Data Science
Prerequisites
Problem solving using computers
Basic mathematics and statistics
Knowledge of Databases
Course Objectives
Provide students with knowledge and skills for data-intensive problem solving and
scientific discovery
Be prepared with a varied range of expertise in different aspects of data science such as
data collection, visualization, processing and modeling of large data sets.
Acquire good understanding of both the theory and application of applied statistics and
computer science based existing data science models to analyze huge data sets
originating from diversified application areas.
Be better trained professionals to cater the growing demand for data scientists in
industry.
Course Outcomes
On completion of the course, student will be able to–
Perform Exploratory Data Analysis
Obtain, clean/process, and transform data.
Detect and diagnose common data issues, such as missing values, special values,
outliers, inconsistencies, and localization.
Demonstrate proficiency with statistical analysis of data.
Present results using data visualization techniques.
Prepare data for use with a variety of statistical methods and models and recognize how
the quality of the data and the means of data collection may affect conclusions.
Prerequisites
Problem solving using computers
Basic mathematics and statistics
Knowledge of Databases
Course Objectives
Provide students with knowledge and skills for data-intensive problem solving and
scientific discovery
Be prepared with a varied range of expertise in different aspects of data science such as
data collection, visualization, processing and modeling of large data sets.
Acquire good understanding of both the theory and application of applied statistics and
computer science based existing data science models to analyze huge data sets
originating from diversified application areas.
Be better trained professionals to cater the growing demand for data scientists in
industry.
Course Outcomes
On completion of the course, student will be able to–
Perform Exploratory Data Analysis
Obtain, clean/process, and transform data.
Detect and diagnose common data issues, such as missing values, special values,
outliers, inconsistencies, and localization.
Demonstrate proficiency with statistical analysis of data.
Present results using data visualization techniques.
Prepare data for use with a variety of statistical methods and models and recognize how
the quality of the data and the means of data collection may affect conclusions.
- Statistical Data Analysis Unlimited
- Data Preprocessing Unlimited
- Data Visualization Unlimited