How to become a Data Scientist after engineering in 2022?
Here’s a complete guide to going from engineer to data scientist
Every industry is driven by data in today’s ever-changing technological world. Data science is the field of study that involves extracting knowledge from all the data collected. Today, Data Science offers one of the most lucrative career opportunities in any industry. As the demand for Data Scientists increases, Data scientists analyze and interpret complex digital data, such as website usage statistics, in particular to assist a company in its decision-making.
A Data Scientist will need to have a bachelor’s degree. Higher or advanced degrees may not be strictly required to land a career as a data scientist. Although each student’s experience is different, we can say with certainty that by keeping the academic background in engineering as a foundation, learners, as well as professionals who turn to the field of data science, receive many career growth opportunities. The field of data science is expected to see an increase in job opportunities, as well as artificial intelligence.
How to become a Data Scientist?
Data scientists are professionals tasked with dealing with big data and helping their employers find the right answers to their questions, whether it’s creating a marketing plan or targeting the right demographics for a product. Data science is a diverse field that requires programming knowledge as well as an understanding of mathematics.
Essential skills to become a Data Scientist
- Suitability in a programming language: Programming tools such as R, Python, and SAS are very important when analyzing data. Therefore, programming ability is important in at least one programming language. Python is an open-source, general-purpose programming language. Python libraries like NumPy and SciPy are used in Data Science.
- Know the tools of Big Data: such as Apache Spark, Hadoop, Talend and Tableau, which are used to process large and complex data that cannot be processed using traditional data processing software.
- Clear view: Data scientists must design efficient and fast algorithms. Therefore, creativity is very important to achieve this. Data science is not just about why it should be done, but how it should be done.
- Learn statistics and mathematical analysis: As data science requires producing raw data and numbers, mathematical ability is a must. Mathematical analysis is the branch of mathematics dealing with limits and related theories, such as differentiation, integration, measurement, infinite series, and analytic functions. Statistics is the science concerned with the development and study of methods for collecting, analyzing, interpreting and presenting empirical data.
- Resolution: Working with a constant influx of data can sometimes be frustrating. Therefore, having a strong determination will help anyone overcome the hardships offered by the data scientist career and reap a lot of benefits from it.
Some of the Best Data Science Courses in India
Purdue University and Simplilearn:
Simplilearn’s Data Science PGP is the best data science course in India, based on the selection and ranking criteria above. This data science course also has a great mix of a comprehensive curriculum, offers a highly interactive learning experience through live lectures by leading professors and experts, and hands-on industry projects. This is a 12 month period of online courses. The program is designed in collaboration with Purdue and IBM. Upon successful completion of the program, the learner obtains a Purdue PG certificate as well as an IBM certificate.
Advanced Data Science Program by IIM Calcutta:
The advanced program in data science is led by IIM Calcutta for the job. This program is primarily online, with a mix of a few live sessions and a four-day on-campus session. The duration of the course is 12 months. The IIM Calcutta certificate would be awarded to learners who successfully complete the program.
In Data Analytics by Imarticus:
The PGP in Data Analytics by Imarticus is a 12-month offline and online program. This data science is a good option for someone starting their data science career with 3 years of experience. It’s also a rigorous program with five offline classes of 4 hours each per week. Learners must therefore be prepared for the time commitment.
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