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9 Import Data From Files Part 1 | Data Science | Data Science Tutorial

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9 Import Data From Files Part 1 | Data Science | Data Science Tutorial

Who should go for this course?

The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data. It is best suited for:
Developers aspiring to be a ‘Data Scientist’
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
‘R’ professionals who wish to work Big Data
Analysts wanting to understand Data Science methodologies


Why learn Data Science?
Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modelling, statistics and analytics. To take complete benefit of these opportunities, you need a structured training with an updated curriculum as per current industry requirements and best practices.
Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes.
Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges.


Topic Covered In this course 1 to 10:
1. What is Data Science
2. R Installation and Data Types
3. Vectors in Data Science with R
4. Data Science Tutorial Part 4 Matrices
5. Factors in Data Science with R
6. Data Frames Part 1 in Data Science
7. Data Frames Part 2 in Data Science
8. List in Data Science with R
9. Import Data From Files Part 1 in Data Science with R
10. Import Data From Files Part 2 and Import from Oracle in Data Science with R

Attachments for this course:

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