About
About
NYC Data Science Academy offers 12-week data science bootcamps in New York City. In these programs, students learn beginner and intermediate levels of Data Science with R, Python, Hadoop, Spark, Github, and SQL as well as popular and useful R and Python packages like XgBoost, Caret, dplyr, ggplot2, Pandas, scikit-learn, and more. Once the learning foundation has been set, students work on multiple projects through the bootcamp. The program distinguishes itself by balancing intensive lectures with real world project work, and by the breadth of its curriculum. Throughout the program students work alone and in teams to create at least four projects that are showcased to employers through multiple channels; private on-campus hiring partner events, student blogs, meetups, and filmed presentations.
Ideal applicants should have a Masters or PhD degree in Science, Technology, Engineering or Math or equivalent experience in quantitative science or programming. Candidates with BA’s who have appropriate experience are also considered.
Throughout the data bootcamp, students are assisted in preparing for the employment process through resume review and interview preparation. NYC Data Science Academy works closely with hiring partners and recruiting firms to create a pipeline of interest for its students.
Recent NYC Data Science Academy Reviews: Rating 4.84
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Courses
Courses
12-Weeks In-Person Data Science Bootcamp
ApplyMySQL, Data Science, Git, R, Data Visualization, Hadoop, Spark, Linux, Data Analytics , SQL, Python, Machine Learning
In PersonFull Time420 Hours/week12 WeeksStart Date None scheduled Cost $17,600 Class size 50 Location New York City In this program students will learn the modern data analytic techniques and master the requisite skills, such as Python and R programming languages as well as Hadoop, to address real-world data science problems. Throughout the program, students work alone and in teams to create at least five projects that are showcased to employers. Along the way, students will have assistance in preparing for the job search through resume review, interview preparation, and opportunities to interview with our hiring partners. Successful completion of the curriculum will present a certification of graduation certified by the New York State Board of Education.Financing
Deposit $5,000 Financing - Full Tuition Total $17,600
- Climb Credit Loan $400* pm for 60 months
- SkillsFund Student Loan
$397.88 pm for 60 monthsTuition Plans We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months. Refund / Guarantee NYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details. Scholarship Limited number of scholarships available to qualified candidates. Getting in
Minimum Skill Level Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming. Prep Work http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/ Placement Test No Interview Yes
Big Data with Amazon Cloud, Hadoop/Spark and Docker
ApplyData Science, Hadoop, Spark, Data Structures, Python, Cloud Computing
In PersonPart Time5 Hours/week2 WeeksStart Date None scheduled Cost $2,990 Class size 10 Location New York City This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.Financing
Deposit N/A Getting in
Minimum Skill Level Students are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful. Placement Test No Interview No
Data Science with Python: Data Analysis and Visualization (Weekend Course)
ApplyData Science, Data Visualization, Data Analytics , Data Structures, Algorithms, Python
In PersonPart Time4 Hours/week6 WeeksStart Date None scheduled Cost $1,590 Class size 20 Location New York City, Online This five week course is an introduction to data analysis with the Python programming language, and is aimed at beginners. We introduce how to work with different data structure in Python. We covered the most popular modules, including Numpy, Scipy, Pandas, matplotlib, and Seaborn, to do data analytics and visualization. We use ipython notebook to demonstrate the results of codes and change codes interactively during the class. Our past students include people with no programming experience or those who have minimal exposure to Python. Students told us our classes are very informative, engaging, and hands-on.Financing
Deposit N/A Refund / Guarantee NYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details. Getting in
Minimum Skill Level Knowledge of basic data types (e.g. string, numeric), data structures (e.g. list, tuple, dictionary) Familiarity with concepts of list comprehension and for/while loop Placement Test No Interview No
Data Science with Python: Machine Learning (Weekend Course)
ApplyStart Date None scheduled Cost $1,990 Class size 10 Location New York City, Online This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. This includes linear regression, Naïve Bayes classifiers, logistic regression, linear discriminant analysis, cross-validation, bootstrapping, feature selection, regularization, model selection, SVM, decision trees, random forest, PCA, K-Means, and Hierarchical clustering. In addition, this course teaches the basics of natural language processing. After successfully completing this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.Financing
Deposit N/A Getting in
Minimum Skill Level Completion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning Placement Test No Interview No
Data Science with R: Data Analysis and Visualization (Weekend Course)
ApplyData Science, R, Data Visualization, Data Analytics , Data Structures
