Data Science Master Programme Training

DATA SCIENCE MASTER PROGRAM
6 Modules : 150 Hours : 3 Months : 3 Capstone Projects
• Statistics – Mathematics
• Machine Learning
• R & Python Programming
• Artificial Intelligence using Tensor Flow
• Machine Learning using AWS, Azure
• BigData Analytics

Statistics (Mathematics for Data Science) Module – 1 (25 hrs)
Understanding the Data
• Data, Data Types
• Meaning of variables
• Central Tendency
• Measures of Dispersion
• Measures of Variability
• Measures of Shape
• Data Distribution
• Correlation, Covariance
• Practical Examples

Probability Distributions
• Mean, Expected value
• Binomial Random Variable
• Normal Distribution
• Poisson Random Variable
• Continuous Random Variable
• Discrete Random Variable
• Practical Examples

Sampling Distributions
• Central Limit Theorem
• Sampling Distributions for Sample Proportion, p-hat
• Sampling Distributions for Sample Mean, x-bar
• Z- Scores
• Practical Examples

Hypothesis Testing
• Type I and Type II Errors
• Decision Making
• Power
• Testing for mean, variance, proportion
• Practical Examples
Association between Categorical Variables
• Contingency Tables
• Independent and Dependent
• Pearson's Chi-Square Test
• Misuses of Chi-Squared Test
• Measures of Association
• Practical Examples

ANOVA Analysis
• Analysis of Variance & Co-Variance
• ANOVA Assumptions & Comparisons
• F-Tests
• Practical Examples

Matrices
• One – Dimensional
• Multi Dimensional
• Arithmetic Operations
• Examples

Vectors

Machine Learning Module – 2 (40 hrs)

Supervised Learning

Linear Methods for Regression

http://www.futurepointtech.com/Data-Science-Masters-Programme-Training.html

Drop a mail [email protected] we will get in touch with u