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Metis

Chicago, Chicago, New York City, Online, San Francisco, Seattle, Washington

Metis

Avg Rating:4.9 ( 97 reviews )

Metis offers data science training via 12-week full-time immersive bootcamps, part-time online bootcamp prep courses, and corporate training programs, with campuses in Chicago, New York, San Francisco, and Seattle. The Metis Data Science Bootcamp is designed and taught by industry practitioners and covers Python, Bash, algorithms, linear regression, machine learning, NLP, databases, and interactive data visualization. Graduates will be comfortable designing, implementing, and communicating the results of a data science project, will grasp the fundamentals of data visualization, and will get exposure to modern big data tools and architecture such as Hadoop, Hive, and Spark. The data science curriculum is delivered through project-based, hands-on, collaborative learning and Metis provides students with on-site instruction, and access to speakers, mentors, events, and job support.

To apply for the Metis Data Science Bootcamp, applicants need to have experience with programming and statistics, and complete 25 hours of academic pre-work. Metis offers a free, self-paced Admissions Prep course for those who need to brush up on their linear algebra, calculus, probability, statistics, and Python skills. Metis is looking for students eager to get their hands dirty by learning new technologies and solving real-life problems, and who have the skills needed to secure entry-level jobs in the Data Science field. Metis is authorized to enroll international students with M-1 visas across all U.S. campuses, which allow non-U.S. students to attend technical and vocational programs. International students who are already in the U.S. on an F-1 visa may also transfer to Metis. Veterans may apply to use the Post-9/11 GI Bill® to develop their data science skills at the New York City bootcamp.

Graduates leave fully qualified for data scientist jobs, with placement programs available. Students receive mock interview training, visit company offices, present their projects to employers at Career Day, and have access to an extensive network of speakers, mentors, events, and ongoing career coaching and job placement support.

Recent Metis Reviews: Rating 4.9

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  • Beginner Python and Math for Data Science

    Apply
    Data Science, Python
    OnlinePart Time6 Hours/week6 Weeks
    Start Date None scheduled
    Cost$750
    Class size20
    LocationOnline
    Considering applying to our Data Science Bootcamp but need to build or brush up on your basic skills first? Our Beginner Python & Math for Data Science course was designed for you, the beginner looking for an introduction to the building blocks essential to developing data science skills or forging a new career in the field. This course sets you on the right track, covering everything you’ll encounter during the bootcamp application process. You’ll learn: Basics of Python programming Common Python libraries: NumPy, Pandas, Matplotlib Foundations of linear algebra, calculus, probability and statistics Please note, the cost of Beginner Python & Math for Data Science can be applied to the cost of the bootcamp once you apply. We welcome all students looking to brush up on data science basics, not just those looking to apply to the bootcamp. Please visit our website to learn more and don't hesitate to contact us with any questions about Beginner Python & Math for Data Science, the Data Science Bootcamp, or any other inquiries.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelAbsolute Beginner
    Placement TestNo
    InterviewNo
  • Data Science Bootcamp

