Computer Science Bootcamps New York

Get to know one of the most widely-used programming languages in the world at this 5-day Java bootcamp. Students get started with Java and use it to learn essential computer science principles such as object-oriented programming, solving programming problems, developing algorithms, understanding recursion, and working with data structures. This bootcamp prepares participants to take the Java SE 11 Programmer 1 Exam.

Learn the essential skills and tools to become a Python Developer. This beginner-friendly course teaches students Python for software development with Django and Django REST in addition to other developer tools such as Git and SQL. After completing this certificate, students will be able to apply for the following roles: Python Developer, Back End Developer, Software Engineer, and many more.

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

This 1-week Python Immersive is geared towards beginners with no prior coding experience and meant to give students a fundamental understanding of Python to start coding on their own. Students will learn best practices for coding with Python, work on exercises and programs in Python, and conclude with 2 projects of their own.

This course provides an introduction to the use of Python programming language for data analysis. Python, through the use of list and string manipulation, control structures, and data analysis packages, can be used to manage and analyze large sets of data. In this course, you will learn how to use Scipy, Numpy, Pandas, Seaborn and matplotlib to analyze data and create visualizations. This course has 4 units, covering list manipulation, strings and simple I/O, control structures and data analysis packages. IPython notebook is also used to show how codes and change codes are used during class.

Build dynamic websites and applications with React and React Native. In this 60-hour bootcamp, you'll develop several fully-functioning apps. You'll start by learning how to compose components and deploy a React project to a server, then move to more advanced React Native development and API integration. By the time you complete the course, you'll have acquired core skills for a career as a Front End Developer. The React Bootcamp allows students who already know the fundamentals of JavaScript programming and basic HTML & CSS to take their skills to the next level.

This 1-week data analytics course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

Gain fluency in Python — the world's fastest-growing major programming language — and start leveraging its versatile capabilities to build web and data science applications. This course is offered in person and live online, in a remote classroom setting.

This certificate program offers an introduction to Python programming. With online and on-campus options, students will learn from expert programmers. The curriculum will begin with syntax, data types, and operators before moving on to more advanced data types and the fundamentals of algorithms. Students will also learn about data manipulation and Python utilities.

Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling.