Course Name: Data Science for Engineers

Course abstract

Learning Objectives : 1. Introduce R as a programming language 2. Introduce the mathematical foundations required for data science 3. Introduce the first level data science algorithms 4. Introduce a data analytics problem solving framework 5. Introduce a practical capstone case study Learning Outcomes: 1. Describe a flow process for data science problems (Remembering) 2. Classify data science problems into standard typology (Comprehension) 3. Develop R codes for data science solutions (Application) 4. Correlate results to the solution approach followed (Analysis) 5. Assess the solution approach (Evaluation) 6. Construct use cases to validate approach and identify modifications required (Creating)


Course Instructor

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Prof. Shankar Narasimhan

Prof.Shankar Narasimhan is currently a professor in the department of Chemical Engineering at IIT Madras. His major research interests are in the areas of data mining, process design and optimization, fault detection and diagnosis and fault tolerant control. He has co-authored several important papers and a book titled Data Reconciliation and Gross Error Detection: An Intelligent Use of Process Data which has received critical appreciation in India and abroad.


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Prof. Ragunathan Rengasamy

Prof. Ragunathan Rengasamy is a Professor at the Department of Chemical Engineering and a core member of the recently established Robert Bosch Center for Data Science and AI (RBC-DSAI) at IIT Madras. He is also a co-Founder and Director of Gyan Data Pvt. Ltd. (GDPL, identified as one of the top 10 start-ups to watch out for in 2018 by Analytics India Magazine), a high tech start-up in the area of data analytics located at IIT Madras Research Park. Recently, he co-founded GITAA Pvt. Ltd., a data science education company, incubated by the IITM Incubation Cell. Prior to this, he was Professor, Chemical Engineering and co-director of the Process Control and Optimization Consortium (PCOC) at Texas Tech University, Lubbock, TX USA, Associate and full Professor at Clarkson University, Potsdam, NY and Assistant Professor at IIT Bombay, Mumbai, India.
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 Course Duration : Jan-Mar 2022

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 Enrollment : 14-Nov-2021 to 31-Jan-2022

 Exam registration : 13-Dec-2021 to 18-Feb-2022

 Exam Date : 27-Mar-2022

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Enrollment Statistics

Total Enrollment: 17044

Assignment Statistics




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Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.