    Apply
    Start Date March 30, 2020
    Cost$17,000
    Class size22
    LocationNew York City, San Francisco, Chicago
    Metis's 12-week accredited data science bootcamp is an immersive program designed to give you the skills and connections you need to launch a career in data science. Career Advisors are dedicated to helping students and grads get hired, while Sr. Data Scientists bring real-world experience to the classroom and guide students as they use real data to build a 5-project portfolio. Each project is a start-to-finish application of the skills needed to be a well-rounded, competitive practitioner in the data science workforce. Each highlights the skills needed in every “facet” of data science: project design, data acquisition and storage, tool selection, analysis, interpretation, and communication. In succession, the projects deepen in both difficulty and independence. Upon graduating, students have completed rigorous training in machine learning, programming in multiple languages (Python, Unix, JavaScript), data wrangling, project design, and communication of results for integration in a business environment. Parallel to this core classroom work is a supporting careers curriculum created and implemented by our Careers Team, which works with each student to secure employment rapidly after graduation with a compatible employer. Our grads go on to work at some of the top companies in their respective markets, including but not limited to Capital One, Facebook, GrubHub, Starbucks, Spotify, NBA and more. We're proud to help our grads land their dream job in data science and our grads are proud to be #MadeAtMetis. Make sure to visit our website and testimonials page to read more. Welcome to Metis!
    Financing
    DepositN/A
    Financing
    We partner with SkillsFund, an innovative financing company that offers financing options for students accepted to our bootcamp. Visit our website to learn more.
    ScholarshipWe offer a $3,000 scholarship for women, members of underrepresented groups, the LGBTQ community, or veterans of U.S. military personnel. We also accept GI Bill® benefits at our NYC campus. Visit thisismetis.com to learn more.
    Getting in
    Minimum Skill LevelSome experience with programming and statistics.
    Prep WorkOnce students are enrolled in the bootcamp, they are granted immediate access to our prework materials, a structured program of 25 hours of academic pre-work and up to 35 hours of set-up is designed to get admitted students warmed up and ready to go.
    Placement TestYes
    InterviewYes
    More Start Dates
    March 30, 2020 - New York City Apply by February 24, 2020
    March 30, 2020 - San Francisco Apply by February 24, 2020
    March 30, 2020 - Chicago Apply by February 24, 2020
  • Introduction to Data Science

    Apply
    Data Science, Git, Python, Machine Learning
    OnlinePart Time6 Hours/week6 Weeks
    Start Date None scheduled
    Cost$750
    Class size20
    LocationOnline
    This course takes you one step closer to becoming a data scientist by offering a subset of the topics covered in our Data Science Bootcamp. You’ll get a well-rounded intro to the core concepts and technologies taught within the bootcamp, including basic machine learning principles and hands-on coding experience. Plus, you’ll put it all to practice through a mini data science project of your own. We’ll cover the following: Data acquisition, cleaning, and aggregation Exploratory data analysis and visualization Feature engineering Model creation and validation Basic statistical and mathematical foundations for data science We welcome all students looking to brush up on data science basics, not just those looking to apply to the bootcamp. Please visit our website to learn more and don't hesitate to contact us with any questions about Introduction to Data Science, the Data Science Bootcamp, or any other inquiries.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelStudents should have some familiarity with basic statistical and linear algebraic concepts. In Python, it will be helpful to know basic data structures.
    Placement TestNo
    InterviewNo
  • Online Data Science Bootcamp

    Apply
    Start Date March 30, 2020
    Cost$17,000
    Class size15
    LocationOnline
    Metis's 12-week accredited online data science bootcamp is an immersive program designed to give you the skills and connections you need to launch a career in data science. Career Advisors are dedicated to helping students and grads get hired, while Data Science Instructors bring real-world experience to the classroom and guide students as they use real data to build a 5-project portfolio. Each project is a start-to-finish application of the skills needed to be a well-rounded, competitive practitioner in the data science workforce. Each highlights the skills needed in every “facet” of data science: project design, data acquisition and storage, tool selection, analysis, interpretation, and communication. In succession, the projects deepen in both difficulty and independence. Upon graduating, students have completed rigorous training in machine learning, programming in multiple languages (Python, Unix, JavaScript), data wrangling, project design, and communication of results for integration in a business environment. Parallel to this core online classroom work is a supporting careers curriculum created and implemented by our Careers Team, which works with each student to secure employment rapidly after graduation with a compatible employer. Our grads go on to work at some of the top companies in their respective markets, including but not limited to Capital One, Facebook, GrubHub, Starbucks, Spotify, NBA and more. We're proud to help our grads land their dream job in data science and our grads are proud to be #MadeAtMetis. Make sure to visit our website and testimonials page to read more. Welcome to Metis!
    Financing
    DepositN/A
    Financing
    We partner with SkillsFund, an innovative financing company that offers financing options for students accepted to our bootcamp. Visit our website to learn more.
    ScholarshipWe offer a $3,000 scholarship for women, members of underrepresented groups, the LGBTQ community, or veterans of U.S. military personnel. We also accept GI Bill® benefits at our NYC campus. Visit thisismetis.com to learn more.
    Getting in
    Minimum Skill LevelSome experience with programming and statistics.
    Prep WorkOnce students are enrolled in the bootcamp, they are granted immediate access to our prework materials, a structured program of 25 hours of academic pre-work and up to 35 hours of set-up is designed to get admitted students warmed up and ready to go.
    Placement TestYes
    InterviewYes
    More Start Dates
    March 30, 2020 - Online Apply by February 24, 2020

