Machine Learning using R

A program on "Machine Learning using R" will commence at Bhaskaracharya Pratishtana from 29th April 2018.
  • Eligibility: Any Student / Industry Personal having basic exposure to Linear Algebra and C++ Programming can chose to opt for the course. No prior knowledge of Statistics is required but having done statistics will be an advantage
  • Course Days: The inaugural session will be held on 29th April 2018 from 2 pm to 6 pm. The regular Sessions will be only conducted on Sundays. The Final Session will be on 1st July 2018.
  • Course Timings: The timings will be in 2 sessions (4 Hours Each)
    • Morning Session: 9 am to 1 pm
    • Lunch Break : 1 pm to 2 pm
    • Afternoon Session: 2 pm to 6 pm
  • Course Mentors:
    • Mr. Hrishikesh Khaladkar (Fergusson lCollege Pune) will be conducting the major part of the course.
    • We have Industry collaborations to conduct certain specific sessions within the course.
    • A presentation regarding a case study of the candidate's choice will be conducted as a part of the Evaluation process.
  • Course Logistics: Students will be working with their own Laptops to do assignments. Complete assistance will be provided regarding the installation and other Queries if any. The course material will be circulated in the form of PDF.
  • Course Fees : Rs 10,000/-
  • All interested in participating may please write to Mr Hrishikesh Khaladkar at hrishi.paradox@gmail.com . Mob No : 8149432374

Course Schedule

Session.
No.
Dates Topics to be discusse No.of
hours
1 29/4/2018 BasicData Structures in R,Control Structues, Functions,OOPS 4
2 6/5/2018 Data Imports and Exports,dplyr package 4
3 6/5/2018 Data Manipulations using tidyr and reshape2 4
4 13/5/2018 Basic Graphics Visualizations using R and ggplot2 4
5 13/5/2018 Basic Statistics, Correlation,Probability Distributions 4
6 20/5/2018 Concepts of Sampling, Parametric Tests (t,χ2 and F) 4
7 20/5/2018 Association between variables and Analysis of Variances 4
8 27/5/2018 Linear Regression and its related Case Study 4
9 27/5/2018 K-Nearest Neighbors and its related Case Study 4
10 3/6/2018 Logistic Regression and its related Case Study 4
11 3/6/2018 Time Series and its related Case Study 4
12 10/6/2018 Using Naive Bayes Classifier and its related Case Study 4
13 10/6/2018 Clustering using K Means and its related Case Study 4
14 17/6/2018 Principal Component Analysis its related Case Study 4
15 17/6/2018 Artificial Nueral Networks and its related Case Study 4
16 24/6/2018 Market Basket Analysis and its related Case Study 4
17 24/6/2018 Text Mining and its related Case Study 4
18 1/7/2018 Reserved Session 4
19 1/7/2018 Reserved Session 4

Remarks

  1. The Topic of Performance Metrics will be discussed during the Case Studies as it is a better understood there.
  2. Each Session will be rigourous of 4 hours with Topic Discussion (Mathematical/Statistical Aspects) 2 Hours + Hands on Programming 2 Hours .
  3. Please get you Own Laptops. I will guide with instructions regarding the step and will solve any of your related Queries if any.
  4. Will try to cover some advanced topics if time permits. It depends on how fast you all cope with the topics.