Course curriculum
-
1
Course Overview
- VID-20200716-WA0053
-
2
Module-1 : (Probability Theory)
- Concept of Random Experiment
- Events
- Special types of events
- Event/Sample Space
- Complementary Event
- Sum of two or more events
- Product of two or more events
- Classical definition of Probability
- Some important rules
- Examples on classical definition of probability
- Axioms of Mathematical Probability
- Examples in probability
- General addition rule of Probability
- Examples on addition rule of probability
- Examples on addition rule of probability(Contd.)
- Conditional Probability
- Examples on Conditional probability
- Examples on Conditional probability(Contd.)
- Bayes Theorem
- Application of Bayes Theorem
- Independent Events
- Example on independent events
- Basic_course_on_Data_science_using_statistics_Probability_Theory_QUIZ_1
- Basic_course_on_Data_science_using_statistics_Probability_Theory_QUIZ_1,Answer Booklet
-
3
Module-2(Basic Statistics)
- Introduction
- Basic Data Types
- Representation of Data: Ungrouped Frequency Distribution Table
- Representation of Data: Grouped Frequency Distribution Table
- Representation of Data: Grouped Frequency Distribution Table continued
- Representation of Data: Histogram, Frequency polygon
- Representation of Data: Ogive
- Introduction to measures of central tendency
- Method to calculate mean
- Properties of mean
- Method to calculate median
- Properties of median
- Method to calulate mode
- Properties of mode
- Relationship among mean,median and mode
- Partition values in a data set
- Introduction to measures of dispersion
- Graphical and algebraic measures of dispersion
- Range
- Quartile deviation
- Mean deviation
- standard deviation
- Co efficient of range,quartile deviation and mean deviation
- Coefficient of variation
- QUIZ_Measures of central tendency and dispersion-converted
- Measures of central tendency and dispersion,quiz
- Moments
- Skewness & Kurtosis
- Correlation: Intro
- Correlation: Understanding from Examples
- Correlation coefficient
- Correlation: Worked out example
- Rank correlation
- Regression
- Quiz_4_Regression
- Quiz_4_Regression Answer Booklet
-
4
Module -3 (Introduction to Datascience)
- Types of Data and Dataset
- Tasks in Data Science
- Data Exploration
- Data cleaning
- Dimensionality Reduction
- Basic Course on Data Science using Statistics_XX_QUIZ_1
- Basic Course on Data Science using Statistics_XX_QUIZ_1 Answer Booklet
-
5
Module -4 (Introduction to Data Mining)
- Tasks in Data Mining
- Machine Learning for Data Modelling
- Implementing Data Mining Tasks using Machine Leaning
- Nearest Neighbour classifier
- Naive Baye's classifier
- Basic Course on Data Science using Statistics_XX_QUIZ_2
- Basic Course on Data Science using Statistics_XX_QUIZ_ Answer Booklet
Image & text (with CTA)
The course focuses on the application of statistics on various tasks associated
with Data Science. Moreover, the course also introduces Machine Leaning as a
tool for building models for data mining tasks.
Course outcome
Instructor(s)
Senior Assistant Professor
Biswadip Basu Mallik
Associate professor
Krishanu Deyasi, PhD
Assistant Professor
Moumita Basu