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  • Dan Taber  User Photo
    Dan Taber • Graduate Verified via GitHub
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    Doing Metis was one of the hardest decisions I ever made. The time/financial commitment is tough to swallow for anyone! That said, it’s one of the best decisions I ever made, as Metis paid off in every way you could imagine.

    Several peers have captured the benefits of Metis here, so I’ll try to avoid repeating them and focus on what stood out to me personally …

    The obvious doubt about a bootcamp was, “Why pay thousands of dollars?? I can learn all this online.” But Metis provided so many intangibles - career support, alumni network, mentorship from instructors, friendship from diverse peers - that you can’t get from an online course. Not to mention improving your chances to get a job. Prior to Metis, I tried to transition from academia to industry, but with zero success; I couldn’t get a single tech company to even consider me. Within 2 months after finishing Metis, though, I received multiple job offers and accepted one with a company that I’m thrilled to be at.

    The project-based curriculum, with the guidance of experienced instructors, is the ideal way to learn. Aside from giving you a strong portfolio of material to use on the job market, the projects teach you to learn and apply new material quickly. In my first job after Metis, I was much more confident learning new tools because Metis had prepared me for the fast-paced learning you need to be a data scientist.

    I can’t emphasize enough how committed the Metis instructors and staff are to students. They go above and beyond to not only teach you data science but provide mentorship, career support, and emotional support. The bootcamp and subsequent job search can be an emotional roller-coaster, so their support is instrumental.

    Finally, one of my favorite things about Metis is that they don’t sugarcoat the challenges of the bootcamp or make grandiose, inflated claims about what the outcome will be. Getting a job in data science is very, very hard. Metis acknowledges it’s hard, doesn’t make any wild promises, but gives you every resource to succeed and remains committed to their alumni long after you graduate. They treat you like you’re part of their family.

    My biggest piece of advice - think carefully about how you need to personalize the Metis experience to suit your needs. Everybody comes in with different backgrounds and life circumstances. There’s no single formula that works for everyone; when making decisions like picking projects, deciding when to start your job search, etc., you need to consider that what’s best for you. Whatever you choose, Metis staff are going to be there to help you through it.

  • Andrew • Financial Data Scientist • Graduate
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    Core data science (and I mean rigorous statistical analysis and predictive modeling), felt so out of reach before Metis. There's so many resources for learning Python and SQL out there (Udacity and Mode Analytics being my favs, respectively) - that I wanted material and curriculum from a bootcamp that matched the cost of attendance. In 3 months, Metis made it worth my while - enabling my growth from pivot table repots in excel and simple sql queries all the way to Natural Language Processing on unstructured text and Deep Learning on Cloud Deployments.

    The bootcamp option isn't for the faint of heart - and my personal thirst for challenge and rigor was satisfied. The immersive experience was so valuable to me for several reasons:

    (a) The "guided tour" experience. There's too many resources for learning data science, and it's helpful to have experienced professionals vet the resources for you. Part of being a good data scientist is knowing what you can down prioritize for learning later. By immersing myself in the best practices and skills that Metis instructors have determined most useful on the job, I generated plenty of leads and had secured an industry role within 3 months of graduating the bootcamp.

