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數(shù)據(jù)科學(xué)與大數(shù)據(jù)分析培訓(xùn)
數(shù)據(jù)科學(xué)與大數(shù)據(jù)分析培訓(xùn)
培訓(xùn)大綱
1. Big Data Analytics
Big Data
State of the Practice in Analytics
Data Scientist
Big Data Analytics in Industry Verticals
2. Data Analytics Lifecycle
Discovery
Data Preparation
Model Planning
Model Building
Communicating Results
Operationalizing
3. Basic Data Analytic Methods Using R
Using R to Look at Data
Analyzing and Exploring the Data
Statistics for Model Building and Evaluation
4. Advanced Analytics: Theory and Methods
K Means Clustering
Association Rules
Linear Regression
Logistic Regression
Na?ve Bayesian Classifier
Decision Trees
Time Series Analysis
Text Analysis
5. Advanced Analytics: Technologies and Tools
Analytics for Unstructured Data
MapReduce and Hadoop
Hadoop Ecosystem
In-Database Analytics: SQL Essentials
Advanced SQL and MADlib for In-Database Analytics
6. Putting it All Together
Operationalizing an Analytics Project
Creating the Final Deliverables
Data Visualization Techniques
Final Lab Exercise on Big Data Analytics
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