# Data Science for Engineers - Institution: IIT Madras - Department: Computer Science and Engineering - Taught by: Prof. Ragunathan Rengasamy, Prof. Shankar Narasimhan - Level: Undergraduate - Language: English - Subjects: Computer science, Engineering - Source: [NPTEL](https://nptel.ac.in/courses/106106179) - Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.) - Syllabus: [at the source](https://nptel.ac.in/courses/106106179) - Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words) Learning Objectives : Introduce R as a programming language Introduce the mathematical foundations required for data science Introduce the first level data science algorithms Introduce a data analytics problem solving framework Introduce a practical capstone case study Learning Outcomes: Describe a flow process for data science problems (Remembering) Classify data science problems into standard typology (Comprehension) Develop R codes for data science solutions (Application) Correlate results to the solution approach followed (Analysis) Assess the solution approach (Evaluation) Construct use cases to validate approach and identify modifications required (Creating) Intended audience: Any interested learner Prerequisites: 10 hrs of pre-course material will be provided, learners need to practise this to be ready to take the course. ## Lectures 1. [Data science for engineers Course philosophy and expectation](https://invisiblenetwork.ai/learn/nptel/106106179/126731936819) (YouTube) 2. [Introduction to R](https://invisiblenetwork.ai/learn/nptel/106106179/5fe37e999673) (YouTube) 3. [Introduction to R (Continued)](https://invisiblenetwork.ai/learn/nptel/106106179/e657196490d7) (YouTube) 4. [Variables and datatypes in R](https://invisiblenetwork.ai/learn/nptel/106106179/594d77780e2e) (YouTube) 5. [Data frames](https://invisiblenetwork.ai/learn/nptel/106106179/b677f78e15bd) (YouTube) 6. [Recasting and joining of dataframes](https://invisiblenetwork.ai/learn/nptel/106106179/70b6d2dd5b1c) (YouTube) 7. [Arithmetic,Logical and Matrix operations in R](https://invisiblenetwork.ai/learn/nptel/106106179/47829168d14a) (YouTube) 8. [Advanced programming in R : Functions](https://invisiblenetwork.ai/learn/nptel/106106179/2f5d161897e7) (YouTube) 9. [Advanced Programming in R : Functions (Continued)](https://invisiblenetwork.ai/learn/nptel/106106179/436a38bb655a) (YouTube) 10. [Control structures](https://invisiblenetwork.ai/learn/nptel/106106179/cc84ec3446a8) (YouTube) 11. [Data visualization in R Basic graphics](https://invisiblenetwork.ai/learn/nptel/106106179/15c66e5f9963) (YouTube) 12. [Linear Algebra for Data science](https://invisiblenetwork.ai/learn/nptel/106106179/ef304c0bf77e) (YouTube) 13. [Solving Linear Equations](https://invisiblenetwork.ai/learn/nptel/106106179/4df665b933e1) (YouTube) 14. [Solving Linear Equations ( Continued )](https://invisiblenetwork.ai/learn/nptel/106106179/6b1ae173ebf4) (YouTube) 15. [Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors](https://invisiblenetwork.ai/learn/nptel/106106179/f6ea38d76a43) (YouTube) 16. [Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 1)](https://invisiblenetwork.ai/learn/nptel/106106179/562a589686e0) (YouTube) 17. [Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 2 )](https://invisiblenetwork.ai/learn/nptel/106106179/44e25fd13069) (YouTube) 18. [Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 3 )](https://invisiblenetwork.ai/learn/nptel/106106179/2f0353e3bedc) (YouTube) 19. [Statistical Modelling](https://invisiblenetwork.ai/learn/nptel/106106179/a1faee3bf3eb) (YouTube) 