Top Melbourne Computer Science Bootcamps

  • General Assembly Python Programming Course

    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.

    In-person @ 12a/45 William St, Melbourne, VIC Also available online
    • $4,500
    • 40 Hours
    • Weekdays or Evenings
    • Beginner
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  • General Assembly JavaScript Course

    Gain fluency in JavaScript — the world's most popular programming language — and start leveraging its versatile capabilities to build rich, interactive websites and applications. This course is offered in person and live online, in a remote classroom setting.

    In-person @ 12a/45 William St, Melbourne, VIC Also available online
    • $4,500
    • 60 Hours
    • Evenings
    • Intermediate
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  • Noble Desktop Java Bootcamp

    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.

    Available live online (virtual training) from anywhere
    • $2,995
    • 72 Hours
    • Weekends
    • Beginner
    • Free Retake
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  • Noble Desktop Python Developer Certificate

    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.

    Available live online (virtual training) from anywhere
    • $4,995
    • 138 Hours
    • Weekdays
    • Beginner
    • Free Retake
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  • Noble Desktop Python for Data Science Bootcamp

    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.

    Available live online (virtual training) from anywhere
    • $1,495
    • 30 Hours
    • Weekdays, Evenings, or Weekends
    • Beginner
    • Free Retake
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  • Practical Programming Python Immersive

    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.

    Available live online (virtual training) from anywhere
    • $1,495
    • 30 Hours
    • Weekdays
    • Beginner
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  • NYC Data Science Academy Introductory Python

    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.

    Available live online (virtual training) from anywhere
    • $1,590
    • 4 Weeks, 5 hr/wk
    • Evenings
    • Beginner
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