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


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