Remote Data Science Bootcamp

Top-Ranked, most comprehensive, 1-on-1 expert support

What we focus on

Remote Data Science Bootcamp vs Other Online Courses

A Complete Curriculum

A Complete Curriculum

There are tons of data science resources online, yet you don’t know what to study. Our curriculum is drawn from data science engagement with corporate consulting and training, hiring partners and active industry participation. We know exactly which technologies you should be learning to be competitive in the job market, so you’ll graduate with everything you need to land a job as data scientist.

High Engagement and Completion Rate

High Engagement and Completion Rate

Open online courses have a very low completion rate, often close to 10%, and an even lower understanding of the material at the end of the course. Our remote bootcamp ensures that students achieve a very high level of proficiency. Students are expected to dedicate themselves fully to this program and fulfill all the requirements, which include completing lecture videos, daily homework, and four projects.

Thorough Interaction and Support

Thorough Interaction and Support

Our applicants consistently tell us about their disappointment with not having personal support in other online programs. The Remote Bootcamp is built as a collaborative environment utilizing online chat and meeting systems. Students also have the opportunity to collaborate on homework, projects, job applications, interview preparation, paired programming, and even further through our extended alumni community.

Amazing Job Placement Assistance

Amazing Job Placement Assistance

We work closely with hiring partners and recruiting firms to create a pipeline of interests for students. Each student receives one-on-one support with job searching and access to all kinds of job assistance resources, including coding reviews, interview prep, resume workshop, and access to our exclusive hiring partner network.

Choose your mode

Part-Time Flexible
$16,000

Self-paced learning through online platform
Interactive coding exercises
Personal data science mentor
4 industry standard Data Science projects
Industry-proven curriculum
Career support

Estimated Time to Complete

divider
25-30 hours per week
Complete within 4 months
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15-18 hours per week
Complete within 6 months
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8-12 hours per week
Complete within 10 months
Full-Time Intensive
$16,000

12 week interactive learning through live streaming with in-person TA
Live interaction with community
Personal data science mentor
4 industry standard Data Science projects
Industry-proven curriculum
Career support

Full Schedule

9:30 AM
Live lecture
12:30 PM
Enjoy lunch break
1:30 PM
Online chat with classmates and instructors, or career coaching sessions
2:00 PM
Afternoon lectures, code review
3:00 PM
Work on projects and homework, project presentations, guest speakers
6:00 PM
Meetup events (optional)

How does the Remote Data Science Bootcamp work?

Example of Student Project

Learn from complete resources

Remote Data Science Bootcamp provides a comprehensive set of materials you will leverage during the program, including lecture videos, slides, homework and solutions, code reviews, jump-start sessions, and a selection of guest speaker talks.

Build real-world projects

Students complete lectures and exercises based on finely tuned schedules. Throughout the program students work alone and in teams to create four real-world projects.

Work with a mentor

One–on–One tutoring, mentorship and project support is provided through online chat and video meetings with dedicated mentors.

Personalized job assistance

We work closely with each student on job searching from Day 1. Career support includes but is not limited to coding reviews, interview prep, resume workshop, and access to our exclusive hiring partner network.

Curriculum

Our bootcamp is renowned the depth and breadth of the curriculum, the richness of the lectures in both programming and statistics, and for its demanding nature. We are the only data science bootcamp that teaches not just Python but also R, Hadoop, and Spark. This bootcamp is probably the most intense program you’ll ever take, but you will get out of the program as much as you put into it.

We are also among the highest ranked Data Science programs on CourseReport.com and SwitchUp.

Download Curriculum
GitHub
R
Python
Hadoop
Spark
Database
Unit 1
Data Science Toolkit
Learn to work from the command line - a must have skill for all data scientists. Work with basic Linux commands, text editing, and Git for version control. MySQL is taught with extensive practice on data manipulation.
Unit 2
Data Analytics & Visualization with R
Dive deep into R programming language from basic syntax to advanced packages and data visualization (e.g. tidyr, dplyr, string manipulation, ggplot2, R Shiny). Create a data-centric application with interactive visualizations.
Unit 3
Data Analytics & Visualization with Python
Basic Python programming, followed by versatile packages such as Numpy, Pandas, Matplotlib, Beautifulsoup, Scrapy and Selenium. Exposure to NoSQL and MongoDB. Complete a Python web scraping project.
Unit 4
Machine Learning with R
Descriptive statistics, hypothesis testing, missingness, imputation & KNN, simple linear regression, multiple linear regression, generalized linear models, principal components analysis, ridge/Lasso regression, trees, random forests, bagging, boosting, support vector machines, unsupervised learning. Complete a Kaggle competition.
Unit 5
Machine Learning with Python
Deepen machine learning skills with scikit learn. Focus on data cleaning, feature extraction, modeling and model selection using regression, SVM, PCA, tree models, clustering and more. Acquire skills in Natural Language processing, Time Series Analysis, and Deep Learning.
Unit 6
High Performance Computing, Hadoop, & Spark
Learn the concepts of high performance computing with parallel computing skills in Python and R. Introduction to MapReduce, Hadoop, Hive, Spark, and Spark MLlib.
Unit 7
Capstone Project & Job Placement Support
Complete a capstone project. Resume review, tips of interview skills, and opportunities to interview with potential employers.

Online Classroom Features

Autograding platform

With autograding tools embedded, you get immediate feedback from your work, saving lots of time from submitting homework and waiting for answers. The autograder supports multiple languages, including R, Python, MySQL, and Bash. You also have access to our dynamic set of exercises, datasets, and resources without leaving the workspace. Error­ highlighting and auto­completion make it easier to correct your code and avoid misspellings.

Work 1-on-1 with your mentor

Throughout your journey, our teaching assistants are available to answer your questions via 1­on­1 appointments and our help desk.

Community support

Our online community ensures you never work alone. A large portion of our curriculum involves group projects and peer programming. You’ll collaborate with your classmates on projects and share knowledge via online chat and community channels. You’ll check and learn from others’ codes, and build the team skills needed in a real working environment.

Career Services

Resume and Profile

1. Resume and LinkedIn profile review, interview skills & elevator pitch workshops

Technical Review

2. Mock technical interview and coding tasks

Post-Interview Review

3. One-on-One post-interview review and feedback outreach

Industry Experts

4. In-class Industry Experts speaker series

Hiring Partner Events

5. Hiring partner event series, including student presentations and a hiring partner networking gala party

Meetup Events

6. Present projects and networking with data science peers through our meetup events

Companies that hired our students

Google
Bloomberg
Spotify
JP
Capital One
Aetna
view complete list >

Student Testimonials

Wann-Jiiun Ma, Fraud Data Scientist
Wann-Jiiun Ma, Fraud Data Scientist

Citi Bank
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I was a postdoc at Duke University (Engineering) and my background is control and optimization. I participated NYCDSA Online Data Science Program (10/2016 - 02/2017).

NYCDSA online video lectures have a very high quality. I found that the well-organized class material and lecture notes very helpful to prepare for data scientist job interviews. I can review the material repeatedly until I am ready for the interviews. Also, almost everything I need to pass a data scientist job interview is covered in the program, which can certainly facilitate my interview preparation.

Finally, Vivian and the entire NYCDSA team are extremely helpful for data scientist job searching. From resume/cover letter revision, coding practice, to data scientist technical interview preparation, NYCDSA has enabled me to make a smooth transition from academia to industry.

I found a job at Citibank as a Fraud Data Scientist. Without NYCDSA online program, I would have to spend much more time to find the right direction to achieve what I have been able to accomplish through this online program.

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This course was the best thing to ever happen to me. In 20 weeks (4: pre work, 12: course, 4 job hunt) I went from someone who couldn't write 'Hello World' in python to a full blown Data Scientist, making six figures, with multiple companies vying for my interest.

What you should know:

You will get as much out of this course as you put in. I had many, many days where I was working well past midnight and back in class by 9:30am. You learn how to learn, which is THE skill required for any coding job. The curriculum is intensive, and a lot of times I couldn't totally complete the homework without checking for answers from my peers, and that's okay! In the real world, much of your job will be interacting and working with a team.

Course: Go every day, work hard, finish the projects on time, and hold yourself accountable. The lecturers do a great job, but ultimately when you're 24+ years old, nobody is going to spoon feed you. The homework is great, but when you try to put everything you've learned together into a well rounded project (there are 4-5 projects), that is when you really understand what is going on. Throw yourself full bore into the projects, and take pride in your work. 90% of what I learned, no exaggeration, was in the 3-5 days before projects were due. Its one thing to figure out homework by looking at the example sets, and a different thing entirely to apply those concepts to a data set with different structure and goals. If you are proud of your projects at the end, you will get a job. Period.

