• Data Science concepts and fundamentals; Methodologies and Frameworks
• R-Language Programming and R package-based Data Analysis
• SQL and NoSQL-based Data Science
• Regression Modelling and other Inferential Schemes
• Clustering and Segmentation Schemes
• Machine Learning Techniques
• Data Acquisition and Cleansing Techniques
• Multivariate Exploratory Data Analysis
• Python-Language-based Data Analysis
• Data Visualization and Visual Analytics
• Advanced Data Modelling Techniques
Duration: The course features both offline and online, instructor-led, weekly synchronous online sessions (2 hours per session), over an 8-week period.
Successful completion gives 3 credit hours towards the Associate-to-Professional Member (A2PM) bridging program.