Computer Science Classes Hartford, CT

Become a Software Engineer or Full Stack Developer in this immersive course. Master the front-end using HTML, CSS, JavaScript, and React; build the back-end with Python, Django, and Node.js. You'll also learn Git for version control, Flexbox and Grid for layout, MongoDB for creating data structures, and much more. Throughout the program, you'll build a portfolio of projects to help you secure a career in software and development. 

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.

Become a JavaScript Developer with this immersive certificate program. Learn object-oriented programming (OOP), create APIs, and learn popular frameworks and libraries to build functional and responsive websites. Over the course of this class, you'll learn fundamentals for JavaScript programming, front-end development with ReactJS and React Native, and back-end development with Node.js and Express.js. You'll also harness the power of MongoDB to organize and store your data. This class includes one-on-one mentoring and portfolio development to prepare you for a career after graduation.

This 5-day introductory Python programming course is designed for students with no prior programming experience and are looking to get comfortable with basic skills needed for Python programming. This skills-centric course will cover foundational Python concepts, including data types, control statements, using functions and modules, handling exceptions and debugging programs, working with lists, and how to work with a variety of data types. By the end of the course, students will be familiar with writing programs to create real-world Python applications.

In this 2-day introductory Python course, participants will learn the fundamentals of Python programming. This hands-on course will give students with no prior Python experience the foundational programming skills needed to continue learning Python’s applications in data science or web development. Topics include Python environment setup, programming concepts, Python syntax, and more. This course offers flexible scheduling options and provides a free retake for students to refresh the material.

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 course on data wrangling with Python offers a 3-day comprehensive introduction. The purpose of this course is to give an immersive foundation that equips students with the most critical data analysis tools. Students will learn how to work with NumPy, Pandas, and MatPlotLib to calculate descriptive statistics, work with alternative data sources, and scrape web pages. The course culminates with a real-life data wrangling project.

This 2-day course on Python with data science is intended for software developers, IT architects, and data scientists. This course will build on their knowledge of statistics and programming, teaching them the theoretical and technical aspects of the use for Python. Students will learn about the history and purpose of data science, life-cycle phases of data analytics, methods for repairing and normalizing data, and how to aggregate and group data. Students will also complete 10 lab exercises.