Job Hunt:

The job is the ultimate goal for 99% of people entering the camp. Unfortunately, there is some confusion about how the search will work. For one, you will not be "given" a job. For most people, the job search will take 1.5-3 months. Vivian has excellent contacts but she also has 40+ students. In order to guarantee yourself a job, you need to approach the process like a data science project. For me, I did "easy apply"s on LinkedIn, 50 a day. These take literally 15 seconds each. I then selected 15 companies a day with a more formal interview process, and sent them a variation of a pre-written cover letter. For my top picks, I tried to find a hiring manager or data scientist on the team, and add them on LinkedIn. I put my name on AngelList, and got many companies reaching out. I humbled myself and told everyone I was more interested in a great learning position, not a great salary. I iteratively changed my own interview methods, including voice tone, inflections, negotiations, honesty levels, until I found a balance that worked for me. You cannot just apply and hope. That is not a method.

Basically, the bootcamp is the first big step. The second big step is learning how to apply and interview. Many people send out 5-10 applications to their top picks (who are often everyone else's top picks as well) and then sit on their hands and wonder why they haven't gotten a job. When entering a new field, you have to make concessions about your salary and place of work, in order to reap the rewards down the line. Also, without multiple options, you will not be able to negotiate because you'll feel this is your only chance. BROADEN YOUR HORIZONS!

Overall:

The camp was the best decision I ever made. I read a book called Design Your Life, which basically said take how you want your life to be, then decide what is necessary to get it there.

I wanted to live in NYC, with a six figure job, working in an office with low stress, and love what I do. NYCDSA made all of that possible. If you have gotten a degree that isn't taking you where you want to be, but you know you're smart and can work hard, I strongly urge you to apply to NYCDSA today.

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Mayank Shah
Mayank Shah

-Live-
Mayank Shah
Mayank Shah

-Live-
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This course was the best thing to ever happen to me. In 20 weeks (4: pre work, 12: course, 4 job hunt) I went from someone who couldn't write 'Hello World' in python to a full blown Data Scientist, making six figures, with multiple companies vying for my interest.

What you should know:

You will get as much out of this course as you put in. I had many, many days where I was working well past midnight and back in class by 9:30am. You learn how to learn, which is THE skill required for any coding job. The curriculum is intensive, and a lot of times I couldn't totally complete the homework without checking for answers from my peers, and that's okay! In the real world, much of your job will be interacting and working with a team.

Course: Go every day, work hard, finish the projects on time, and hold yourself accountable. The lecturers do a great job, but ultimately when you're 24+ years old, nobody is going to spoon feed you. The homework is great, but when you try to put everything you've learned together into a well rounded project (there are 4-5 projects), that is when you really understand what is going on. Throw yourself full bore into the projects, and take pride in your work. 90% of what I learned, no exaggeration, was in the 3-5 days before projects were due. Its one thing to figure out homework by looking at the example sets, and a different thing entirely to apply those concepts to a data set with different structure and goals. If you are proud of your projects at the end, you will get a job. Period.

Job Hunt:

The job is the ultimate goal for 99% of people entering the camp. Unfortunately, there is some confusion about how the search will work. For one, you will not be "given" a job. For most people, the job search will take 1.5-3 months. Vivian has excellent contacts but she also has 40+ students. In order to guarantee yourself a job, you need to approach the process like a data science project. For me, I did "easy apply"s on LinkedIn, 50 a day. These take literally 15 seconds each. I then selected 15 companies a day with a more formal interview process, and sent them a variation of a pre-written cover letter. For my top picks, I tried to find a hiring manager or data scientist on the team, and add them on LinkedIn. I put my name on AngelList, and got many companies reaching out. I humbled myself and told everyone I was more interested in a great learning position, not a great salary. I iteratively changed my own interview methods, including voice tone, inflections, negotiations, honesty levels, until I found a balance that worked for me. You cannot just apply and hope. That is not a method.

Basically, the bootcamp is the first big step. The second big step is learning how to apply and interview. Many people send out 5-10 applications to their top picks (who are often everyone else's top picks as well) and then sit on their hands and wonder why they haven't gotten a job. When entering a new field, you have to make concessions about your salary and place of work, in order to reap the rewards down the line. Also, without multiple options, you will not be able to negotiate because you'll feel this is your only chance. BROADEN YOUR HORIZONS!

Overall:

The camp was the best decision I ever made. I read a book called Design Your Life, which basically said take how you want your life to be, then decide what is necessary to get it there.

I wanted to live in NYC, with a six figure job, working in an office with low stress, and love what I do. NYCDSA made all of that possible. If you have gotten a degree that isn't taking you where you want to be, but you know you're smart and can work hard, I strongly urge you to apply to NYCDSA today.