    (b) Legitimized work experience. It's credible to potential employers to see accredited Metis experience on my resume, with work references from my instructors and cohort members to further validate my experience to potential employers. Whenever a potential employer asked me to list references for someone I worked with, I had a list of capable data scientists that could vouch for me. This set me up for plenty of technical assessments and technical interviews.

    (c) Connections to a learning network. Metis alumni are growing with every cohort! Data scientists are a minority compared to Software Engineers, and I was told early on that it wouldn't be unusual to work alone or on small teams on the job. That said, over a year later I'm still leaning on the community to keep my updated as data science tools and methods improve. Post-bootcamp, I learned so much more from my cohort and other alums from soliciting help and resource sharing. If I had done all the same projects by myself, then I wouldn't have had the breadth of exposure or network to be as successful a data scientist as I am.

    I can't stress enough how worth it this experience was for me.

  • Dana • Data Scientist • Student
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    I completed my Metis bootcamp in December 2018 in Seattle.  What an amazing 12 week experience.  Every person in the 16 student group was smart, committed and caring as were the Metis staff as well.  We were a diverse group in ages and backgrounds but everyone was there to get the most out of the 12 week experience.  We were together in the classroom from 9am-5pm, 5 days a week.  That made for an amazing energy.  

    We learned a lot but it's bootcamp and the information comes at you fast.  This meant we were on a very steep learning curve which is pretty exciting.  Be prepared to be all in for the 12 weeks to get the most out of your time at Metis and then spend time afterwards learning the stuff you missed along the way.

  • Andrea • Business Data Analyst • Graduate
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    I attended Metis in the summer of 2018 and I could not be happier with my Metis experience. The instruction was state of the art and the staff was accessible, helpful, and supportive.

    Probably the most important feature of a data science bootcamp is the quality of the instruction and Metis instructors are excellent. One of my instructors had relatively a stronger background in computer science and the other a relatively stronger background in math and they complemented each other perfectly. The classroom culture was collaborative and supportive. Learning from peers was highly encouraged and practiced daily. Every morning, we completed a pair programming exercise; this was an incredible opportunity to learn from peers who came from diverse backgrounds and had incredibly advanced and varied skillsets. Moreover, updates to the curriculum are continuously being implemented such that the curriculum stays on the cutting edge of data science.

    I also found the way the curriculum was structured to be highly effective. The curriculum is project-based and covers topics from exploratory data analysis, to regression to classification to unsupervised learning and finally to a passion project of students’ choosing. Students complete a project for each of these units. Metis does not provide the data sources or provide students with a pre-packaged template for the projects. Students have to go out and scrape their own data or otherwise obtain data from publicly available sources and determine (with guidance from instructors of course) what direction they want to take their projects. Students’ diverse backgrounds and interests are then reflected in the choice of projects; in my cohort alone, student projects ranged from predicting the stock market (of course), to predicting good locations for cat cafes, to natural language processing of religious texts, and predicting locations and severity of wildfires. I found this project-based approach to be highly effective. In contrast to other data science programs which are centered around only one capstone project, Metis’ curriculum allowed for students to take deep dives into each of these topics.

    Career support was also extremely effective. From the careers team, I learned how to update my resume and LinkedIn profile to be consistent with industry standards and even practiced in person and technical interviews. I eventually got my first job as a result of a tip from one of the career’s staff. To me, this indicated just how well the career’s staff knows their students; they knew that this opportunity would be a good fit for me and indeed it was.

    Of course, Metis is not cheap but none of these bootcamps are. When I made the decision to attend Metis, I knew that I was making an investment in my future and at the time, I predicted (because hey I am a scientist and scientists like to make predictions) that I would have a strong return on that investment. In the few months that it has been since I graduated I have already had a return on that investment and I know that return will continue long into the future.

