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Course curriculum (Course duration-90 days)

1. Introduction to Data Science

2. Business Statistics

a. Data types

  • Continuous Variables
  • Ordinal variables
  • Categorical Variables
  • Time Series

b. Descriptive Statistics

c. Sampling

d. Data distributions

  • Normal distributions – Characteristics
  • Binomial distributions

e. Inferential statistics

f. Hypothesis testing

3. Introduction to R

  • What is R?
  • Types of Objects in R
  • Creating new variables or updating variables
  • IF Statements and conditional loops-For, while etc
  • String manipulators
  • Sub setting data from matrices and data frames
  • Casting and melting data to long and wide format
  • Merging datasets

4. Exploratory data analysis and visualization

  • Getting data into R- reading from files
  • Cleaning and preparing the data-converting the data types
  • Handling missing values
  • Visualization in R

5. Introduction to Python

6. Statistical Modelling

a. Supervised Learning

  • Linear regression
  • Logistic regression

b. Unsupervised Learning

c. Time series analysis

d. Market Basket analysis

e. Text analytics

fK-NN

7.  Machine Learning

8.  Model validation and deployment

9.  Handling problem cases

10. Advanced packages

11. Artificial intelligence tools in Data Science

12. Extra Offering from Sumedha

  • Interview preparation
  • Case Studies
  • Resume preparation guidance
  • Industry trends, companies information data