Python is a versatile programming language. When you learn Python, the programming language makes you competent for several job roles.
It finds applications in Data Science, Web Development, Analytics, Automation, Scripting, and Game Development.
Why is it so widely used?
Let's explore the reasons to learn Python in the following sections.
What are the technical requirements of the Data Science industry?
Data Science and Analytics industry is based on mathematics and statistics. As a Data Scientist, technically, you will need some assistance to complete your job. These are listed below.
- Fundamentals: You must know and learn Python programming language. Additionally, SQL is essential for understanding querying and database management.
- Mathematics and Statistics: Creating reliable models is the main responsibility of a Data Scientist. This can only be done with sound knowledge of probability, regression analysis, hypothesis testing, and linear algebra.
- Data Analysis and Manipulation: A Data Scientist performs data manipulation and analysis regularly. The programming language used for this job must help with feature engineering and data cleaning.
- Big Data Technologies: Along with the fundamentals, you must learn frameworks. Apache Hadoop, Dask, or Apache Spark frameworks efficiently analyze and process massive databases.
- Machine Learning: A Data Scientist must know machine learning algorithms. They help in performing regression, clustering, and classification.
Why should Data Scientists learn Python over other languages?
When you learn Python for Data Science and Analytics, each lesson will speak of the language's relevance in the field.
Listed below are the reasons that make Python important for Data Scientists.
If you're wondering the reason for choosing Python over other languages, keep reading.
Simplicity: When compared with C, C++, or C#, Python is easy to learn. Data Scientists can learn the language easily and start coding in no time. The syntax of Python is simple and almost in the English language.
This enables you to focus on problem-solving instead of bothering yourself with the format of a new language. It does not just help you with the process, but it also enables teamwork. This means you can collaborate with others to complete a project on time.
Library: Python is popular for its vast library. When you talk about Data Science, the language offers one of the largest collections of frameworks and libraries. These are specific to Data Science and Analytics. For example, NumPy, Matplotlib, and Pandas are important libraries.
Support for Artificial Intelligence (AI): Tensorflow is one of the most useful libraries in Python for AI. The language also offers other frameworks and libraries. You can use these for building and training complex models. With Python, you can also integrate machine learning pipelines directly into the production systems.
Integration: In the previous section, you must've learned the importance of Big Data Technologies, SQL, and Visualization Tools. Python is compatible with SQL, Hadoop, and Tableau to enhance your capabilities as a Data Scientist. You can also integrate your Python code with other programming languages.
These reasons compel professionals to learn Python for Data Science and Analytics. However, you must note that programs like R, MATLAB, and Julia also help in Data Science. But, the simplicity of Python and its vast library has made it the top choice of professionals.
Join a job-assured Postgraduate Data Science & Analytics Course
As Python is lightweight, with extensive libraries, and customer support, the demand for this program is not getting down anytime sooner. When you become a data science expert, you must have a clear understanding of the fundamentals. Strengthen your concepts of mathematics and statistics and learn machine learning.
A Postgraduate Data Science and Analytics Course will direct your career in the right direction. Imarticus Learning presents a job-centric curriculum to make the most of your investment. You will also get assistance for participating in Hackathons that add value to your resume. Get ahead of your competitors by starting your journey today!