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Part-time, self-paced

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.

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.

Learning Roadmap

4 Months
Commit 25-30 hours/week
(Recommended)
Typical Schedule
Week 1: Data Science Toolkit
Week 2-3: Data Analysis and Visualization with R
Week 4-5: Data Analysis and Visualization with Python
Week 6-12: Statistics and Machine Learning with R
Week 13-15: Machine Learning with Python
Week 16-18: Advanced Topics in Deep Learning and Big Data
Week 19: Final Review Week and Final Exam
Other Options:
6 Months
Commit 15-18 hours/week
10 Months
Commit 8-12 hours/week
Want to commit full-time to learning data science?

Curriculum

Our curriculum covers the expanse of all the skills required in the data science industry. We cover both R and Python as well as Machine Learning Theory, Big Data, and Deep Learning.

Our program is among the highest ranked on both Course Report 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.
Unit 6
Data Engineering/Big Data Track
Learn database management tools such as AWS, NoSQL, MongoDB. Introduction to MapReduce, Hadoop, Hive, Spark, and Spark MLlib.
Deep Learning Track
Build Deep Learning models in TensorFlow. Acquire knowledge and skills in Machine Visions, Natural Language processing, Time Series Analysis, and Reinforcement Learning.
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 >

Tuition and Financial Option

Tuition
$17,600 USD
Financial Option

We partner with Skills Fund, and innovative financing company who offers fixed interest rates on 3- and 5-year loands, regardless of current income, employment, or educational background.

Learn More

Student Testimonials

William Zhou, Informatics Specialist
William Zhou, Informatics Specialist

Memorial Sloan Kettering Cancer Center
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WHY Data Science and WHY NYCDSA: I had no idea about data science until 2016 Feb when Alphago defeated Li Shishi and it was the first time for me to get to know what is Artificial Intelligence and what is machine learning. Bringing my huge curiosity, I self-learnt an online Machine Learning course on Coursera and was able utilize the skill , for the first time, in my working project and had a positive outcome. Being proud of my achievement, I also realized there was still a long way down the road.  This is actually the reason why I decided to join bootcamp -  fully armed myself with comprehensive data science skillset and then shifting my career towards a new page. NYCDSA is a perfect choice for me as it teaches anything you need to know to work as junior data scientist and allows you to keep full time job as the same time.

Experience: Even though it is an part-time online bootcamp, I was investing 40+ hours / week on studying slides, having office hour with TA and doing projects with current full time students. The bootcamp starts with an introduction Toolkits (Unix,Git,SQL,etc.), followed by introduction to R/Python, then followed by statistics and machine learning immediately applied using R and Python. The comprehensive curriculum is completed by an introduction to Big Data tools. I was able to finish a strong portfolio with 4 projects in Shiny App, Web Scraping, Kaggle and Capstone. I learned a lot especially by collaborating with full time students and TAs, so I would strongly recommend those online students who are physically in NYC, walk in the classroom and collaborate with full-time students on your last two projects.

In terms of job assistance, NYCDSA can provide tremendous assistance on your job hunting after your graduation. Vivian and Chris know what you need to have on your resume to catch HR’s eye and get an interview, and they have a strong network which can expose you to much more opportunities.

Outcome: I finally received offer from 2 Top insurance companies, 2 Top hospitals, and 2 boutique consulting companies. I feel my investment of 7 months of study and $16K totally worth as it allows me to finally launch my dream job. Thank you New York City Data Science Academy and I would recommend it to anyone who has same dream to be a data scientist.