    Lastly, while Metis was definitely an intense and challenging experience, it was also a fun one. It was extremely stimulating to be surrounded everyday by such knowledgeable instructors and peers with such incredibly diverse skillsets. There were late nights and work on the weekends to be sure, but I also found the work to be manageable. During Metis, I remember telling myself not to let perfect be the enemy of good and I think that advice served me well. The skills that I think are critical for students to succeed at Metis are curiosity, a willingness to try something and fail on an initial attempt, a willingness to iterate, and openness to collaboration. If these qualities resonate with you, I would strongly encourage you to check Metis out. It was an amazing experience and I am so glad that I made the choice to do it.

  • Kelly • Graduate
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    I can't say enough about the curriculum, staff, and community. I completed my course in Fall 2017, I got a job within 2 months. and have continued to benefit from the community as well as the course resources. My background is in psych research in academia. I got my PhD in Psych/Neuroscience and was facing a bleak job market so I made the decision to transition to data science. It was a rough transition. The bootcamp is not for the faint of heart, but my cohort was comprised of really bright and supportive students (many PhDs and graduates with genuine technical and mathematical prowess) who kept me motivated and on-track. My instructors were amazing and the administrators were incredibly hard working, organized and caring. The curriculum was comprehensive (i.e., a lot so be prepared to be overwhelmed). Regardless of how smart/hardworking you are, you will struggle to keep up. BUT if your experience is anything like mine, you'll be surrounded by people who genuinely care about your success. What's impressed me the most is that a year into finding a well-paying tech job, I'm still very much a part of- and benefit from- the Metis community. I STILL use notes from my session. and my cohort still supports each other's growth and success through referrals and knowledge-sharing. The administrators are still available a year plus into graduating for advice and help because they genuinely care about their students. If I could give this place a 6/5 I would. I really loved my time there and I have a ton of respect for the Metis family.

  • Mark Hayes • Graduate
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    I two took Metis' online courses:

    1. Python/Math for Data Science

    2. Intro to Data Science

    I thought both were very good and definitely worth the money. I was a complete programming beginner but had done some pre-work using Zed Shaw's "Learn Python the Hard Way" and I had taken one intro Python/Data Science class at Simplilearn (very good too).

    Class #1 above was the first Metis class I took. Without my preparation I would have been lost, but the prep I did allowed me to keep up with the programming part of the class. The math I fortunately already knew, but it would have been confusing had I not known it. [If you don't know it, then use the class as a menu for what you need to know eventually]. Interaction with the instructor took place via chat window, but he was responsive to Q&A. The course materials (Jupyter Notebooks) were very through and detailed & I've reviewed and re-reviewed afterward and continue to get value from  them.

    Class #2 built on Class #1 but got more into techniques of statistical modelling. In this class, we spoke with the instructor (not just chat box), which was very very valuable given the subject matter. I thought the course material (again Jupyter Notebooks) was well structured and clearly showed how to run the models using Python code. The instructor was fantastic, even agreeing to have "office hours" before class and hanging out after class for extra Q&A. Way beyond the call of duty, but it replicated a bit the university environment.

    In general, I'd highly recommend either course (and I paid myself, no corporate reimbursement). If -- like me -- you are a total beginner, then do some learning on your own before enrolling. It will be very hard to keep up if you go in cold. They cover a lot of material and go fast. But if you're willing to really try and work hard to learn, I bet you'll find good value and a lot of insight to help you on your path. I did.

