered by Metis. It is and will always be useful to be connected with Metis people. 

Metis could have concentrated more on the time-series analysis and A/B testing part as that is a major requirement in interviews of Data Analysts atleast. Also, I feel that Metis can be more involved even after the bootcamp for may be 3 months to make students have a more guided interview process. 

Where one can end up after Metis: 6 months after the bootcamp, my whole cohort was placed pretty well in good companies. I would say, with passion, a lot of hard work, little patience (because getting into the feel of data science interviews to cracking it, takes time and all of this will take time but it is all worth it if you are going to enjoy the work you are going to do), Metis will definitely be able to help you reach where you want to. I won't at all be wrong in saying that it has changed my life in a positive way.

 

 

Attending Metis changed my life. I went from not knowing how to code in Python last year, to now working as a level III Data Scientist at a 10k+ employee company and purchasing my first house at the SF Bay Area. I compared a few different bootcamps before attending, but Metis has the best curriculum and I like that it is very student-centric. I think Metis gives the best balance among hands-on projects, understanding algorithms under the hood, and job searching resources/training. The 12 weeks was intense but surprisingly I also had a lot of fun with like-minded people. Our instructors and staff were friendly, dedicated, and willing to spend extra time with students answering questions. Some of us have families and long-commutes, and I find the Metis program flexible enough to allow autonomy. Realistically, I think one should expect a 9-6 schedule of work, plus a few hours in the weekends, plus, before project dues, some additional hours during weekdays. I did my first deep learning (CNN) project at Metis and it has been extremely valuable in my new career. I had a lot of job hunting support, which was consistent months after I graduated, including Metis employer network, interview skill training, and 1-on-1 job consultations. Overall, I highly recommend Metis.

I've always been a math geek, which is what drew me towards the data science space.  Having already had some exposure to coding and statistical modeling as an EE major, I realized that self-study wasn't enough to fill in the gaps, and a graduate program in data science would have been excessive.   

I spent a lot of time researching different programs, and very few compared in terms of community and level of attention as Metis.  Not only did the program do well to fill in the gaps and help to build a well-rounded portfolio, but it introduced me to a huge community of people who are all as eager as I am to learn.

Inevitably there were gaps in the curriculum (it's impossible to cover everything in 12 weeks), but the program and instructors did well to establish a foundation and point me in the right direction to dig deeper.  Even after finishing the program I was still learning and working on independent projects with their support. 

The career staff bent over backwards to make sure I had all the resources I needed as I went through the uphill battle that is the interview process as a newly-minted data science graduate. 

In short, it was a difficult decision for me to go through with the program, but I don't regret it.

I graduated from the Seattle Fall cohort (the second cohort in Seattle) in December. I come from a pure math background, and I'm a recent Ph.D. grad who was pretty nervous about going into data science.

Metis is everything I wanted out of a bootcamp. The project based curriculum works really well, especially since the topics of projects 2-5 are entirely self directed. It's easy to get excited about learning this stuff when you're applying it to a topic you really care about. That also makes it easier to pick yourself up when you fall -- and you'll fall a lot.

The lectures are an excellent introduction to the material, too. I had the opportunity of both learning from the Fall 17 instructors and TAing for the Winter 18 instructors, and all four of them were awesome.

Some quick warnings. Definitely do the prework. Definitely work ahead as much as possible -- everything sneaks up on you, from project MVPs to student investigations. This bootcamp is extremely intense -- I had to defend my Ph.D. in the middle of it, and that was the next thing to impossible. Don't do that. :P

Career resources are incredible, too. The job hunt is a long, demoralizing, frustrating process, and our career advisor made everything go so much more smoothly. I had no idea how much I was doing wrong, or making things harder for myself, when I was trying to figure out everything on my own.

The community of alumni is a great resource. My cohort actually had Thanksgiving together -- not every one will be that closely knit, but you'll definitely make friends and business contacts, and you have the whole network of Metis alums to draw on.

