Courses

E-Learning

Curriculum

  • Sl. No.
  • Chapter
  • Chapter - 1
  • Getting Started With Python
  • Chapter - 2
  • Python for Data Science(NumPy, Pandas , Matplotlib , Seaborn )
  • Chapter - 3
  • Exploratory Data Analysis
  • Chapter - 4
  • Data Analysis Using SQL
  • Chapter - 5
  • Statistics
  • Chapter - 6
  • Hypothesis Testing
  • Chapter - 7
  • Machine Learning - Supervised Learning (Regression)
  • Chapter - 8
  • Logistic Regression
  • Chapter - 9
  • Decision Trees
  • Chapter - 10
  • Classification Techniques-CART
  • Chapter - 11
  • Support Vector Machine(SVM)
  • Chapter - 12
  • Unsupervised Learning : Clustering
  • Chapter - 13
  • Principal Component Analysis (PCA)
  • Chapter - 14
  • Ensemble Modelling
  • Chapter - 15
  • Time Series Analysis
  • Chapter - 16
  • BI Tools:- Tableau Basics
  • Chapter - 17
  • Natural Language Processing
  • Chapter - 18
  • Text Mining And Sentimental Analysis
  • Chapter - 19
  • Reinforcement Learning
  • Chapter - 20
  • AI & Deep Learning - Introduction
  • Chapter - 21
  • Advance Deep Learning & Computer Vision
  • Chapter - 22
  • BI Tools:- Google Data Studio
  • Chapter - 23
  • BI Tools: PowerBI
  • Chapter - 24
  • Getting Started with R

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Post Graduate Program in Data Science , this Course and batch also available in other locations View

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