Let?s discuss the importance eligibility of learning data science. The Data Science is very complex topic and many technologies plays major role in the development of AI/ML applications. So, the data science requires lot of complex technological knowledge along with good understanding of mathematics.
Understanding the eligibility for data science course is essential for anyone planning to make career in data science application development.
Many data scientists choose to work in data science teams when they are studying for a data science degree. Data scientists should expect to be knowledgeable enough to understand all the technical details of a complex project
While there are no specific educational qualifications to become a data scientist, there are a few skills that you might to need to become one.
Here is a list of eligibility or skills to become a Data Scientist:
Education ? In most of the cases companies are looking for the engineers having Masters Degree/PhD in mathematics, statistics, or computer science. So, if you have Masters Degree/PhD in mathematics, statistics, or computer science degree you can go for data science course to become data scientists. But if you have strong will and you are simple graduate then also you can learn and become data scientists and in this case you will have to make your profile to get job as data scientists. Learning mathematics and computer programming is key to a successful Data Scientist. To become a data scientists you should have a fair idea of mathematics, statistics, programming and data processing skills.
The best educational qualifications for Data science are:
- Engineer Degree or masters
- Mathematicians or any degree in mathematics
- Statisticians or any degree in stat
- Commerce Degree
Programming Languages- You should learn Python, R or any other language used in data science. These days mostly data scientists are using Python as a major language for developing AI/ML models. So, its wise to first learn Python programming language and then practice with the machine learning libraries.
Hadoop/Big Data- This skill is not mandatory and very essential as most of the data is stored in the Big Data environment and to get the data for machine learning you might have to interface with these systems.
Apache Spark - Apache Spark is used for large scale processing of data and data scientist might use Spark for data preparation and even for training models. So, its beneficial for a data scientists to learn Apache Spark framework, here also you can use PySpark for developing program.