20. [Random Variables and Probability Mass/Density Functions](https://invisiblenetwork.ai/learn/nptel/106106179/2f8acf4ce31f) (YouTube) 21. [Sample Statistics](https://invisiblenetwork.ai/learn/nptel/106106179/eb4ee2041f67) (YouTube) 22. [Hypotheses Testing](https://invisiblenetwork.ai/learn/nptel/106106179/a83a12f37375) (YouTube) 23. [Optimization for Data Science](https://invisiblenetwork.ai/learn/nptel/106106179/7d406a90ba6a) (YouTube) 24. [Unconstrained Multivariate Optimization](https://invisiblenetwork.ai/learn/nptel/106106179/34ab7c8948d3) (YouTube) 25. [Unconstrained Multivariate Optimization ( Continued )](https://invisiblenetwork.ai/learn/nptel/106106179/be8d00d6dacc) (YouTube) 26. [Gradient ( Steepest ) Descent ( OR ) Learning Rule](https://invisiblenetwork.ai/learn/nptel/106106179/8807c912039c) (YouTube) 27. [Multivariate Optimization With Equality Constraints](https://invisiblenetwork.ai/learn/nptel/106106179/3f228f603ca3) (YouTube) 28. [Multivariate Optimization With Inequality Constraints](https://invisiblenetwork.ai/learn/nptel/106106179/50259bf42b84) (YouTube) 29. [Introduction to Data Science](https://invisiblenetwork.ai/learn/nptel/106106179/b1ae512791c8) (YouTube) 30. [Solving Data Analysis Problems - A Guided Thought Process](https://invisiblenetwork.ai/learn/nptel/106106179/f08a18601183) (YouTube) 31. [Module : Predictive Modelling](https://invisiblenetwork.ai/learn/nptel/106106179/067d8d6902b5) (YouTube) 32. [Linear Regression](https://invisiblenetwork.ai/learn/nptel/106106179/bb3d021883d5) (YouTube) 33. [Model Assessment](https://invisiblenetwork.ai/learn/nptel/106106179/e47c80c24ccb) (YouTube) 34. [Diagnostics to Improve Linear Model Fit](https://invisiblenetwork.ai/learn/nptel/106106179/b688b3c679b1) (YouTube) 35. [Simple Linear Regression Model Building](https://invisiblenetwork.ai/learn/nptel/106106179/1dc2147b6285) (YouTube) 36. [Simple Linear Regression Model Assessment](https://invisiblenetwork.ai/learn/nptel/106106179/ed67d8bf73d2) (YouTube) 37. [Simple Linear Regression Model Assessment ( Continued )](https://invisiblenetwork.ai/learn/nptel/106106179/2dfd15359352) (YouTube) 38. [Muliple Linear Regression](https://invisiblenetwork.ai/learn/nptel/106106179/fd3c1b258f3d) (YouTube) 39. [Cross Validation](https://invisiblenetwork.ai/learn/nptel/106106179/9455ee24f202) (YouTube) 40. [Multiple Linear Regression Modelling Building and Selection](https://invisiblenetwork.ai/learn/nptel/106106179/a338034ad4b5) (YouTube) 41. [Classification](https://invisiblenetwork.ai/learn/nptel/106106179/6476702c1afb) (YouTube) 42. [Logisitic Regression](https://invisiblenetwork.ai/learn/nptel/106106179/712e3dde1705) (YouTube) 43. [Logisitic Regression ( Continued )](https://invisiblenetwork.ai/learn/nptel/106106179/53ec603af784) (YouTube) 44. [Performance Measures](https://invisiblenetwork.ai/learn/nptel/106106179/9d2910ad32b0) (YouTube) 45. [Logisitic Regression Implementation in R](https://invisiblenetwork.ai/learn/nptel/106106179/bb9685525aec) (YouTube) 46. [K - Nearest Neighbors (kNN)](https://invisiblenetwork.ai/learn/nptel/106106179/ada339f61c40) (YouTube) 47. [K - Nearest Neighbors implementation in R](https://invisiblenetwork.ai/learn/nptel/106106179/34fbfe9fc830) (YouTube) 48. [K - means Clustering](https://invisiblenetwork.ai/learn/nptel/106106179/aa467ab29611) (YouTube) 49. [K - means implementation in R](https://invisiblenetwork.ai/learn/nptel/106106179/a264b76ee75d) (YouTube) 50. [Data Science for engineers - Summary](https://invisiblenetwork.ai/learn/nptel/106106179/44384190de56) (YouTube)