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Pro Data Science – Industry Focused Expert Program

This course caters to become industry expert in Data Science and Analytics field.

Key Features

  • Mode –Instructor Led Training
  • Duration – 3 Months
  • Timings –Weekend Regular classes (Saturday + Sunday) and 1 doubt clearing class on weekdays
  • Business Case Studies covered – 20
  • Exercises & Project Work
  • Certification and Job Assistance
  • Flexible Schedule
  • Lifetime free upgrade
  • 24 x 7 Lifetime Support & Access
  • Certified by top MNCs
  • Data Science enabled real industry projects
  • CV and Profile revamp
  • Job referrals and assistance

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Below is the Curriculum of Pro Data Science course:

Exploratory Data Analysis (EDA)

  • Why EDA is important?
  • Steps to follow to start with?
  • Covering all visualization libraries
  • At the same time with data set will learn the stuff
  • working on projects
  • Advance statistics
  • CLT
  • Hypothesis testing

Hyper – Parameter Tuning

  • Gradient descent
  • Hyper – parameter tuning major algorithm will cover as per industry guidelines.

Feature Engineering

  • Feature Engineering Introduction
  • Variable Transformation
  • Raw Data to Feature
  • Good Vs Bad Feature
  • Dimension Reduction
  • Representing Features
  • Filter methods
  • Constant, quasi constant, and duplicated features
  • Basic methods + Correlation + uni-variate ROC-AUC pipeline
  • Wrapper methods RFE, Forward/Backward
  • Aggregation
  • Dimensionality Reduction
  • Feature Creation
  • Introduction to Feature Crosses
  • Implementing & Embedding Feature Crosses
  • Discretization
  • Binarization
  • Memorization & Generalization
  • Sparcity Handling
  • Embedded Methods: Lasso Regularization, Linear, Tree methods
  • Feature Importance
  • Evaluating Features
  • VIF

Pre-Processing

  • Feature scaling Introduction
  • Standardization
  • Mean normalization
  • MinMaxScaling
  • Maximum absolute scaling
  • MaxAbsScaling
  • Robust Scaling
  • Vector unit length Scaling
  • One hot encoding
  • Probability ratio encoding
  • Ordinal encoding
  • Count or frequency encoding
  • Target guided ordinal encoding
  • Mean encoding
  • Weight of Evidence
  • Rare label encoding
  • Binary encoding and feature hashing
  • Merge Train and Test
  • Memory reduction
  • NAN trick
  • Dataflow Pipelining

Sampling Techniques

  • Simple Random Sampling
  • Stratified Sampling
  • Progressive Sampling

Sample Certificate:

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  • 28,000.00 7,500.00
  • 3 months
  • Course Certificate
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