Data Scientist Course

Satya Training Institute

Course Summary

IT, Software & Hardware
Class room
Beginner/Entry level

Course Overview

Satya Technologies is established in 1996 and started its services in the field of education. A journey that began as an Educational Academy has transformed over a period of time into software training provider and the training institute has been started in Ameerpet.

Satya Technologies has been doing a great job in keeping abreast with the latest versions, updates in various technologies and current market strategies, strengths, requirements and trends. With this determined attitude of providing best services Satya Technologies ventured into all the latest technologies

Course Description

Data Scientist: In this course you will get an introduction to the main tools and ideas which are required for Data Scientist/Business      Analyst/Data Analyst. The course gives an overview of the data, questions, and tools that data analysts and data scientists work         with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable   knowledge. The second is a practical introduction to the tools that will be used in the program like R Programming, SAS, MINITAB       and EXCEL. Course

Topics Covered

     Descriptive & Inferential Statistics

    •  Turning Data into Information
    •  Data Visualization
    •  Measures of Central Tendency
    •  Measures of Variability
    • Measures of Shape
    •  Covariance, Correlation
    • Using Software-Real Time Problems

    Probability Distributions

    • Probability Distributions: Discrete Random Variables
    • Mean, Expected Value
    •  Binomial Random Variable
    • Poisson Random Variable
    • Continuous Random Variable
    •  Normal distribution
    • Using Software-Real Time Problems

     Sampling Distributions

    •  Central Limit Theorem
    • Sampling Distributions for Sample Proportion, p-hat
    • Sampling Distribution of the Sample Mean, x-bar
    • Using Software-Real Time Problems

    Confidence Intervals

    • Statistical Inference
    • Constructing confidence intervals to estimate a population Mean, Variance, Proportion
    • Using Software-Real Time Problems

     Prediction Analytics

     Applied Multivariate Analysis

    Machine Learning

    R Programming

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