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Learn Numba with online courses and programs

Numba is an open-source compiler that translates a subset of Python code into machine code. Explore how to learn Numba and leverage its capabilities to make your Python programs run faster.

What is Numba?

Numba is a just-in-time (JIT) compiler for Python that accelerates numerical computations and performance optimization.Footnote 1 It allows developers to write Python code that can compile into machine code for efficient execution on central processing units (CPU) or graphics processing units (GPU).Footnote 2 This results in speedups for numerical computations without sacrificing the ease of use and flexibility of Python.

Numba dynamically compiles Python code during runtime, optimizing performance for specific functions using decorators like “@jit” and “@njit”.Footnote 3 It can work well with popular Python libraries like NumPy and Pandas. You can also extend Numba SciPy in Numba to optimize SciPy algorithms.

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Numba tutorial curriculum

There are a variety of online courses and tutorials where you can learn Numba. A Numba course may start with introductory concepts, covering: what Numba is; how to install it; how to begin using it; what a decorator is; and how to use a decorator. 

Once you’ve grasped the basics, you can move on to intermediate Numba concepts, which may include:

  • Difference between Cython and Numba 

  • Difference between Numba and PyPy 

  • Using Numba with pandas 

  • Numba CUDA GPU acceleration 

  • Numba parallelization 

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Explore jobs that use Numba

Numba can be a valuable tool in various fields where numerical computing and performance optimization are important. Understanding how to use Numba can be helpful in roles such as:

  • Data scientist: Collects, analyzes, and interprets large datasets using statistical methods, machine learning, and data visualization to derive insights and develop data-driven solutions.Footnote 4

  • Python developer: Codes, tests, and designs software applications using the Python programming language. A strong grasp of Python leads to the effective use of Numba.

  • Machine learning engineer: Designs and develops machine learning models and systems that can derive insights from data.

  • Quantitative analyst: Creates mathematical models and algorithms to analyze financial data and derive insights.Footnote 5

Each of these roles will have different education and skills requirements. For example, you may be able to build relevant skills in a coding boot camp. However, some employers may seek candidates with a degree in computer science or engineering, depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.

How to use Numba in your career online

Numba can be incredibly valuable for data science professionals conducting data analysis and scientific computations. Data science applications of Numba may include optimizing numerical computations, such as data preprocessing, feature engineering, and model training. Numba for Python can accelerate performance-critical parts of data science pipelines. It enables faster data processing and model training, which can be particularly beneficial for handling large datasets or time-sensitive tasks.

If you are interested in working as a data scientist, you will likely need at least a bachelor’s degree in mathematics, computer science, engineering or a related field that can provide you with a solid foundation in subjects such as linear algebra, calculus, and statistics. You may also need to understand data-oriented programming languages, database management techniques and tools, and data visualization techniques and tools. Strong analytical and problem-solving skills are essential for roles in this field as well.Footnote 6

Start building the skills you need for your next professional challenge. Whether you need to brush up on specific concepts or want to study a brand new discipline, edX can help you on your learning journey.

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