Learning path
/ Data Science
Data science can be defined as a blend of mathematics, business acumen, tools, algorithms, and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.
1. Programming: Python, SQL, Scala, Java, R, MATLAB.
2. Machine Learning: Natural Language Processing, Classification, Clustering.
3. Data Visualization: Tableau, SAS, D3.js, Python, Java, R libraries.
4. Big data platforms: MongoDB, Oracle, Microsoft Azure, Cloudera.
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Start Learning for FreeData Science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle.
This level in SkillPractical DataScience Path is designed by our experts to give our learners the best way to LEARN real-time DataScience using R Programming, PRACTICE competitive tests, and PREPARE for Interviews.
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