In PersonPart Time7 Hours/week6 WeeksStart Date None scheduled Cost $2,190 Class size 15 Location New York City, Online This course is designed to provide a comprehensive introduction to R. Students will practice programming and analyzing data with R. Students will learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models to data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis. This course also covers the creation of dynamic reports with the knitr package in R as well as the creation of dynamic dashboards with R Shiny. By the end of the course, students will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting the code.Financing
Deposit N/A Getting in
Minimum Skill Level Basic knowledge about computer components Basic knowledge about programming Prep Work None Placement Test No Interview No
Data Science with R: Machine Learning (Weekend Course)
ApplyStart Date None scheduled Cost $2,990 Class size 40 Location New York City, Online This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems. Unit 1: Foundations of Statistics and Simple Linear Regression Unit 2: Multiple Linear Regression and Generalized Linear Model Unit 3: kNN and Naive Bayes, the Curse of Dimensionality Unit 4: Tree Models and SVMs Unit 5: Cluster Analysis and Neural Networks Final Project After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged.Financing
Deposit N/A Getting in
Minimum Skill Level Knowledge of Python programming Able to munge, analyze, and visualize data in Python Prep Work Knowledge of R programming Able to munge, analyze, and visualize data in R Placement Test No Interview No
Deep Learning with Tensorflow (Weekends and In-Person Only)
ApplyData Science, Game Development, Artificial Intelligence, Python, Machine Learning
In PersonPart Time6 Hours/week6 WeeksStart Date None scheduled Cost $2,990 Class size 15 Location New York City Via analogy to biological neurons and human perception, this course is an introduction to artificial neural networks that brings high-level theory to life with interactive labs featuring TensorFlow, the most popular open-source Deep Learning library. Essential theory will be covered in a manner that provides students with an intuitive understanding of Deep Learning’s underlying foundations. Paired with hands-on code run-throughs in Jupyter notebooks as well as strategies for overcoming common pitfalls, this foundational knowledge will empower individuals with no previous understanding of neural networks to build production-ready Deep Learning applications across the major contemporary families: Convolutional Nets for machine vision; Long Short-Term Memory Recurrent Nets for natural language processing and time series analysis; Generative Adversarial Networks for producing realistic images; and Reinforcement Learning for playing video games.Financing
Deposit N/A Getting in
Minimum Skill Level Object-oriented programming, ideally Python (introductory course: https://nycdatascience.com/courses/introductory-python/) Simple shell commands, e.g., in Bash (tutorial of the fundamentals: https://learnpythonthehardway.org/book/appendixa.html) Placement Test No Interview No
Full-time Online Data Science Bootcamp
ApplyMySQL, Data Science, Git, R, Data Visualization, Hadoop, Spark, Linux, Data Analytics , SQL, Python, Machine Learning
OnlineFull Time28 Hours/week12 WeeksStart Date None scheduled Cost $17,600 Class size 25 Location Online This program was designed for students that have the time to be a full-time student, but can't commute to our school. Students will be placed on a rigorous curriculum that spans from 9:30 AM to 6:00 PM EST as well as have access to prerecorded modules with over 1000 coding challenge questions on online learning platform for additional practice. In addition, they have access to dedicated TA’s as well as the larger network of a shared slack channel between both in-person and remote bootcamp students. Classes: You will learn streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Personalized Job Support: Students also have access to the full resources of NYC Data Science Academy to help them find their dream job upon graduation. 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.Financing
Deposit 5000 Financing - Full Tuition Total $17,600
- Climb Credit Loan $400* pm for 60 months
- SkillsFund Student Loan $397.88 pm for 60 months
Tuition Plans We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months. Refund / Guarantee NYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details. Scholarship Limited number of scholarships available to qualified candidates. Getting in
Minimum Skill Level Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming. Prep Work http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/ Placement Test No Interview Yes
Introductory Python (Evenings)
ApplyMySQL, Data Science, Data Visualization, Data Analytics , Data Structures, Algorithms, Python
In PersonPart Time5 Hours/week2 WeeksStart Date None scheduled Cost $1,590 Class size 40 Location New York City This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web. This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class.Financing
Deposit $1590 Refund / Guarantee NYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details. Getting in
Minimum Skill Level This Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming. Prep Work In the class, we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video. Link: https://vimeo.com/160172414 Placement Test No Interview No
Part-time Online Data Science Bootcamp
ApplyData Science, R, Data Visualization, Spark, Virtualization, Data Analytics , Data Structures, Artificial Intelligence, SQL, Python, Machine Learning
