Best Coaching Institutes in Ameerpet : Data science is a multidisciplinary blend of data inference, algorithmm development, and technology in order to solve analytically complex problems. At the core is data. Troves of raw information, streaming in and stored in enterprise data warehouses. Much to learn by mining it.![]() |
- Introduction to Data science
What is data science?
How is Data Science different from BI and Data Analyst
Who are Data Scientist?
What skill sets are required to become a Data Scientist ?
What is machine learning?
Statistics and Mathematics for Data Science
- Mathematical and Business Statistics Concepts for Data Science
Mean, Mode Median
Standard deviation, Variance, Correlation Analysis, Skewness, Quartile
Linear Algebra, Probability, Optimization Theory
Time series data representation
Some Common Terms Used in Statistics
Data Distribution: Central Tendency, Percentiles, Dispersion
Histogram
Bell Curve
Hypothesis Testing
Chi-Square Test
Correlation Matrix
Inferential Statistics
Data type
ICategorical Data (Nominal, Ordinal)
Numerical Data (Discrete, Continuous, Interval, Ratio)
Why Data Types are important?
Statistical Methods
Descriptive Statistics
Measures of Frequency: * Count, Percent, Frequency .
Measures of Central Tendency. * Mean, Median, and Mode
Measures of Dispersion or Variation. * Range, Variance, Standard Deviation
Measures of Position. * Percentile Ranks, Quartile Ranks.
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