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Kyle Gallatin
Kyle Gallatin
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Honestly one of the best decisions I’ve ever made. Yes it’s a reasonably difficult course, but if you are truly interested in data science you enjoy every second of it. Like anything, you get out what you put in. If you’re ready to work as hard as you need to in order to master this wealth of knowledge in 12 weeks, this course is 100% for you.

The instructors and TAs are excellent, all accomplished data scientists with a wealth of skill and knowledge. The resources, from slides to code examples and practice questions, are things I will continue to use throughout my career as a data scientist. There is ALWAYS more to learn in the field of data science.

If you’re thinking about going because you simply want a pay raise, then don’t. The course is relatively difficult, and if you aren’t willing to put in the work to master everything you need to land a job, then you won’t get a job. Simple as that.

However, if you are committed to becoming an expert data science, the job support here is immense. There are mock interviews, code interview practice questions, linkedin workshops, presentations from hiring companies and data scientists etc…I myself recently accepted a dream offer from a company I was connected with through the bootcamp.

You likely won’t get a job immediately, it’ll take awhile and a lot of interview practice. It took me about 3 months. If you haven’t mastered the skills you need to be a data scientist, then you don’t have the skills to pass through the interview process. But again, if you are committed there is no shortage of resources made available to you. If you do not succeed here, it is because you did not put as much effort into them as they did into you.

Finally, an underrated part of the experience is the other students. Some of my best friends in the city I met through the bootcamp, and we still go out for drinks all the time. The course not only provides you with knowledge, but connections. It’s a room full of intelligent, driven and entrepreneurial people. You could expect nothing less.

If you want to be a data scientist, and more importantly you have the drive to learn and succeed, you’ll thrive here. Simple as that.

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I was enrolled in the NYC Data Science Academy full-time bootcamp during 1Q17. I found it a very good programme to enhance my computer science skills, particularly in the fields of EDA (exploratory data analysis), machine learning and web scrapping. In my case it was a very good way to upgrade my skill set and enhance my professional profile (originally finance field). Positives: - The program materials are very good (theory and exercises) allowing to properly study the syllabus and find the right balance between theory and practice. - The school staff is very close and dedicated to the cohort and always looking for feedback to improve the experience. - I am more a "lone wolf" type of person but I found useful to be forced to cooperate in one project with other team mates as it allows to have a experience close to what a real job in Data science will be. Things to bear in mind: - You need to have at least a good basic-to-intermediate level in coding. If you never have coded, you better spend 3-6 months preparing yourself using Python and R beginner courses since the programme can be an uphill struggle for those who lack of minimum programming skills. - This bootcamp is very focused on EDA (Exploratory Data Analysis) and Machine Learning. Although big data software like Hadoop or Spark is in the syllabus, it's basically an introduction since the program lasts only 3 months. If you are looking for a pure Big Data experience, this is not your program although it offers a good intro. - This is a non-stop bootcamp so prepare yourself to be fully-committed during the 3 months as you will have to attend lectures in the morning and deliver homework almost on a daily basis. Overall, I enjoyed my time at NYCDSA and think is probably the best bootcamp for professionals looking to upgrade and enhance their computer science skills specializing in Data Science.
 
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Carlos Salas
Carlos Salas
Carlos Salas
Carlos Salas
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I was enrolled in the NYC Data Science Academy full-time bootcamp during 1Q17. I found it a very good programme to enhance my computer science skills, particularly in the fields of EDA (exploratory data analysis), machine learning and web scrapping. In my case it was a very good way to upgrade my skill set and enhance my professional profile (originally finance field). Positives: - The program materials are very good (theory and exercises) allowing to properly study the syllabus and find the right balance between theory and practice. - The school staff is very close and dedicated to the cohort and always looking for feedback to improve the experience. - I am more a "lone wolf" type of person but I found useful to be forced to cooperate in one project with other team mates as it allows to have a experience close to what a real job in Data science will be. Things to bear in mind: - You need to have at least a good basic-to-intermediate level in coding. If you never have coded, you better spend 3-6 months preparing yourself using Python and R beginner courses since the programme can be an uphill struggle for those who lack of minimum programming skills. - This bootcamp is very focused on EDA (Exploratory Data Analysis) and Machine Learning. Although big data software like Hadoop or Spark is in the syllabus, it's basically an introduction since the program lasts only 3 months. If you are looking for a pure Big Data experience, this is not your program although it offers a good intro. - This is a non-stop bootcamp so prepare yourself to be fully-committed during the 3 months as you will have to attend lectures in the morning and deliver homework almost on a daily basis. Overall, I enjoyed my time at NYCDSA and think is probably the best bootcamp for professionals looking to upgrade and enhance their computer science skills specializing in Data Science.
 