One small gap in the curriculum -- at least for me -- was some fundamental statistics stuff, especially related to experimental design and a/b testing. But the curriculum is evolving, and Seattle is still a young campus. Be forewarned, though, if your basic statistics is a little shaky like mine was, you might need to do some self-study in some areas.

If you can afford it (both in terms of time and money) then Metis will give back so much more than you put in. Highly recommended.

I attended the Fall 2017 bootcamp in Chicago. From the beginning, Metis was very helpful to me. I live in the DC area and the NYC cohort was full, but they helped me come out to Chicago so that I could still participate. They were very helpful (Nathan Vermeiren) with my housing search and all of my other out-of-town needs.  I ended up staying right next to the Metis office which worked out great. It was actually helpful for me to be away from home because I didn't have any of my usual distractions/duties to do, so I recommend  going out of town.  The only downside to going out of town was that Metis was not as connected in the DC area. Metis did continue to support me fully in the job search until I obtained employment and I had no trouble contacting the DC Metis alums who were quite helpful.

The curriculum is great. They spend a small amount of time on many methods and tools used in data science. They are not simply choosing the tools that are 'always done'. I know our teachers went out of their way to have us use the most current tool for the job (like spark vs. hadoop) and/or the best tool for the job. Often they would show us several ways to do something and then we would choose the one that we liked best or were familiar with.  One of the many things that make this bootcamp more valuable than sitting in your PJs on coursera, is the ability to ask them questions (more on this below). Another is that you will learn the method/tool and then USE it in a major project, not just  a homework. This project will be something that you are proud of and can put on your resume. These projects are the reason I got job interviews. Not my PhD, or my peer reviewed publications, but  my ML projects from Metis. The interviewers would ask far more questions about my metis projects and I was able to speak about the methods with confidence and authority because the project required me to know what I was doing.

The timing of the teaching is just right, in that they teach it to you the day before you need to start using it in your project. The best way to learn is to use it right away, and you will. Cloud computing/storage (AWS, Spark,hadoop) and databases (SQL, MongoDB) are other topics where it is valuable to have an in-person teacher. These are things that are difficult to get right when reading a forum because some things will be specific to your hardware or router. It would have taken me MUCH longer to figure out how to use AWS by myself.

 

Teachers are what makes the Metis experience. Our teachers were Zach Miller and David Ziganto. These 2 are truly great instructors and also great mentors. They are incredibly knowledgeable about all things Machine Learning and Python, and are so patient when you have questions. They also have many informative stories about their experiences when working in data science or interviewing data scientists for jobs. They taught us about what you do as a data scientist, and pitfalls to watch out for. One of the things that they manage to do is push you really hard and enforce difficult deadlines, but at the same time support you. They aren't going to give you answers (like any good teacher) but they will help you get out of being stuck on one thing for too long. They come and sit with us ALL day, every day and were never dismissive or impatient.

I have never had someone be so hard on me about presentations. They have incredibly high standards and it has taught me so much about something I thought I was already good at. I didn't fully understand why they wanted these 5-6 min presentations until I had my first interview and realized that a quick presentation is what you are doing every time you get an interview. It's literally interview prep, w/o labeling it that way. The career advisor Ashley Purdy was a big part of the presentation brigade and she helped me communicate complex things  in a less technical way (which is very important for a data scientist).  These three never let up on me for a single second and it was perfect.

I paid for bootcamp so that I could get better and that means I need to be pushed into a place(s) where I am not comfortable. I can do comfortable projects on my own. Full disclosure: I did not always succeed when they encouraged me to do things that were harder and that was ok. They were there for me when I failed and helpful about what I could do to deal with it. I know that's not always the case (it's completely possible to fail bootcamp if you are underperforming consistently), but because I choose something that was less 'safe' for me, they took this into consideration, and made sure that I was mentally/emotionally ok.  

