Data Science

Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.Spectrum has the highest number of candidates got trained in Data Science in the last year. We train you to analyse data in to number of ways  using Python,Machine Learning and MySql database.Data Science training course for freshers to make them good programmers through quality training in Python & machine Learning in Coimbatore.

Crash Course

Duration 1 Month

Introduction to Data Types

  • Numerical parameters to represent data
    Mean
    Mode
    Median
    Sensitivity
    Information Gain
    Entropy
    Statistical parameters to represent data
 
 
 
 
 
 
 
 
 
 
 
 

Internship Program

Duration 3 Month

    • Introduction to Data Types,Numerical ,parameters to represent data,Mean,Mode,Median,Sensitivity,Information Gain,Entropy,Statistical,parameters to represent data
    • Uses of probability,Need of probability,Bayesian Inference,Density Concepts,Normal Distribution Curve
    • Point Estimation,Confidence Margin,Hypothesis Testing,Levels of Hypothesis Testing 
    • Parametric Test,Parametric Test Types,Non- Parametric Test,Experimental Designing,A/B testing
 
 
 
 
 
 
 
 

Inplant training

Duration 6 Month

    • Introduction to Data Types,Numerical ,parameters to represent data,Mean,Mode,Median,Sensitivity,Information Gain,Entropy,Statistical,parameters to represent data
    • Uses of probability,Need of probability,Bayesian Inference,Density Concepts,Normal Distribution Curve
    • Point Estimation,Confidence Margin,Hypothesis Testing,Levels of Hypothesis Testing 
    • Parametric Test,Parametric Test Types,Non- Parametric Test,Experimental Designing,A/B testing
    • Association and Dependence,Causation and Correlation,Covariance,Simpson’s Paradox,Clustering Techniques
    • Logistic and Regression Techniques,Problem of Collinearity,WOE and IV,Residual Analysis,Heteroscedasticity,Homoscedasticity