Statistics for Data Science and Analytics

1. Understand the fundamentals of statistics 2. Different types of data 3. Different types of distribution

Beginner 0(0 Ratings) 0 Students enrolled
Created by Vignesh Sekar Last updated Tue, 23-Nov-2021 English
What will i learn?
  • Master the concepts in statistics

Curriculum for this course
0 Lessons 00:00:00 Hours
Requirements
  • 1. A computer (Windows/Mac/Linux) with internet connection thats it!
  • 2. Willingness to learn and practice
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Description
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About the instructor
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  • 0 Students
  • 3 Courses
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Hey there, I'm Vignesh S S!

  • I’m currently working as a Data Scientist in Deloitte USI. Working in real time ML project for Healthcare client.
  • Completed Microsoft Certified Azure Data Scientist Associate Microsoft Data Scientist
  • Completed Certification in Microsoft as Microsoft Certified Azure AI Fundamentals AI Fundamentals
  • Completed Certification in Microsoft as Microsoft Certified Azure Fundamentals Azure Fundamentals
  • My previous employer is TCS-digital where my primary tasks is to build various ML POC under airlines and retail domains.
  • Learning from Kaggle and Analytics Vidhya
  • Actively writing blogs on Linkedin in Cloud_AI_Analytics.
  • Sharing back to community through youtube on advanced techniques in cloud like Azure and ML and NLP related technologies through Cloud_AI_Analytics
  • Actively learning and looking for better opportunities in Machine Learning and Bigdata technologies.
  • Open for collaborations in Data Science and Machine Learning projects.

-> Scroll down to see my Pinned Repositories.

def vignesh_07():
  skills_with_proficiency = {'Python': 'Advance', 'SQL & NoSQL': 'Intermediate', 'DSA': 'Intermidiate', 'Statistics' : 'Advance'}
  tools = ['numpy', 'pandas', 'pyspark', 'sklearn', 'nltk','spacy' ,'matplotlib', 'seaborn', 'keras', 'flask', 'powerBI', 'pyspark', 'time series', 'devops', 'Bigdata technologies']
  cloud_architecture = ['Microsoft Azure Services', ' Google Cloud Platform']
  active_blogger = True
  return cool
 
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