Ashley Purdy (career advisor) pushed me to do things that I never would have done in my search for jobs and online presence. Metis required me to write a blog, which has earned me more than one interview, and I now enjoy writing posts. Our teachers have even promoted my posts via linked in and data science weekly. Ashley also showed me how to cold call people on linked in and just talk to them about their job (informational interview). This was very scary and really paid off, as one of the people I spoke with got my resume in front of the right people which led to me obtaining the job I wanted!  She is there when I have questions about salary negotiation or whether a recruiter is just spamming me. There were also some great presenters that came to talk about what they do at company X as a data scientist. The Metis alumni is a great community and will really help to build your data science contacts.

Metis’ career advisor (Ashley in Chicago) is one of the main reasons I chose Metis over some other bootcamps. Metis is very invested in whether you are able to obtain a job that you love. They don’t just present you to a few employers and say ‘bye’; they continue to make sure that you are structuring your days and applying to places that will be a good fit for you. It was always very clear that they were not just trying to get me to take any job so that they could check a box. In fact, they encouraged me to hold out for what I want rather than take the first thing I was offered.

Zach, David, Ashley and Nathan are also just really great people. They have a great sense of humor and are fun to be around. We had plenty of good laughs together (students+staff) and I know I had a great time while also being stressed out. This is why I always say, it's like grad school (in fast-forward) w/o the emotional abuse. lol  

Students were another important part of the bootcamp. Every student was highly motivated and smart. We hall had various  areas of expertise and I liked learning from them. It's very much a feeling of 'we're all in this together' and even when I wanted to slack off, I was inspired by them to continue to bring my 'A game' because they operated at such a high level. They were an important part of the high standards that Metis and our teachers set.

This bootcamp is  intense. If you have been through a PhD program, it's kinda like the night before you have to send your abstract/poster to the conference committee and you all stay up all night together working on it. Except that's every day for 12 weeks. You will want to spend your weekends on your projects, and come home pretty late (not everyone does this, but I did). So, be prepared for that level of work. It's completely worth it, but not possible for everyone. There's a reason they call it a bootcamp...

In sum, I highly recommend the Metis bootcamp to people who can devote the time. I obtained 2 very good job offers, in writing, within 2 months of the graduation date. I now have a job at Booz Allen Hamilton as a data scientist that is exciting, and I am ready to connect you to my network once you graduate from Metis!  

Overview: 
The Metis data science bootcamp is three months of intense learning. The curriculum is a data science survey course covering a wide range of data science topics from linear regression to natural language processing. Each topic is divided into approximately two week segments where you learn about the math and details behind the topic and at the same time, work on a project implementing what you learned. 

Difficulty Level: 
I attended Metis to make a career change. I was formerly a trader for 11 years. For me, the lessons and coursework at Metis were extremely challenging. I spent every day and night working on projects, debugging code, and reviewing material and still felt over my head for much of the bootcamp. I was putting in 12+ hour days, seven days a week. 

Metis's Strengths:
Metis especially shines in three aspects. One is the quality of the students. My cohort had 11 people in it. There was a large range of math and programming skills in the cohort. The students with more advanced technical skills were able to take advantage of material and produce more advanced projects than others. Everyone completed a portfolio of projects. Given this differing skill level, the learning atmosphere was collaborative. Every student was stressed and overworked. We used this common bond and help and support each other.

Another strength of Metis is the quality of the instructors. The instructors for my cohort were tough but fair. Their data science knowledge was impressive. They held our cohort to a very high bar. I both succeeded and failed at times, but they were there to guide me on how to improve and make progress.

Finally, Metis focuses on getting its graduates employed. Throughout the entire bootcamp, there is an overarching theme of getting employed. Each campus has a full time career advisor who knows the ins and outs of navigating the data science job market. Upon completing the program, you will have a portfolio of five projects to show employers that you are capable of performing as a data scientist. The instructors gave us insight into what employers are looking for in terms of the interviewing process and job performance. This combination of projects, instructors, and career advisors is how I managed to land job interviews and eventually get hired. 

One thing I wish I knew before Metis:
I would have gotten more out of Metis if I had more of an introduction to the machine learning algorithms. Understanding the machine learning algorithms was the most challenging part of the course. There were times where we spent two hours on an algorithm then moved on to the next topic. It was impossible for me to understand this complex new material in that short amount of time. 