OnlinePart Time28 Hours/week26 WeeksStart Date None scheduled Cost $17,600 Class size 25 Location Online This is an online part-time self-paced program. Students have 4 - 10 months to complete this program. The curriculum is the same as our on-campus program, with full-financing options, career support and with a one on one support from our mentors. This program is designed for students that work full-time and are not able to quit their jobs. Our curriculum is drawn from data science engagement with corporate consulting and training, hiring partners and active industry participation. 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. 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. 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.Financing
Deposit 17600 Financing - Full Tuition Total $17,600
- Climb Credit Loan $400* pm for 60 months
- SkillsFund Student Loan $397.88 pm for 60 months
Tuition Plans We have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months. Refund / Guarantee NYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details. Scholarship Limited number of scholarships available to qualified candidates. Getting in
Minimum Skill Level Ideal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming. Prep Work http://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/ Placement Test No Interview Yes
Reviews
NYC Data Science Academy Reviews
- Rewarding and challenging experience!- 5/14/2019Eric Adlard • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
The NYC Data Science Academy is an amazing place to get started if you are looking to make a transition into Data Science.
That being said, you really need to do the pre-work before the boot camp and having math and stats knowledge is very helpful. The program is very challenging and covers a broad range of material to get you exposed to the vast realm that is 'Data Science'.
You will work with great instructors who are extremely helpful and really care about the students. If you put in the effort it is truly a transformative experience. I could not have landed my most recent job without the skill set I acquired in this boot camp. Finally, you will also make a few friends along the way with your great classmates :)
- Rewarding experience!- 5/12/2019Derek Li • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
I attended the immersive 12-weeks bootcamp during fall cohort 2018. It took me a while to write this review because I am busy but happily working as a Data Scientist, solving exciting and challenging data problems.
The instructors are very attentive and helpful. If you are Math/Statistics background, it would help a lot during the bootcamp. But the instructors make sure you understand the theories through well-designed course structure, examples and practices no matter what your background is.
Not only do they teach you on data science and technical tools, but they also offer exceptional advice on searching and interviewing for jobs. Their support is amazing and is what helped me get my current job. Special thanks to Luke and Vivian!
The immersive program was intense but I also learned a lot from fellow students. I made a lot of great friends through the bootcamp. You get to know people from various academic backgrounds and industries. You would learn how they formulate solutions to data problems in their domain, which are always enlightening. Shout out to team JLP aka team Ostrich Pillow!
- Great bootcamp- 5/8/2019Mimi • Data Analyst • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
The bootcamp provided absolutely everything we needed to boost our resume and give us the skills we needed to start out as a Data Analyst or Scientist. I was offered a position and started working immediately after the bootcamp, and it was due to the resume tweaking and data analysis skill set that I obtained in such a short time.
- Pranati Jain • Course: Data Science with Python: Data Analysis and Visualization (Weekend Course) • Campus: New York City • Verified via GitHub
I attended the 5 week Python course with Anthony Schultz . The syllabus was extremely comprehensive and provided a very well structured approach to Python and its applications. Anthony was a fantastic teacher and effectively covered a wide range of concepts and topics in a short time period. I enjoyed the weekly homework problems as well - they cemented what was learnt in class and really made me think. I feel a lot more comfortable in my coding abilities and would highly recommend this course.
- Confidence-Inspiring !- 4/15/2019Bob Trieste • Finance & Investments • Course: Data Science with Python: Data Analysis and Visualization (Weekend Course) • Campus: New York City • Verified via GitHub
New York Data Science Academy & Python for Data Anslysis and Visualization
This course was not only extremely cutting-edge for all of today's industries and work areas but it gave me a great deal of confidence to continue my data and computer science studies at the next level. This course has actually inspired me to not only enroll in other NYC Data Science Classes but also think longer-term about continuing graduate level work in CS. This was my first class at NYCDSA and all I an say is I am extremely grateful to have had Dr. Anthony Schwartz as an instructor. Anthony kept the material vibrant and fun with colorful analogies that made the subject matter easy to digest and remember. This allowed for both an esoteric understanding of what was happening "inside the code" coupled with real-world applications that began to streamline and automate a lot of my day-to-day work right after Class 1.
