Data Science Batch 1(DS1)

We have opened registrations for DS1, please reach us to register.

The curriculum for DS1:

Chapter#Description
IIntroduction
 1. History – Data & Its evolution
 2. Insight – Why Data Science buzz everywhere?
  
IIMaths & Statistics – Basics 1
 Descriptive & Inferential Statistics
 Random Variables – Discrete/Continuous 
 Few Definitions : – Percentile, Decile, Quartile, Quantile
 Probability
 Few more definitions – Dispersion, Degrees of Freedom, Centering data, mean, mode, median, sd ..etc
 Expected Value, Variance, covariance
  
IIIData Visualization
 Box Plot, Line chart, Bar chart, Histogram, Scatter Plot. Pie chart..etc
  
IVR/Python Programming 
 Programing Fundamentals
  
VMaths & Statistics – Basics 2
 Data Distributions – Discrete/Continuous
 Sampling Distributions of Mean and variance
 Central Limit Theorem
 Decision making
 Confidence Interval, Z,t,F tables, 
 Estimation of Variance, Chisquare distribution, proportions
 One/two samples z/t test, P-value method
 Test of Hypothesis
 ANOVA
  
VIMaths & Statistics – Basics 3
 Matrix Algebra (As per need)
 Coordinate geometry (As per need)
 Calculus (As per need)
  
VIICRISP-DM Framework
 Life cycle of Data science projects
 Data Sourcing, cleaning, uni/bi variate analysis, derived metrics
 Model Building & Evaluation
  
VIIIMachine Learning – Part 1
 R/Python Programming – Adv
 Simple Linear regression with case study
 Multiple Linear regression with case study

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