Conclusion:
Before Metis, I was not competitive for any data science positions. I wasn't even competitive to receive an interview.

After completing the 3 month program at Metis, I was competitive for entry level data analyst and data science positions. I received an offer 2 months after the bootcamp ended.

Pros:
- Metis gives you all the tools for success
- They spend time helping you develop the soft skills necessary to excel in your career (project presentations, public speaking, working in a team, communication)
- They touch base on industry skills that aren't always used in an academic setting (git, open-source programming languages)
- They scratch the surface of many topics -- some might see this as a flaw and make someone a 'jack of all trades, master of none' but Metis provides you all the tools to get started in a specific topic domain -- it's up to the student to really exploit the resources that they provide.
- Job support and alumni network is incredible. After graduating, all alumni from all cohorts from the other campuses are connected and this provides a great network of people to reach out to for advice or help on a specific problem or job opportunities, et cetera. The careers department helps you with everything from resume to salary negotiation to just plain advice on what to do next when you're talking to a potential employer.
- Instructors are some of the coolest and smartest people I've ever met. They're incredibly intelligent and focused on their  but so down-to-earth and unpretentious that you would have no idea that they went to MIT or Cornell.

Cons:
This isn't even a 'CON'. I just wish I knew this beforehand.....
- In my opinion, Metis is BEST for those that are making a career CHANGE. In other words, someone who has already has an established career and looking to get into the data science realm. With data science being such a hot industry, most employers are looking for people with job experience (regardless of the domain). So for people (like myself) who don't have work experience and chose Metis as a substitute for graduate school --- expect to have to work a little harder to land that first job :)

I hope this review helps other people in a similar situation as mine.  I came to the 12-week bootcamp with little to no relevant professional experience (I was in software sales beforehand), but willing to do whatever it took to break into a career in Data Science.

If you want to transition career paths like I did, Metis is absolutely the way to do it.  I had several interviews with interested employers within days of graduating, with one interview coming just minutes after I presented my final project at career day -- and this all during the holidays, when recruiting is generally slower.

Metis provides the tools and support that are impossible to get for a career-switcher like myself.  Yes, you can crack a book on statistics and do some Hackerrank coding -- and you should do those things anyway! -- but that is nothing compared with the legitimacy that I've gained in employers' eyes by investing time and money in the program.  Moreover, the career support is excellent and doesn't expire; the Career Services staff have done an outstanding job of building a hiring network that you as a Metis student have full access to, and they give top-notch advice on the minutiae of resume writing, LinkedIn profiles, and so on.

In my opinion, a further vastly underrated aspect of Metis is the strength of the alumni network.  By graduating from the program, I instantly have connections to alums that have ended up at major companies in many different industries.  Browse the LinkedIn profiles of Metis alumns and you can see for yourself.

I will give two pieces of advice: one for those making a decision about Metis, and one for those who have decided to attend the bootcamp.

My advice in making a decision whether to attend is to contact as many alums as you can via LinkedIn or through their blogs, and ask them about their lives pre-, post-, and during Metis.  You will learn a lot about what Metis students are like, and whether you can see yourself as one of them.

My advice for you, if you will be attending, is to take as much initiative as you can to learn what you can beforehand.  I personally read and noted "Intro to Statistical Learning," a Machine Learning textbook, and I found that I got much more out of the bootcamp because of that.  You may decide that Andrew Ng's Coursera course is more your speed, or maybe something else -- but putting in the work regardless will pay off.  The bootcamp is only 12 weeks long, and you can't possibly learn 100% of everything that's thrown at you.  Putting in the sweat equity ahead of time will pay enormous dividends if you're not seeing most of the machine learning concepts for the first time.

I financed the bootcamp myself with savings.  It is obviously not cheap to attend, and I thought long and hard before finally submitting my payment.  But in end the desire to change careers won out, and I have not looked back since.  The bootcamp was worth every penny that I spent, even if it was nerve-wracking to commit to at first.

In sum, I would wholeheartedly recomend Metis to anybody that is truly motivated to change careers, even if it is a significant change like it was for me.