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LIL - Data Science & Analytics Career Paths & Certifications:…
LIL - Data Science & Analytics Career Paths & Certifications: First Steps
Definition
History
Role of Computer Science
Empowering statistics
Inventions
1960 - DBMS
1970 - relational db
1980
'data mining'
1990
Data Science
2000
predictive modelling in compagnies
Fundamentals
Big Data
Machine learning frees humans
Data mining
aspect of discovering pattern in data set
Big data
Distributed computing
'devide and conquer'
Technologies
Data Infrastructure technologies
Data Management Technologies
Visualization Technologies
Marketplace
Fraud detection
Machine learning
Train themselves and reduces false positives
Social media analytics
Unstructured but rich data sets
Text mining & parsing
via API
Desease control
Dating services
Simulations
Climate research
Network security
Skills
Data Mining
Examining large amount of data to find patterns and relationships
Machine Learning
Field of AI, focus on optimizing algorithms for data anal tasks
Types
Supervised (classifications) or not (clustering)
NLP
Statistics
Minimum
Proba
Correlation
Var, distrib, regression
NHST
Confidence intervals, t-test, ANOVA, X-square
Software tools
R
Excel
SAS
Additionnal topics
Logreg
Support vector machines (SVMs)
Bayesian methods
Vizualisation
IT skills
Programming languages
R
Python
C++
Java
Text Mining
AWK, grep, find and sort
Distributed computing
Cloud computing
Hadoop
Roles
Data scientist
Data engineer
Business intelligence architect
Machine learning specialist
Data analytics specialist
Data visualization developer
Certifications
MCSE Business Intelligence
Cloudera Certified Professional
EMC Data Science Associate
Oracle BI Implementation Specialist
SAS Certified Data Scientist certifications
CAP - Certified Analytics Professional
NOT TIED TO A VENDOR.
Future of DS