Course Content
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Module1: Introduction Data Science
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Module 2: Visualization & Summization (EDA)
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Module 3: Data Validation Normality Predictive Analytics: Supervised Learning Algorithms
- Part-5: Data Validation Data Normality
- Part – 6 Data Cleaning outlier treatment
- Part-7: Test of Hypothesis
- This data science certification course contains basics of the python programming such as lambdas, reading and manipulating CSV files, data manipulation and cleaning techniques using the popular python pandas data science library, abstraction of the Series and DataFrame. By the end of the data science certification course, you will be able to take tabular data and manipulate the basic inferential statistical analyses. To become pro, enroll into data science course training institute in Hyderabad.
- Part -5
- Part -6
- Part -7
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Module 4: Supervised Learning Algorithms with Applications in Predictive Analytics Advanced Analytics
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Module 5: Advanced Data Analytics (Unsupervised Learning Algorithms)
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Module 6 : Machine Learning/Artificial Intelligence Machine Learning Algorithms/AI
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Module 7
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Module 8 Python Programming for data Science
Part-5: Data Validation Data Normality
Part-10: Predictive modelling & Diagnostics
- Correlation
- SLR Regression
- MLR Regression
- Examination Residual analysis
- Auto Correlation
- Test of ANOVA Significant
- VIF Analysis
- Test of Ttest Significant
- CP Indexing
- Eigen Value for PCA Analysis
- Homoscedasticity
- Heteroskedasticity
- Stepwise regression
- Forward Regression
- Backward Regression
- Multicollinearity
- Cross validation
- MAPE
- Check prediction accuracy
- Standardized regression
- Quadraint Regression
- Transformed Regression
- Dummy Variables Regression
