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Python for Data Science

By Prof. Raghunathan Rengasamy   |   IIT Madras
Learners enrolled: 56840
The course aims at equipping participants to be able to use python programming for solving data science problems. INTENDED AUDIENCE: Final Year Undergraduates PRE-REQUISITES: Knowledge of basic data science algorithms INDUSTRY SUPPORT: Honeywell, ABB, Ford, Gyan data pvt. Ltd.
Summary
Course Status : Completed
Course Type : Elective
Duration : 4 weeks
Start Date : 26 Aug 2019
End Date : 20 Sep 2019
Exam Date : 16 Nov 2019 IST
Category :
  • Computer Science and Engineering
Credit Points : 1
Level : Undergraduate

Page Visits



Course layout

Week 1: BASICS OF PYTHON SPYDER (TOOL)
Introduction Spyder
Setting working Directory
Creating and saving a script file
File execution, clearing console, removing variables from environment, clearing environment
Commenting script files
Variable creation
Arithmetic and logical operators
Data types and associated operations
Week 2: 
Data Structures
  1. Lists
  2. Tuples
  3. Dictionary
  4. Sets
Numpy
  1. Array
  2. Matrix and associated operations
  3. Linear algebra and related operations
Week 3: 
Pandas dataframe and dataframe related operations on Toyota Corolla dataset
  1. Reading files
  2. Exploratory data analysis
  3. Data preparation and preprocessing
Data visualization on Toyoto Corolla dataset using matplotlib and seaborn libraries
  1. Scatter plot
  2. Line plot
  3. Bar plot
  4. Histogram
  5. Box plot
  6. Pair plot
Control structures using Toyota Corolla dataset
  1. if-else family
  2. for loop
  3. for loop with if break
  4. while loop
Functions
Week 4: CASE STUDY
Regression
  1. Predicting price of pre-owned cars
Classification
  1. Classifying personal income

Books and references

1. Introduction to linear algebra - by Gilbert Strang 2. Applied statistics and probability for engineers – by Douglas Montgomery 3. Mastering python for data science, Samir Madhavan

Instructor bio


Prof. Rengaswamy was a Professor of chemical engineering and co-director of the process control and optimization consortium at Texas Tech university, Lubbock, USA. He was also a Professor and Associate Professor at Clarkson university, USA and an Assistant Professor at IIT Bombay. His major research interests are in the areas of fault detection and diagnosis and development of data science algorithms for manufacturing industries.

Course certificate

  • The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centers.
  • The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
  • Date and Time of Exams: 16th November 2019 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
  • Registration url: Announcements will be made when the registration form is open for registrations.
  • The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
  • Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE
  • Average assignment score = 25% of average of best 3 assignments out of the total 4 assignments given in the course. 
  • Exam score = 75% of the proctored certification exam score out of 100
  • Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75
  • If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.
  • Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras. It will be e-verifiable at nptel.ac.in/noc.
  • Only the e-certificate will be made available. Hard copies are being discontinued from July 2019 semester and will not be dispatched.


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