     

  • Monica Ramirez • Data Scientist at everis • Graduate
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    * Content: It´s an injection of information straight to your brain as expected.  You get to see all of the concepts on Data Science and the stats/math underneath, so be sure to make the prework, and during the bootcamp read more or look for videos on any concept you don't understand very well.  There's a lot of self learning needed: instructors will be there to explain things to you, and you can ask for review sessions on some concepts.  But it's practicing, researching and discussing with your peers that you'll get everything well understood

    * Assignments: The most important part are the Projects (every 2/3 weeks) you'll feel you don't have time for anything, but you'll be amazed on how much you learn and get done in a little time, and that's the point.  There are 5 projects: the fist of them given to you, very fast (to deliver in just a week), in group with some of your partners, to get the idea of the bootcamp methodology.  The next 3 will be individually and chosen by you, each of them to practice a particular topic, methodology or algorithm (Regression, Classification, Supervised/Unsupervised learning, NLP, Neural Networks...).  The last one, your "passion project", also individually and chosen by you, can be almost anything you want with what you learn.  So the projects are as hard as you push youlself. 
    There are also other assignments: challenges (like homework that will help you with your assignments) every week, a blog and blog posts (and blog posting culture) every now and then, and two personal investigations during the bootcamp... So you´ll think its a lot but it´s all well structured: Make them all, because all assignments will help you in your projects that are the most important part

    * Instructors: Since you're learning a wide range of concepts: Statistics, Math, Programming skills, methodologies, libraries... You'll also find different instructors that will give a different focus to the things you are learning.  It can be frustrating sometimes not to get a straight forward answer, but at the end you'll find out that Data Science has a lot of points of view and you have to learn to find the best fit for you, so that's what the instructors are doing by helping you find an answer and not giving it straight away. One thing they'll always help you and support a lot with is the fact that no project is wrong and you can move on with any crazy idea even if you think it's impossible, and they'll show you ways of seeing things that you'll only get by practice and experience.

    * Carrer Support: You'll get very useful workshops: to fix your CV, your LinkedIn profile, your networking and interviewing skills, which is great.  There's also people coming over from different companies and Data Science roles to talk about their experience and you can ask them anything!   After bootcamp, people from Carrer Support are still in contact with you for help, advice or any questions until you get a job (Or even after, if you need it)
    In my case, that's as far as it goes: I was an international student so other support like: visit to hiring companies, salary negotiation skills or networking with hiring partners was not very useful for me (Although I heard it was very useful for my peers), neither do they offer sponsor for a working visa, that depends on the company and I was not very interested at the time.  However, back home, with what I learned on the workshops, the tips that they gave me and post bootcamp advice I found a job back home in a couple of months.

    * Environment: New York's campus is in a WeWork building, there a lot of areas to study in groups or concentrate individually, it's open 24/7 and there are common areas to meet the instructors or your partners regarding bootcamp topics or chat about anything else.

    * Conclusion: Bootcamp experience is great. Personally I think is a little expensive, but totally worth it.  You'll get the tools you need to become a Data Scientist and the culture to keep learning and keep growing. If you're an international student, don't expect to get a job to stay in the US and change your life, but you will come back home in only 3 months, having learned a lot of stuff people take maybe a year to learn and succeed.

  • Jhonsen Dj • Graduate
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    This review is for intro-to-DS live/online course.

    I recently got interested in data science (DS), and I wanted to do a career-transition through the 12-week DS bootcamp offered by METIS. In preparation for the bootcamp, I decided to take the Intro-to-DS live/online course, and I’m glad I did! This course gave me the necessary overview and hands-on coding experience with DS and machine learning (ML) fundamentals. The exploratory analysis techniques I learned in this course helped me tackle the DS challenge given during my (bootcamp) application process.

    This Intro-to-DS course is fast-paced and filled with lots of content. The curriculum is structured in such a way that, we could apply the techniques we learn at each session to our project interest and continue to build upon it throughout the course. There was a total of twelve (3-hr) live sessions where we got to learn basic concepts of DS, i.e., math (LinAlg & Stats) and python, supervised- & unsupervised learning, and pretty much everything involved in a typical model-building pipeline. By the way, twelve sessions surely won’t be enough to cover all existing ML techniques today, but at least we got to see a high-level overview of most of them. Each session was held live and online via ZOOM (where the instructor and students could share each other’s screen); these sessions were also recorded so we were able to download the videos after. Course materials (e.g., lecture notes, jupyter notebooks) were distributed via git-hub, so I could keep these notes for future reference. I wished there were more homework sets given to help solidify the concepts we learned in class, but I suppose I could just google search for various datasets and explore them myself.

