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Diganta
- Rate $7
- Response 1h
-
Students8
Number of students Diganta has taught since their arrival at Superprof
Number of students Diganta has taught since their arrival at Superprof
$7/h
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- Data analysis
Learn Data analytics and Introduction to Data Science using R programming from ( Data Scientist at Accenture Strategy, Ex-Mu Sigma, IIT Kharagpur, CAT 2018 - 98.36 percentile, GATE AIR-184).
- Data analysis
Lesson location
About Diganta
Hello students,
My name is Diganto and I am a post-grad data scientist! ( Data Scientist at Accenture Strategy, Ex-Mu Sigma, IIT Kharagpur, CAT 2018 - 98.36 percentile, GATE AIR-184).
I am a Kaggle expert Tier data scientist with a rank of 1134 and I am within the top 0.7 percentile of data scientists in Kaggle. I have close to 3 years of experience in Data Science and Analytics and I have developed various commodity price prediction models and have extensively worked with time series algorithms, Linear, Logistic Regression Modelling, Classification, and Regression Trees (CART) as well as with unsupervised learning algorithms such as Clustering Algorithms and purchase propensity models using Python, R, and R Shiny.
I have trained more than 300 students in data science using R and Python.
I look forward to interacting with you all during the course.
Happy learning!
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About the lesson
- All Levels
- English
All languages in which the lesson is available :
English
It is a 4-week course. However, guidance and contact are perpetual. There are 2 modes of training.
Mode 1 is where I'll share the materials with you which have theory notes plus recorded lectures plus hands-on videos on R. Mode 2 will be 1:1 live sessions via google meets every weekend. The live session will have theory explained and practical demonstration on R.
This course includes a step-by-step approach to Data Science and Machine Learning. With each lecture, you will develop the mathematical understanding as well as the understanding of necessary libraries to help you ace Data Science interviews and enter into this field.
The course is structured in a very crisp and comprehensive manner to help you understand industry-relevant algorithms. It is structured the following way:
Part 1.) Getting started with R
Setting up R
Getting Started with R Studios IDE
Swirl
Part 2.) Introduction to Statistical Measures
Measures of Central Tendencies
Introduction to Data Science using R
Part 3.) Data Processing and Data Visualisation in R
Measures of Dispersions and Outlier Treatment
Missing Value Treatment using R
Data Visualization using R ( boxplots, bubble plots, heat plots, automated-EDA in R)
Part 4.) Building Regression Models in R
Linear Regression Theory
Linear Regression using R
Multivariate Linear Regression Theory
Multivariate Linear Regression using R (Multiple Linear Regression, R-square, Adjusted R-square, p-value, backward selection)
Part 5.) Building Classification Models in R
Classification using Logistic Regression
Logistic Regression and Generalized Linear Models in R & Measures of Accuracy for a Classification Models (AIC, AUC, Confusion Matrix, Precision, and Recall)
Part 6.) Random Forest Models in R
Introduction to decision tree classifier (trees package, Gini index, and tree pruning )
Creating decision tree and Random Forest in R (Random forest package in R, hyper-parameters tuning, visualizing a tree in R)
Building Random Forest Regressors
The course takes you through practical exercises that are based on real-life datasets to help you build models hands-on.
And as additional material, this course includes R code templates which you can download and re-use on your own projects.
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Rates
Rate
- $7
Pack rates
- 5h: $34
- 10h: $68
online
- $7/h
Details
For a self-paced course, the fee is Rs 999/- for the entire course. For live lectures, the fee is Rs 600/- per hour. There will be 6 lectures, each of 1 hour, thus, the cumulative fee will be Rs 3600/- for the entire course in live lecture mode.
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