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Yvonne Lau
Yvonne Lau

Rochetmiles
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Overall: 

100% YES!!! I wholeheartedly recommend NYC Data Science Academy! If you want to switch into data science, the bootcamp will help you land your dream job. I got an internship offer shortly after the end of bootcamp(~2.5 weeks) through the bootcamp’s hiring partner event, and recently became a full-time data scientist at the same company. All of this would not have been possible without the help of NYCDSA!

Full Review

When I was reading through bootcamp reviews, I personally thought it was more helpful to find people of similar background as mine and see how well they fared.  For instance, knowing that people with only bachelors degree attended NYCDSA and got data scientist jobs helped to not only inspire me, but also to set realistic expectations on what type of jobs I could get and how long it could take. So here is a blurb about myself:

TL-DR;

  • Bachelors degree In math and economics
  • <1 yr of work experience
  • Limited exposure to R/SQL/Big Data tools prior to the bootcamp(Does using a select statement in SQL count?)
  • Prior experience coding in C and basic Python through an intro level computer science course in college. No exposure to data packages in Python.

Prior to coming into the bootcamp, I asked myself: “Is the bootcamp worth the $16,000 investment?” Is it going to give me enough skills to find a job as a data scientist?”. If you read my introduction, the ultimate answer is an obvious YES! Below, I am listing the top 7 reasons why I think NYDSCA was a worth investment for me:

  1. Top-notch job assistance:  From teaching how to craft your resume to preparing for technical interviews, Vivian and Chris did an excellent job at explaining what interviewing for data scientist positions was like. This “soft skill” portion was really important for me since I wasn’t accustomed to interviewing for technical roles. Thank you Vivian for always pushing me to become a better data scientist! Thank you Chris for all the earnest advices on job hunting!
  2. Connections of the bootcamp: As I mentioned earlier, I got my job through the bootcamp’s hiring partner event. Being able to take advantage of the wide network of employers definitely made “getting the foot in the door” much easier
  3. Learning both R and Python: I wanted to learn both as I knew it would help me cover my bases and be prepared for most data science-related jobs.
  4. Transforming me into a confident coder: having learned coding through a class in college and a bit of self-learning, I knew I needed to improve my skills if I ever wanted to land a serious job as a data scientist. The pre-work material along with projects were really helpful in that sense
  5. Structured curriculum: There is a lot of thought put into the structure of each class. It was very nice to have all materials that I needed to learn organized for me so that my only worry was to learn.
  6. Instructors: They deserve their own section as most staff have been teaching for quite a few cohorts. They are all very knowledgeable and approachable. Special shoutout to Zeyu for being an amazing TA and always offering helpful guidance through my projects!
  7. Projects: Each project covers an essential area of data science-data visualization, web scraping, machine learning - and I learned so much through them. The projects were also essential to build my data science portfolio and showcase my skillset to employers.

If you made it all the way to the end, thank you reading this review! All in all, NYCDSA was great!! It worked perfectly for me as it gave me the skills (both technical and soft) I needed to land a data scientist job.  BE PREPARED TO WORK HARD. Treat both the bootcamp and job hunting as a full-time job and you will be rewarded. :)

