Diganta - Data Analysis tutor - Kolkata
Diganta - Data Analysis tutor - Kolkata

The profile of Diganta and their contact details have been verified by our experts

Diganta

  • Rate 72 GHS
  • Response 1h
  • Students

    Number of students Diganta has accompanied since arriving at Superprof

    8

    Number of students Diganta has accompanied since arriving at Superprof

Diganta - Data Analysis tutor - Kolkata

72 GHS/hr

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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

  • Primary school
  • Junior high school
  • SHS 1
  • +20
  • levels :

    Primary school

    Junior high school

    SHS 1

    SHS 2

    SHS 3

    BTS

    University education

    Adult Education

    Facultate (Licență)

    Master's degree

    Higher national diploma

    Doctor of philosophy

    Other

    GDL

    Qualified Lawyer Transfer Scheme

    MBA

    Pre school

    Beginner

    Intermediate

    Advanced

    Professionel

    Others

    Child

  • 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

  • 72 GHS

Pack prices

  • 5h: 359 GHS
  • 10h: 719 GHS

online

  • GHS72/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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