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Big data, business intelligence, business analytics, machine learning, and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean?Why learn it? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognize the appropriate approach to solving a problem. Our course on Data Science will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science.

36,733.00 25,713.00
Course Access

2 weeks, 1 day

Last Updated

December 15, 2020

Students Enrolled

0

Total Video Time

EXPIRED

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Certification
Download Syllabus Course Description  
  • This course will help learners gain expertise in skills required to be a Data Scientist
  • Training on programming tools such as R and Python along with real time hands on projects.
  • This course would also help to create dashboards and storytelling with Tableau.
  Requirements  
  • Learners should have understanding of the services involved in the IT lifecycle.
  • Learners should have knowledge of basic statistical and mathematical functions.
  What are the system requirements for this course? Hardware Requirements:  
  • Memory – Minimum 8 GB RAM
  • Processor – Intel Core i3 CPU @2.00 GHz or above
  • Storage – 250 GB HDD/SDD or above
  • Software Requirements:
  • Operating System – Windows 7 or above, Ubuntu 14 or above
              What am I going to get from this course? Through this course you understand several data science concepts and machine learning algorithms using the most sort after programming tools R and Python.
  • You'll be given capstone projects to work on and assignments.
At the end of the course
  • you'll be efficient with the programming tools R and Python
  • know different machine learning algorithms
  • perform exploratory data analysis
  • manipulation of the data
  • and finally create reports for data visualization
           

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Course Currilcum

  • Class Details 00:00:00
    • Introduction to Data Science with R and Python Details 00:00:00
    • Introduction to Statistics Details 00:00:00
    • Data Exploration Details 00:00:00
    • Data Manipulation Details 00:00:00
    • Data Visualization Details 00:00:00

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