Data Science for Engineers

Duration:8 Weeks

@VTU COE

5.0
(1) 410 Students
Download Brochure

What you will learn

  • Computer Science and Engineering

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)

play
Linear Algebra for Data science
Preview 28:42
play
Solving Linear Equations
Preview 24:33
play
Solving Linear Equations ( Continued )
Preview 24:32
play
Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors
Preview 33:16
play
Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 1)
Preview 28:32
play
Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 2 )
Preview 33:41
play
Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 3 )
Preview 24:16

play
Statistical Modelling
Preview 25:03
play
Random Variables and Probability Mass/Density Functions
Preview 28:21
play
Sample Statistics
Preview 33:53
play
Hypotheses Testing
Preview 37:20

play
Optimization for Data Science
Preview 39:42
play
Unconstrained Multivariate Optimization
Preview 29:56
play
Unconstrained Multivariate Optimization ( Continued )
Preview 18:34
play
Gradient ( Steepest ) Descent ( OR ) Learning Rule
Preview 23:59

play
Multivariate Optimization With Equality Constraints
Preview 30:49
play
Multivariate Optimization With Inequality Constraints
Preview 44:53
play
Introduction to Data Science
Preview 41:56
play
Solving Data Analysis Problems - A Guided Thought Process
Preview 34:40

play
Module : Predictive Modelling
Preview 23:44
play
Linear Regression
Preview 41:02
play
Model Assessment
Preview 35:41
play
Diagnostics to Improve Linear Model Fit
Preview 29:09
play
Simple Linear Regression Model Building
Preview 11:51
play
Simple Linear Regression Model Assessment
Preview 08:44
play
Simple Linear Regression Model Assessment ( Continued )
Preview 13:33
play
Muliple Linear Regression
Preview 39:03

play
Cross Validation
Preview 23:07
play
Multiple Linear Regression Modelling Building and Selection
Preview 14:46
play
Classification
Preview 19:19
play
Logisitic Regression
Preview 29:21
play
Logisitic Regression ( Continued )
Preview 18:36
play
Performance Measures
Preview 32:49
play
Logisitic Regression Implementation in R
Preview 20:52

play
K - Nearest Neighbors (kNN)
Preview 26:24
play
K - Nearest Neighbors implementation in R
Preview 29:11
play
K - means Clustering
Preview 31:19
play
K - means implementation in R
Preview 21:13
play
Data Science for engineers - Summary
Preview 06:20
img
No Discussion Found

5.0

1 Reviews

5
1
4
0
3
0
2
0
1
0
user
sanjana yg

9 months ago

Very nice

Meet Your Instructor
@VTU COE
img

Instructor
3.2 Rating
2542 Students
759 Courses
About Instructor

VTU is one of the largest Technological Universities in India with 24 years of Tradition of excellence in Engineering & Technical Education, Research and Innovations. It came into existence in the year 1998 to cater the needs of Indian industries for trained technical manpower with practical experience and sound theoretical knowledge.

video

Free

  • Course Duration
    20 h 28 m 43 s
  • Course Level
    Intermediate
  • Student Enrolled
    410
  • Language
    English
This Course Includes
  • 20 h 28 m 43 s Video Lectures
  • 2 Quizzes
  • 0 Assignments
  • 0 Downloadable Resources
  • Full Lifetime Access
  • Certificate of Completion