This is a complete Data Science bootcamp specialization training course from SV Tech Soft . We provides you detailed learning in data science, data analytics, project life cycle, data acquisition, analysis, statistical methods and machine learning.
Doubt clarifying sessions: Every Sunday doubt clarifying sessions/ Real time case study based problems are solved under the guidance of data scientist from the Industry. 
Project#1: Performance of Thermal Conductivity Coating
Description: Identification of best coating
material for efficient performance
Data Size: Rows-24, Coating types-4
Statistical techniques used: ANOVA
Tools used: Excel, R


Project#2: Boston Housing data
Description: Prediction of real estate price
of a house
Data Size: Rows-506, no of variables-13
Statistical techniques used: Multiple
Linear Regression, Variable selection
methods, Transformation techniques
(Box-cox, Box Tidwell), Multicollinearity,
Influential and leverage points
Tools used: Excel, R


Project#3: Crime Data
Description: Grouping different crime
zones using the data collected
Data Size: Rows- 50, No of variables-8
Statistical techniques used: Cluster
Analysis, Principle Component Analysis
Tools used: SQL, R


Project#4: Diagnostic Breast Cancer data
Description: Prediction of patient into
malignant or benign based on data
collected
Data Size: Rows-570, no of variables-30
Statistical techniques used: K- Nearest
Neighbor classifier
Tools used: SQL, R


Project#5: Spam mail's detection
Description: Classification of a mail into
spam and ham mail using data collected
Data Size: No of document messages-
5574
Statistical techniques used: Naïve Bayes
theoryTools used: Excel, R

​​Project#6:
Title: Yahoo finance Stock market data
Description: Prediction of S&P stock index
based on last 5 days’ performance
Data Size: Rows-1250, no of variables-5
Statistical techniques used: Logistic
regression
Tools used: SQL, R


Project#7: Home loan application data
Description: Prediction of loan application
into Safe and Risky loan
Data Size: Rows- 90153, No of variables-
20
Statistical techniques used: Decision
Trees, PruningTools used: SQL, R


Project#8: Super market data
Description: Identify the association rules
of different products in super market to
improve the sales
Data Size: No of transaction-9835
Statistical techniques used: Market
Basket AnalysisTools used: SQL, R


Project#9: Cement Data
Description: Prediction of cement
Strength based on different material
composition mixing
Data Size: Rows- 1030, No of variables-8
Statistical techniques used: Neural
Network with two hidden layers
Tools used: SQL, R


Project#10: Optical Character Recognition
Description: Classification of 26 alphabets
based on data collected
Data Size: Rows-20000, no of variables-16
Statistical techniques used: Support Vector
MachineTools used: Excel, R