Today, Data Science has become one of the hottest professions in the IT world. The demand for qualified and talented data scientists who can help in data-driven decisions has reached exponential heights. The data scientist must have the fundamental knowledge and skillset in open source tools, libraries, SQL, Python, Statistical Analysis, and relational databases. Handling the real-world data sets means learning these data science prerequisites. Apart from theoretical knowledge, you will also require practical knowledge and some experience to dig deeper into data science and start working on advanced projects.
Learning Python is regarded as one of the fundamental skills required for a career in data science and as a Python developer. However, Python was not always the most preferred programming language for data science. In fact, R was used in the majority of the data science projects. However, in 2018, Python became the most widely used language for data science and data analytics. This trend of using Python in data science has also given rise to constant development in the Python ecosystem. The journey to becoming a data science professional begins by learning the Python programming language. However, learning Python has become really easy with Python certificate courses from educational institutions that provide practical training.
Python certification courses can help you prepare for a data science career. It will challenge and encourage you to write useful code and utilise real-world data to work in data science projects. Apart from learning Python, you will also need to develop a couple of soft skills to become a python developer and data science professional.
Learning the Python basics is super important to get a clear introduction to the world of data science. Joining a Python community is a great idea to learn about the plethora of Python libraries.
Hands-on learning brings the best learning experience to Python students. You can start building simple apps and games to familiarise yourself with the fundamental concepts of Python and solidify your understanding of the basics. Continuously practising with mini Python projects will polish your skills and won’t take much time from your schedule. Plus, you will be prepared to handle complex data science projects in the near future.
Exploring Data Science with Python and SQL
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