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Preface:
I attended the July cohort and was then a Data Science in Residence at the NYCDSA prior to accepting an offer for a Data Scientist role at a consulting firm based in NYC. I will do my best in this review to be as straightforward about my experience and address a lot of questions I had prior to the program and have understood a lot of incoming students to have had through prepping them for the program.
My Overall Opinion:
Lets start with this: get over your hesitation, take a leap of faith, and you surely will not regret your decision to attend the NYC Data Science Academy 12 Week Bootcamp. Whatever reservations you have, you are not alone; almost all graduates have felt that prior to attending the program. You may be wondering about if this program will really teach me the necessary skills to get a job, am I prepared enough for this, will the program be rigorous enough, and most pivotally; is this the right decision for me? I cannot speak for you, but I can attest to my own experience and I graduated this program with no regrets, soak in a waterfall of new knowledge and skills, and have walked away a smarter, more capable, more confident professional now employed Data Scientist in field. The program is amazing, and the instructors are passionate, and you will learn a lot, but that also being said, you get as much as you put in and the first step is trusting in yourself to join and commit to the three rigorous and insightful months ahead of you.
My Background:
Prior to attending NYCDSA, I was a software engineer at a large shipping company for almost 2 years focusing primarily on front end development. Before that I attending another bootcamp called Hack Reactor, similar to NYCDSA, to study software engineering and javascript. It was growing interest in machine learning, the success of my experience at Hack Reactor and the thirst for that similar immersive and intensive program that led to me to the NYC Data Science Academy. In another life, I graduated from NYU with a degree in Music Business.
Common Questions:
Do you need a masters or a background in a quantitative field?
The answer is no. No, you do not need a masters degree or professional experience in a quantitative field. During my cohort, I thought some of the best and most creative presentations and chosen topics by students were from some that had no prior coding or heavy math experience. That being said, coming in with a math or software engineering background will definitely allow you to vamp up your projects flashiness and you may have an easier time understanding some of the formulas associated with the advanced machine learning algorithms.
Will I get a job from this program? What are the job stats? etc..
Although I can't attest to job stats, I received my first offer less than 6 weeks after the program ended. I met the firm at the Career Day at the end of the program. Vivian, the CEO of NYCDSA, is the job placement tsar and wizard and without her and her relationships with so many great firms there would not be as many companies at the career day as there are: Spotify, JP Morgan Chase, MindShare, etc.. Vivian will do every in her power to connect you with your dream job. That being said, getting an offer is entirely on you. You must have great visual and complex projects, you must interview well, and you must be actively job seeking and cultivating relationships on your own. Vivian and the team will do everything they can to prepare you and connect you with your dream job, but you need to show up with the bus fair to ride the bus. I cannot stress this enough.
How does this compare to other bootcamps?
I am actually in a unique position to answer this question. A few years prior to graduating NYCDSA, I graduated Hack Reactor, which is a similar 12 week bootcamp, but for software engineering. Prior to that I took web development course at General Assembly, Coursera Machine Learning courses, Harvard Extension School’s Intro to Data Science class to name a few. Needless to say, I’m hungry for knowledge and a challenge. I can’t speak to the other Data Science bootcamps out there like Metis or Galvanize, but I can say that there is nothing like 3 months of learning something at a such a rapid pace. The sum of its parts is greater than the whole and you can spend years learning on your own secondary to whatever else you are doing or you can jump in the deep end. I did before with Hack Reactor and walked away amazed and the same held true for NYCDSA.
Inside Tips:
Pick good project topics. Your projects will be portfolio to potential employers and if your project outshines the other students, employers will take notice.
Pick good project team mates. I didn't have a poor experience with anyone I worked with, but it goes without saying that if you pick bright, easy to work with project partners, you'll be able to build a better end product.
If you don’t know how to code in R or Python and have no prior experience code - Learn now. Codeschool.com is an excellent introductory resource.
DO NOT think you will have a social life. This is only 3 months of your life, but 3 very important months, so give it your all and don't expect to get as much out of it if you don't.
Comments to the Academy:
Scaling the program will require more job assistance personnel.
Increasing the amount of coding done in the program may be beneficial as most jobs now require coding every day and are rarely purely theoretically
Additional content on computer vision would be fun
More TAs and one on one knowledge quizzes (like done as a group at the end of the course)
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Spencer Stebbins
Spencer Stebbins
Data Scientist
CKM Advisors
Spencer Stebbins
Spencer Stebbins
Data Scientist
CKM Advisors
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Preface:
I attended the July cohort and was then a Data Science in Residence at the NYCDSA prior to accepting an offer for a Data Scientist role at a consulting firm based in NYC. I will do my best in this review to be as straightforward about my experience and address a lot of questions I had prior to the program and have understood a lot of incoming students to have had through prepping them for the program.
My Overall Opinion:
Lets start with this: get over your hesitation, take a leap of faith, and you surely will not regret your decision to attend the NYC Data Science Academy 12 Week Bootcamp. Whatever reservations you have, you are not alone; almost all graduates have felt that prior to attending the program. You may be wondering about if this program will really teach me the necessary skills to get a job, am I prepared enough for this, will the program be rigorous enough, and most pivotally; is this the right decision for me? I cannot speak for you, but I can attest to my own experience and I graduated this program with no regrets, soak in a waterfall of new knowledge and skills, and have walked away a smarter, more capable, more confident professional now employed Data Scientist in field. The program is amazing, and the instructors are passionate, and you will learn a lot, but that also being said, you get as much as you put in and the first step is trusting in yourself to join and commit to the three rigorous and insightful months ahead of you.
My Background:
Prior to attending NYCDSA, I was a software engineer at a large shipping company for almost 2 years focusing primarily on front end development. Before that I attending another bootcamp called Hack Reactor, similar to NYCDSA, to study software engineering and javascript. It was growing interest in machine learning, the success of my experience at Hack Reactor and the thirst for that similar immersive and intensive program that led to me to the NYC Data Science Academy. In another life, I graduated from NYU with a degree in Music Business.
Common Questions:
Do you need a masters or a background in a quantitative field?
The answer is no. No, you do not need a masters degree or professional experience in a quantitative field. During my cohort, I thought some of the best and most creative presentations and chosen topics by students were from some that had no prior coding or heavy math experience. That being said, coming in with a math or software engineering background will definitely allow you to vamp up your projects flashiness and you may have an easier time understanding some of the formulas associated with the advanced machine learning algorithms.
Will I get a job from this program? What are the job stats? etc..
Although I can't attest to job stats, I received my first offer less than 6 weeks after the program ended. I met the firm at the Career Day at the end of the program. Vivian, the CEO of NYCDSA, is the job placement tsar and wizard and without her and her relationships with so many great firms there would not be as many companies at the career day as there are: Spotify, JP Morgan Chase, MindShare, etc.. Vivian will do every in her power to connect you with your dream job. That being said, getting an offer is entirely on you. You must have great visual and complex projects, you must interview well, and you must be actively job seeking and cultivating relationships on your own. Vivian and the team will do everything they can to prepare you and connect you with your dream job, but you need to show up with the bus fair to ride the bus. I cannot stress this enough.
How does this compare to other bootcamps?
I am actually in a unique position to answer this question. A few years prior to graduating NYCDSA, I graduated Hack Reactor, which is a similar 12 week bootcamp, but for software engineering. Prior to that I took web development course at General Assembly, Coursera Machine Learning courses, Harvard Extension School’s Intro to Data Science class to name a few. Needless to say, I’m hungry for knowledge and a challenge. I can’t speak to the other Data Science bootcamps out there like Metis or Galvanize, but I can say that there is nothing like 3 months of learning something at a such a rapid pace. The sum of its parts is greater than the whole and you can spend years learning on your own secondary to whatever else you are doing or you can jump in the deep end. I did before with Hack Reactor and walked away amazed and the same held true for NYCDSA.
Inside Tips:
Pick good project topics. Your projects will be portfolio to potential employers and if your project outshines the other students, employers will take notice.
Pick good project team mates. I didn't have a poor experience with anyone I worked with, but it goes without saying that if you pick bright, easy to work with project partners, you'll be able to build a better end product.
If you don’t know how to code in R or Python and have no prior experience code - Learn now. Codeschool.com is an excellent introductory resource.
DO NOT think you will have a social life. This is only 3 months of your life, but 3 very important months, so give it your all and don't expect to get as much out of it if you don't.
Comments to the Academy:
Scaling the program will require more job assistance personnel.
Increasing the amount of coding done in the program may be beneficial as most jobs now require coding every day and are rarely purely theoretically
Additional content on computer vision would be fun
More TAs and one on one knowledge quizzes (like done as a group at the end of the course)
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Lydia Kan
Lydia Kan
Data Scientist
Publicis
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Overall:
I will recommend this bootcamp to anyone who is eager to learn and have great passion towards data science. Before I attended the bootcamp, I received my master degree in marketing from school. I did not have a lot of math and coding background back then. With my passion towards data science, I decided to take a deep dive and applied for the NYCDSA’s 12 weeks bootcamp. Due to my limited coding background, they did not accept me at the beginning, instead, they provided one month prep course for me to get prepared for the bootcamp. I attended the September cohort after the prep course. It was one of the best decisions I have ever made. With the extensive knowledge and training, and great support in job assistance, I am able to land my dream job in 2 months after bootcamp.
Curriculum:
The curriculum is very well designed. I did a lot of research before I applied for this bootcamp. NYCDSA is the only program that covered data science in both R and python, big data processing tools such as Hadoop, Spark at once. I am really glad that I started my journey in data science with them, so my foundation in data science is much stronger now than I was when taking online classes by myself before. The curriculum will also help you to develop a portfolio for job hunting, however, you are the one who decides how much effort you want to put in and how far you want to go.