I cannot day enough good things about NYCDSA and Dr. Shultz !!
Bob Trieste
Long Island, NY
- Thorough introduction to Python Data Analysis- 4/14/2019Trang Nguyen • Student • Course: Data Science with Python: Data Analysis and Visualization (Weekend Course) • Campus: New York City • Verified via LinkedIn
I had the Python Data Analysis class with Tony. He did a great job in explaining Python in details and gave specific examples every time new knowledge was introduced. I would definitely take his class again.
- Great Bootcamp- 3/28/2019Chaoran Chen • Data Engineer • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
Great Bootcamp.
The program is very comprehensive and intense. The syllabus is well structured. They make sure your time is only spent on most popular and useful technologies which are needed for a Data Scientist.
The instructors are very responsive. They also hold events to build the relationship between you and the potential hiring partners.
- Not for everyone, but can be really great.- 3/18/2019John • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
This is perfect for you if you already have some coding and math background and want to tie it all together into data science. The instructors are invested and clearly know their stuff, but with this kind of material you really need to apply yourself and study on your own to gain a complete understanding. You will acquire a good foundational understanding of machine learning techniques, but I think even more valuable is the broad (though in some places not super deep by necessity) exposure to lots of different data science and data engineering tools (R, pandas, AWS, Spark, Hadoop, Keras). The field is huge, and this is a good place to start. You can go a lot of different directions with the knowledge you gain here.
- Fantastic Bootcamp- 3/13/2019James Lee • Data Analyst III • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
Fantastic Bootcamp. I was able to gain a solid fundamental on Python, R, and Data Science skills. I was able to start my career and advance quickly in this field. Be sure to be ready to climb up a steep learning curve with highly knowledgeable mentors. The job assistance has been great and Vivian has always provided me with stellar recommendations and references.
- Data Scientist- 3/11/2019Thomas Deegan • Data Scientist • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via GitHub
I could not have been happier with the bootcamp experience I had at NYC Data Science Academy. The staff was incredible and does an amazing job of designing a curriculum and creating an environment for a broad range of participants to develop their data science skills. They are constantly working to update the curriculum and are very open to feedback.
I gained a great deal of confidence with both the theory and applications behind supervised and unsupervised machine learning methods, data analysis, statistics, data visualization, and big data tools. I became very comfortable with both Python and R and completed four projects that were enormously helpful come interviewing time. Post-bootcamp, I received several job offers as a Data Scientist that I was very pleased with.
Perhaps most importantly, should you decide to attend this bootcamp, you'll be joining a constantly growing alumni network. There will be endless opportunities for networking, corporate training, and engagement.
I would highly recommend this bootcamp to an aspiring data science professional.
- Fantastic 12 week DS bootcamp- 2/20/2019Tristan Dresbach • Data Scientist • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
I didn't have a coding background and I was hired as a data scientist after graduating from the bootcamp.
The program is extremely comprehensive, with challenging problem sets and 4 mandatory projects to showcase your abilities. The support staff (TAs, teachers and bootcamp management) are always available and are more than helpful when job hunting. Not only does the bootcamp have deep connections with a multitude of firms, but they also setup a networking event for recent graduates to meet potential future employers which is how I ended up finding a job.
- Deep Learning- 12/20/2018Navin Krishnakumar • Applicant • Course: Deep Learning with Tensorflow (Weekends and In-Person Only) • Campus: New York City • Verified via GitHub
Deep learning course conducted by Jon offers a great learning experience for people starting with their journey on deep learning. Jon starts with the basics and gradually moves on the advance topics. The topics are shared well in advance so that we can prep ourselves before the class. Jon mixes the intuitiveness and the mathematics on the topic in a balanced way. As part of the course, Jon also encourages everyone to do a project and offers great support. My only piece of constructive criticism (which by the way is not at all a criticism) would that the last class is a bit heavy content wise and hence breaking it down a little would be something to consider. Overall, I would highly recommend this course to someone who wants to start with deep learning.