    During the course, we were strongly encouraged to complete a mini DS project. About half the class (including myself) selected a project, worked on it throughout the course and presented it at our last session. This was a good experience for me, as I had never worked on an end-to-end DS project before. I’ve taken a couple of self-paced MOOC’s, but the live (online) classroom setting in this course was more helpful for me, as I somehow felt accountable to keep up with the materials as the course progresses. 

    I’d recommend taking this course, if you have some programming experience with python and are interested in getting hands-on coding experience with ML. By the way, the tuition for this course can be applied to the bootcamp, if accepted to the program. So, it’s basically a free, pre-bootcamp (warm-up) training.

     

  • Data Scientist
    - 11/19/2018
    Phillip Tan • Data Engineer • Graduate
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    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!

  • Bootcamp
    - 11/6/2018
    Vicky • Data Science • Graduate
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    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.

     

  • Data Science
    - 10/18/2018
    Kalgi Shah • Senior Data Analyst • Student
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    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.

     

     

  • Changed my life
    - 10/11/2018
    Katie H • Data Scientist • Graduate
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    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.
  • Avi Kejriwal • Data Scientist • Graduate
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    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.

  • Vicky Szuflita • Graduate
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    Coming with little technical background, it was definitely challenging, but I learned so much! I accomplished all I set out to do and more. Completely changed my career path and life — If you’re interested in learning data science I highly recommend!

  • NYC Bootcamp
    - 8/3/2018
    B • Data Analyst • Graduate
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    The Metis bootcamp was a great experience and so far seems well worth its value in skills, project experience and career assistance.

     

  • Gavin King • Data Scientist II • Graduate
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    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.

  • Summer Rankin • data scientist • Graduate
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    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!  

  • Eric Chan • Associate Consultant • Graduate
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    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.

  • Alexander Hughes • data scientist • Graduate
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    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 :)

  • Dave Oxnard • Graduate
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    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.

  • d3.js was great!
    - 12/27/2017
    Alex • Software Developer • Graduate
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    I took the d3.js/data science course at Metis with Mollie Petit. 

    Mollie was really helpful and positive throughout the course. She provided a ton of resources for us to learn throughout the classes as well as after. I learned a lot both about data science as well as the practical application of d3.js. 

    The only thing I wish was that we had a bit more time and/or the class was more spread out so as to allow for a slower learning pace. 

    The course overall was great. Mollie was an enthusiastic, positive teacher who was always available for help. I would highly recommend the class for anyone interested in data science or d3.js specifically. 

  • Dangaia Sims • Senior Data Scientist and Strategy Consultant • Graduate
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    Prior to enrolling in Metis I was a PhD candidate in a subject matter that is generally not seen as related to data science. While I was confident in my statistics background I had only coded sparingly and was completely new to machine learning concepts. On a whim I decided it was time to leave academia and stumbled upon data science as a career option. After debating whether or not to enroll in a bootcamp or teach myself the curriciulum I quickly found Metis and decided to apply, was accepted, and enrolled soon thereafter.

    Having received a PhD I was no stranger to learning and was happy to discover that the Metis program design and curriculum was exactly what I was looking for. It was the perfect combination of fun, knowledge, and rigor. Given that the course is only 12 weeks the pace can be relatively quick at times; that said, I felt confident in the material I was learning and truly engaged in the projects I was delivering. At times I felt stressed, afraid, and overwhelmed that the work I was doing wasn't up to par but was continually validated and supported by my classmates, instructors, program manager, and career staff. And for my final project I was able to create an app that combined my PhD expertise with data science and was elated to find merging the two fields was a relatively easy task.