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The motivation for attending a data science bootcamp generally starts with reading testimonials, which are the experiences and thoughts of past fellows. I believe that my experience as a remote participant in the Summer 2017 bootcamp is unique as the NYC Data Science Academy made it live stream to me throughout the bootcamp. This is totally different experience than doing bootcamp online as I was able to join lectures, industry expert speaker sessions, and workshops as the fellows did in person. This was indeed a great opportunity for me as I was able to ask my questions during the lectures and seminars and participated actively with my comments. The crucial point here is that live streaming the bootcamp and communicating through Slack channel made it possible for the team at the Academy to track my progress in the assignments and projects daily and encouraged me to participate fully in the bootcamp.
I can definitely say that attending the NYC Data Science Academy bootcamp was one of the greatest investments in my life. I learned how to code efficiently in R and learned to code in Python with real-life projects. I am hundred percent sure that my attendance to the bootcamp let me to find my current data science related post doctoral position. I could suggest future candidates take some initial online courses for machine learning and deep learning, where they will find themselves more comfortable while approaching highly-technical projects in the bootcamp.
One of the strongest sides of this bootcamp at the NYC Data Science Academy is the time and effort that the hiring team spends on. For remote participants, this is much more valuable than any other thing as you are receiving constant help in finding the best job depending on your portfolio. And you feel that you are a member of an excellent group of data scientist. As an active learner of data science field, I recommend the NYC Data Science Academy with full of confidence.
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Mustafa Koroglu
Mustafa Koroglu
Mustafa Koroglu
Mustafa Koroglu
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The motivation for attending a data science bootcamp generally starts with reading testimonials, which are the experiences and thoughts of past fellows. I believe that my experience as a remote participant in the Summer 2017 bootcamp is unique as the NYC Data Science Academy made it live stream to me throughout the bootcamp. This is totally different experience than doing bootcamp online as I was able to join lectures, industry expert speaker sessions, and workshops as the fellows did in person. This was indeed a great opportunity for me as I was able to ask my questions during the lectures and seminars and participated actively with my comments. The crucial point here is that live streaming the bootcamp and communicating through Slack channel made it possible for the team at the Academy to track my progress in the assignments and projects daily and encouraged me to participate fully in the bootcamp.
I can definitely say that attending the NYC Data Science Academy bootcamp was one of the greatest investments in my life. I learned how to code efficiently in R and learned to code in Python with real-life projects. I am hundred percent sure that my attendance to the bootcamp let me to find my current data science related post doctoral position. I could suggest future candidates take some initial online courses for machine learning and deep learning, where they will find themselves more comfortable while approaching highly-technical projects in the bootcamp.
One of the strongest sides of this bootcamp at the NYC Data Science Academy is the time and effort that the hiring team spends on. For remote participants, this is much more valuable than any other thing as you are receiving constant help in finding the best job depending on your portfolio. And you feel that you are a member of an excellent group of data scientist. As an active learner of data science field, I recommend the NYC Data Science Academy with full of confidence.
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Thomas Kassel, Data Scientist
Thomas Kassel, Data Scientist

Carbon Lighthouse
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I spent my undergraduate years focusing on the life sciences without much formal educational background in programming and advanced statistics. While working as a data analyst my first few years out of college, I gained practical coding experience in R, picking up general programming and modeling experience - even still, I lacked the underlying foundation needed to understand and implement more complex machine learning for my projects at work. The NYCDSA online bootcamp was the perfect blend of machine learning theory and practical, hands-on projects helping to solidify the lecture concepts. The overall experience was intense: I worked full-time at my day job and spent most of my free time (~30 hours/week) keeping up with lectures, course projects and career development - but got out an incredible learning experience, which helped me to perform more advanced projects at my current job and ultimately to find a new full-time data science role. My TA, meeting with me at least weekly, along with my online cohort of 4 other students, held us all accountable for staying on track with course deadlines and project work. This accountability was a crucial component in keeping us motivated throughout the 5 months; other online programs fail to do this and suffer student dropout as a result. Another invaluable outcome of the program is the portfolio of projects (~5), which NYCDSA greatly emphasizes and helps groom. I used these as a demonstration of my experience (both from a coding standpoint on GitHub, and data storytelling standpoint, on the NYCDSA blog) in almost all job applications. While one does not need to attend a bootcamp in order to create a project portfolio, NYCDSA makes sure to curate and grade the assignments so as to demonstrate in the portfolio an important mix of technical skillsets sought in the job market, and holds its students to higher standards of work quality than they might hold themselves.
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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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Wann-Jiiun Ma, Fraud Data Scientist
Wann-Jiiun Ma, Fraud Data Scientist

Citi Bank
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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Shin Chin, Senior Data Scientist
Shin Chin, Senior Data Scientist
Associate - Senior Data Scientist
Booz Allen Hamilton
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I am really enjoying taking the NYC Data Science Academy data science bootcamp remotely. I find their online classroom and materials very effective for learning the fundamentals of data science. The videos are very informative and the material well communicated and taught by the lecturer. The accompanying slides are clearly written and mostly self contained and you can learn a lot, just by reading them. The course is a nice blend of theory and practical programming experience using R and Python and other tools. The learning process is aided by doing and submitting the homeworks for the lecture materials, as well as completing project assignments. I interact frequently with the TA assigned to me. We often have Google hangout sessions where he helps set up my environment on my laptop like Git, R and Python. We also review my project assignments through Google hangouts where he provides valuable feedback and suggestions. The TA is very helpful, competent and knowledgable. I would definitely recommend the online version of this bootcamp.
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