Python for Data Science: FAQs
1. What to do after learning Python?
After learning Python, you can opt for the following domains to start your carrier:
- Web Development
- Mentor/Teacher
- Full Stack Developer
- QA Engineer
In case, if you want to learn further, it is suggested to go for the following domains after learning Python:
- HTML, CSS, or JavaScript to brush up your web development skills
- Start with Machine Learning, Deep Learning, NLP, etc. to start your carrier as ML Engineer
2. How Python is used in Data Science?
Backed up by large community support, Python entails more than 137,000 libraries which means you can possibly do anything alone with Python and one must focus on grasping the popular tools & frameworks that can make their work easier. Talking of Data Science, libraries such as NumPy, TensorFlow, SciPy, Pandas, Keras, PyTorch, etc are among them for different purposes and makes data science work lot more easier.
3. Is Python sufficient for Data Science?
Python alone is not sufficient for Data Science for sure. However, it can help you to start your journey but as per market demand and growing technology, it is mandatory to have a hands-on practice that includes machine learning, statistics, data visualization, data analysis, web scraping, numeric computation, etc.
Python for Data Science – Learn the Uses of Python in Data Science
In this Python for Data Science guide, we’ll explore the exciting world of Python and its wide-ranging applications in data science. We will also explore a variety of data science techniques used in data science using the Python programming language.
We all know that data Science is applied to gather multiple data sets to collect information, project the insight, and interpret it to make an effective business decision. However, being a data scientist requires you to learn some of the best and most highly used programming languages, such as Java, C++, R, Python, etc. Among these, Python has been considered the preferred choice among data scientists throughout the globe.
Prerequisites: In order to make the most of this article, it is recommended to have a basic understanding of Python programming language. .