Data Science Bootcamp Curriculum

Get Your Copy of the NYC Data Science Academy Bootcamp Curriculum


Our Data Science Course Curriculum covers everything you will cover during our 12 week Data Science Bootcamp.  Our data science bootcamp curriculum covers:

  • Data Science Toolkit
  • Git
  • SQL
  • Data Analytics with R
  • Shiny Apps
  • Statistics
  • Data Analytics with Python
  • Numpy
  • Pandas
  • SciPy
  • Developing Data Science Business Cases
  • Machine Learning
  • Advanced Data Science Topics
    • Neural Networks
    • Scalability
    • Cloud Computing
  • Capstone Project

Our Data Scientist Bootcamp Curriculum has been designed to transform you into an in-demand, highly compensated data scientist.  It is based on constant industry feedback and is continuously updated to reflect the latest developments in the industry. 



Why the NYC Data Science Academy?

NYCDSA Switchup Award

Recognized as the Best Data Science Bootcamp for 2016, 2017, 2018, 2019, and 2020

Get Your Copy of the Data Science Bootcamp Curriculum

Secure a spot of a highly competitive program if you submit your application today,  apply now

Best Data Scientist Bootcamp Reviewed

Best Reviewed Bootcamp

Our data science bootcamp has been rated the best one in the United States for the past three years

Complete Data Scientist Bootcamp Curriculum

Complete Curriculum

The only bootcamp that teaches both Python and R with machine learning, data analytics, and data visualization

Cutting Edge Data Scientist Training Course


Curriculum drawn and updated through the engagement with corporate trainees, hiring partners, and leading industry experts

Project Oriented Real World Data Scientist Projects


Four real-world and company-sponsored projects including a capstone to develop your programming and professional skills

Data Scientist Career Services

Career Services

Lifelong career support including one-on-one resume reviews, interview prep, and exclusive access to networking opportunities with our hiring partners

Engaging Data Scientist Community

Engaging Community

An active community of 2000+ working data scientists, like-minded peers, and data experts across various fields

Dean Goldman Data Engineer

"After graduating, I was offered my first full-time job as a data engineer. (I do not come from a CS, math or stats background). They are very successful at getting their students fluent in the tools and technologies, and prepared for finding great jobs in the field."

Dean Goldman
Data Engineer, Samsung Ads
Elsa Vera Amores, Data Scientist

"I learned everything I know about machine learning from the bootcamp. The curriculum gives you all the tools you need to develop your data science skills for the job."

Elsa Vera Amores
Data Scientist, JP Morgan Chase
Kweku Ulzen, Senior Data Scientist

"It's the hardest three months you'll ever experience. But at the end, it's really worth it. My advice is to be prepared for a very tough, but rewarding experience."

Kweku Ulzen
Senior Data Scientist, Nielsen

Unit 1

Data Science Tool Kit

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 & Data 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 & Data Visualization with Python

Basic Python programming, followed by versatile packages such as Numpy, Scipy, Matplotlib, Pandas, and Beautifulsoup. 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, PCA, ridge/lasso, trees, random forests, bagging, boosting, support vector machines, neural networks, time series analysis, 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, natural language processing, modeling and model selection using regression, SVM, PCA, tree models, clustering and more.

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 and Job Placement Support

Complete a capstone project. Resume review, tips of interview skills, and opportunities to interview with potential employers. Receive customized resume support, LinkedIn profile review, elevator pitch workshops and career guidance, and more.

Join thousands of our graduates who have landed jobs in these companies


Data Scientist Employing Companies