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Want to become a Data Scientist? Best course to pursue in India

Data science courses are high in demand. A data scientist needs to interpret the data accurately because he/she is responsible to communicate the complexity of the topic to the target audience in easiest ways.

Edited by: India TV News Desk New Delhi Published : Mar 25, 2021 16:54 IST, Updated : Mar 25, 2021 16:54 IST
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Want to become a Data Scientist? Best course you can pursue in India 

Data science courses are very high in demand in the recent times. At least 88% of the Data Scientists hold Master’s degree and 46% are PhDs. While there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist.

To become a data scientist, you can opt for a Bachelor’s degree in Computer science, Social sciences, Physical sciences, and Statistics. The most common fields of study are Mathematics and Statistics (32%), followed by Computer Science (19%) and Engineering (16%). A degree in any of these courses will give you the skills you need to process and analyze big data.

According to a research by LinkedIn, the supply of workers with the correct skills isn't sufficient, thus making data science skills among the most in-demand. Thankfully, there are plenty of online learning opportunities available today to help become a highly-skilled data scientist.

Below are a few of the most popular data science options:

IntelliPaat’s Data scientist Master’s program in collaboration with IBM: This training program offered in collaboration with IBM lets learners gain proficiency in Data Science with Python, Machine Learning, AI, Deep Learning, Big Data Hadoop, Spark, Tableau Desktop, etc with 24*7 support. This program comprises 10+ courses, 53+ industry-specific projects, and 232 Hours of online instructor-led training with a CAPSTONE project. Learners will get access to the IBM course and earn a certificate from IBM.

The best part of this course is that learners have lifetime access to attend multiple batches and keep themselves abreast with technology updates. This course also provides career assistance which includes resume preparation, mock interviews.

GreatLearning Data Scientist program in collaboration with Great Lakes: Designed for freshers and young professionals exploring rewarding careers in Data Science. With Python, SQL, Tableau, Data Science and Machine Learning tools & techniques and its applications. They teach through immersive lectures delivered by our expert faculty in a classroom. Great Lakes faculty have been ranked among India’s Top Data Science academicians.

UpGrad Data Scientist Masters program in collaboration with Liverpool John Moores University: Any specialization can be chosen regardless of background. The program caters to: Engineers, Marketing & Sales Professionals, Freshers, Data Professionals, Domain Experts, Software & IT Professionals. They teach Statistics, Predictive Analytics using Python, Machine Learning, Data Visualization, Big Data Analytics, etc

Simplilearn’s Data Scientist Master’s Program in Collaboration with IBM: This course offered in joint collaboration introduces students to integrated blended learning, equipping them with expertise in both Artificial Intelligence and Data Science. This advanced course in Data Science will make students industry-ready for skills in Artificial Intelligence and Data Science and consequently render them job-ready. This Data Science certification training provides hands-on exposure to key technologies including R, Python, Machine Learning, Tableau, Hadoop, and Spark via live interaction with practitioners, practical labs, and industry projects.

 
Coursera Data Scientist Program in collaboration with Johns Hopkins University: In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

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