Computer Science Classes Live Online

Learn computer science fundamentals with two versatile and powerful programming languages, Java and Python. This 6-week summer course is designed for high school and college students looking to get a head start in programming, or preparing for college-level course work and the AP exam. The certificate program covers everything from programming basics to advanced data science and computer programming concepts. Students also learn Python’s dynamic applications in data science, machine learning, and automation.

This 36-week Foundations of Computer Science and Software Engineering program was designed to teach students the skills they need to launch careers in the fields of computer science and software engineering. This program is split into trimesters and covers a wide range of computer science and programming tools and concepts, including how to work in C and Unix programming, understanding data structures and algorithms, an introduction to higher-level languages like Python, database management and working with SQL, front-end programming, web scraping with JavaScript, and more. Throughout the program, students will also learn important soft skills to enhance their job readiness, with an emphasis around technical writing, collaboration, whiteboarding, as well as the opportunity to participate in mock interviews.

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.

In this 18-hour course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

In this Python automation course, students will learn to automate tasks using Python for various applications. This course is meant for those with prior Python experience looking to learn automation techniques like scheduling programs, updating spreadsheets, and web scraping. Topics include HTML and CSS basics, web scraping techniques, working with spreadsheets using Python, and scheduling scripts. This course offers flexible scheduling options plus a free retake for students to refresh the material.

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.

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.

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.

This data science with Python course is for people with a basic knowledge of programming with Python. This comprehensive course will explain how to work with some of the most widely-used data analysis and visualization modules, such as Pandas, matplotlib, Numpy, Scipy, and more. The course will begin with a review of the basic syntax and data structures of Python before moving on to object-oriented programming, scientific computation, and data visualization. The final unit will teach you how to manipulate data with Pandas before you complete a final project.