Machine Learning Using Python

Who should attend

The programme is open to the faculty of engineering colleges, degree colleges, MCA colleges and other allied disciplines in India.

Industry personnel working in the concerned/allied discipline can also attend.

Course Content

• Python programming: Introduction
    • Mutable and Immutable
    • Introduction to basic (native) data structure
    • Difference between list and array
• Analytics around / using Python
    • Numpy / Pandas / Scipy / Matplotlib
    • Vector and array manipulation
    • Plotting, functions, input and output
    • Hands on session using Python
• Machine Learning: Introduction
    • Supervised Vs Unsupervised Learning
    • Linear Regression, • Decision Trees, KNN
    • Multilayer Neural Network, Back propagation
    • Bayesian Networks, SVM
    • Clustering :K Means
    • Python API's for implementing Machine Learning
Algorithms
    • Case Studies using Python

Registration Fee

Faculty and Research Scholars	Rs. 2500/-
Faculty of SC/ST Category	Rs. 1875/- (SC/ ST participants should submit their caste certificate to claim the concession along with application form)
Industry Participants	Rs. 7500/-

SC/ST concession is only for Faculty of mentioned states. Research Scholars are not eligible for SC/ST concession.
The Participants need to send a crossed demand draft (DD) drawn in favour of "Director, NIT Warangal" and payable at SBH, NIT Warangal branch
or
On-line Mode:
Account Name: Electronics & ICT Academy NITW
Account No: 62423775910
IFSC Code: SBIN0020149

How to Apply

A filled-in form of application in the prescribed format duly signed and sponsored by appropriate authorities (along with demand draft) should reach the coordinator on or before the last date by post/courier. Participants are requested to write their name and contact number backside of demand draft. It is also mandatory to send scanned application form and demand draft through e-mail to hodit@staff.vce.ac.in as selection will be intimated only through e-mail.

Accommodation

All the selected participants will have to make their own arrangements for their accommodation. No TA will be paid for the participants. Working Lunch, Tea & Snacks would be provided during the Training in the campus.