Instructors:
The instructors and TAs are the best part of the bootcamp. You will never receive this kind of learning experience through online courses. They are all very knowledgeable in computer science, statistics, and machine learning. They are so passionate, and so willing to help each student. There were so many times that they stayed after 7pm, came in during weekends, answered slacks questions at 11pm to provide extra helps. They are far more than just instructors and TAs, but also supportive friends after I finished the program.
Job assistance:
I got hired by a major ad agency as a data scientist within two months of completing the bootcamp.
The hiring team put the best effort to help their students. They hosted awesome hiring partners event, which the students got to make connections and talk to some great companies, such as IBM, citi bank, Mindshare, Publicis and so on. During my job hunting process, Vivian tried her best to provide any connections with the companies that I really wanted to get in. I also received a lot of helps and mentorship from Chris. The way he helped me to prepare for net-working and interviews are very strategic, systematic, and effective. I learned so much and I won’t get this far without him. You can learn all the hard skills anywhere else, but this kind of support and mentorship is hard to find even if you have a lot of money.
They provide as many helps as they can, but you have to be proactive and eager to learn to take everything in!
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I recommend this bootcamp to anyone who wants to transition into the field of Data Science. Before this bootcamp I was a process engineer for a large North American steel company. With the rate of growth in the technology industry, I knew it was time to transition to a new career, and I could have not chosen a better place to do so than NYC Data Science Academy. Instructors: The Instructors were amazing. Chris is extremely knowledgeable in statistics, and his passion for teaching really shines through. With every lecture, he not only shows mastery of the material but also the best way to teach complex materials to a class of non-programmers. Luke goes above and beyond to describe the theory behind the algorithms. His work ethic is shown through the countless hours he has stayed to review lessons with students and believe in continuous improvement. The TAs (Shu, Zeyu) were immense help, and had very good knowledge of big data applications (Hadoop ecosystem, front end work, SQL database design, etc.) Curriculum: The bootcamp offers a good basis for understanding prediction models and when to use which types of algorithms. There just isn't enough time to cover all aspects of statistics and the many branches of prediction models. Both R and Python are taught here, which allows for great flexibility. While this bootcamp is rigorous, self discipline is required to fully delve into algorithms and build impressive products for your portfolio (natural language processing, image recognition, recommendation engines, etc. ; these advanced topics are covered briefly but enough for you to take the reins). All in all I believe the bootcamp set me on the right foot into the industry. Job Assistance: While there is some assistance, the majority of the legwork work is still on the student to be duly diligent - sending out applications, getting interviews, networking and working their way up towards their dream job. There is no easy formula for this, and you MUST continue learning (Algorithms, data architecture, and more advanced ML topics etc. ; network to find out what people in your ideal companies expect you to know) and reviewing material even after the bootcamp to prepare for interviews.
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Charles Leung
Charles Leung
Associate
Societe Generale Corporate and Investment Banking - SGCIB
Charles Leung
Charles Leung
Associate
Societe Generale Corporate and Investment Banking - SGCIB
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I recommend this bootcamp to anyone who wants to transition into the field of Data Science. Before this bootcamp I was a process engineer for a large North American steel company. With the rate of growth in the technology industry, I knew it was time to transition to a new career, and I could have not chosen a better place to do so than NYC Data Science Academy. Instructors: The Instructors were amazing. Chris is extremely knowledgeable in statistics, and his passion for teaching really shines through. With every lecture, he not only shows mastery of the material but also the best way to teach complex materials to a class of non-programmers. Luke goes above and beyond to describe the theory behind the algorithms. His work ethic is shown through the countless hours he has stayed to review lessons with students and believe in continuous improvement. The TAs (Shu, Zeyu) were immense help, and had very good knowledge of big data applications (Hadoop ecosystem, front end work, SQL database design, etc.) Curriculum: The bootcamp offers a good basis for understanding prediction models and when to use which types of algorithms. There just isn't enough time to cover all aspects of statistics and the many branches of prediction models. Both R and Python are taught here, which allows for great flexibility. While this bootcamp is rigorous, self discipline is required to fully delve into algorithms and build impressive products for your portfolio (natural language processing, image recognition, recommendation engines, etc. ; these advanced topics are covered briefly but enough for you to take the reins). All in all I believe the bootcamp set me on the right foot into the industry. Job Assistance: While there is some assistance, the majority of the legwork work is still on the student to be duly diligent - sending out applications, getting interviews, networking and working their way up towards their dream job. There is no easy formula for this, and you MUST continue learning (Algorithms, data architecture, and more advanced ML topics etc. ; network to find out what people in your ideal companies expect you to know) and reviewing material even after the bootcamp to prepare for interviews.
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