Just like the word Apple instantly brings to mind the brand rather than the fruit, the word Python today is more likely to make you think of its iconic programming logo rather than a snake.

Created in the late 1980s, Python’s popularity skyrocketed after 2010, both globally and in Nepal, thanks to its user-friendly nature and versatility across the IT industry. Among its many applications, Data Science and Machine Learning (DSML) stand out as some of the most relevant fields today and for the future, especially in a growing tech market like Nepal.

You might have heard the phrase, “Data is the new oil.” In Nepal, this is increasingly relevant: every click on your phone generates data, and companies use this data to understand and serve their customers better. Data Science is the art and science of extracting meaningful insights from such data and applying them to benefit both businesses and customers. It combines logic, domain knowledge, and computer science to solve real-world problems, making it a critical skill in today’s data-driven economy.

You may have also heard that “AI will automate most jobs.” Whether this comes true or not, AI is undeniably shaping the future of work. Within AI, one branch is seeing explosive growth both in Nepal and abroad, with jobs in this domain expected to increase almost tenfold in the next five years. This domain is Machine Learning (ML)—a branch of AI that allows computers to learn from data and make predictions without being explicitly programmed, enabling businesses and industries to make smarter decisions faster.

While exact numbers are hard to come by, industry observations suggest that a significant majority of IT professionals in Nepal—roughly 80,000 people—work with Python in some capacity. Practically speaking, if you aim for a career in DSML, having Python on your CV is more strategy than hope. Python has become the preferred language because of its versatility, simplicity, and efficiency. It is a general-purpose language, capable of handling everything from data analysis and machine learning to web development, automation, and deployment. Its closest competitors, such as R and C++, lack this breadth in Nepal’s context. While R is suited for deep statistical research, research-focused roles are limited locally, and C++, although powerful, is better suited for performance-critical systems rather than everyday DSML workflows.

Python dominates Data Science and Machine Learning not just because it is easy to learn but also because of its clean syntax, which allows learners and professionals to focus on solving problems rather than wrestling with complicated programming logic. Its rich ecosystem of libraries—such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and PyTorch—makes data analysis, visualization, and model building faster, more reliable, and scalable. Backed by a strong community and widespread industry adoption, Python enables rapid experimentation and real-world deployment, making it the most practical and preferred language for DSML in Nepal and beyond.