    Within about a month after I completed the bootcamp, with the help of the career team, I had multiple job interviews under my belt and received a job offer as a Senior Data Scientist. I can't say enough good things about the careers staff both on site and around the country. In my experience, they were constantly on my side on my job hunt, during negotiations, and even after I accepted the offer.

    Without a doubt I am confident that Metis was the right choice for me. While I'm certain I could teach myself to code and some overarching machine learning concepts, I found the classroom experience to be invaluable for me. The opportunity to engage with peers, ask questions, and of course the career support could not be self-taught. If you're on the fence about whether or not Metis is the right choice for you I strongly suggest that you take the leap!

  • Amazing Experience
    - 10/4/2017
    Antonia Antonova • Data Scientist • Graduate
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    Metis is an absolute gem. The bootcamp was an amazing experience and extremely worthwhile. I felt like I got more out of it than any other educational program I've been in.

    What made Metis stand out for me was the support that students received at every step of the way. From the coursework, to the projects, to career help- Metis truly has every student's back. It feels amazing to know that you have someone to turn to who will actually help (or try very hard even if they don't know how). The focus on employability is also very refreshing. It seemed at times that Metis was more urgently trying to get us employed than we were- which I loved! Like a pushing parent- it was what we all needed.

    My thoughts in summary: the coursework leaves your thoroughly prepared for a position in data science, the speakers introduce you to an amazing array of applications and directions to head in after the course, and the career help is extremely thorough and personal.

  • Anthony • Software Engineering Manager
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    I'm a fulltime software engineering manager with 3 kids.  It's challenging to find time at home to level up on a new language so every couple of years I look for a short-term night class to force it.  I maintain a metrics pipeline at work and I chose D3 because I was looking to take my visualizations to the next level.

    My first impression is that Metis has a very high bar for instructors.  This course was taught by Michael Freeman who is a University of Washington professor and a widely recognized expert in the data visualization community.

    His creds:  https://ischool.uw.edu/people/faculty/mikefree

    Michael is someone who can write 300 lines of D3 from memory in 10 to 15 minutes while verbally explaining every detail to the class along the way.  By the end of the 15 minute session he's manipuated a huge dataset into a beautiful visualization, answered all of your questions along the way, and taught it in a way where *everyone* in the class could start working on in it in their next lab.  For me the teacher makes the class.  By the end of the course I felt like it was money well spent.

  • Tim Schletter • UI Developer
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    I am happy to say that I got a lot out of this course -- not only in knowledge and practical application but in inspiration and critical thought. In my experience this class was successful in what it set out to accomplish and I would very much recommend it to a friend or colleague.

    It is important to note that the origin of my praise is the teacher himself, Kevin Quealy. His approach to teaching was interactive, casual and paced to maintain the inclusion of those who quickly understood as well as those who needed a bit more time to comprehend. I found myself on both sides of the spectrum throughout the course and felt confident that my questions would be addressed.

  • Xavier Vila • Data Analyst • Student
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    I recently finished the Metis Introduction to Data Science class in NYC and I have nothing but good things to say about it. I have been interested in Data Science for a while so I decided to go to a Metis meetup where they went over the curriculum of the class. I found it very interesting but what sold me was the teacher, Sergey Folgelson. He is an excellent and energetic teacher.

    The class is intense and moves quickly. At the time of this review it runs every Tuesday and Thursday from 6:30pm to 9:30pm. You may be tired after a long day of work but Sergey will wake you up. There will be exercises thrown in at different portions of the lecture. You will learn a lot if you put in the work. I found that reviewing the notebooks after class on my own and completing the exercises really helped me retain the information. If you expect to just go to class and not do any homework then you might not get much out of it. As with most things you learn by doing. 

    For me it was a perfect introduction to the field and just made me want to learn more. I loved it so much I applied to the 3 month intensive.If you work with data and are curious about what all the fuss is about Data Science then I cannot recommend this class enough. Best investment I have made in a long time.

Thanks!