Data Science Overview
Accelerate your career in data science by mastering concepts of Data Management, Statistics, Machine Learning and Big Data from most influential Data Science leaders.
Learn. Experience. Master.
- For the Industry, By the Industry
- Domain Specialization
- Career Guidance
Data Science – A Definition
Data Science is the science which uses computer science, statistics and machine learning, visualization and human- computer interactions to collect, clean, integrate, analyze, visualize, and interact with data to create data products.
What is a data scientist to do?
These data scientists, who have expertise in computer applications, data modeling, statistical analysis, and more. Not only analyzing and resolving informational problems of the organization, their role in providing information security is very important.
Thanks to the digital revolution that is sweeping the world and India in particular, data scientists are now the most sought-after professionals by big corporations as well as startups. And companies across industries are rewarding good data analysts and scientists with desirable career growth and salaries.
Learn by Application
Learn from our comprehensive collection of case-studies, hand-picked by industry experts, to give you an in-depth understanding of how data science moves industries like telecom, transportation, e-commerce & more.
Course Duration: 40 hours
Time Commitment: 4 hours per week – Program Fee: Rs.16, 000/-
Statistics with R
- Understanding R and its data structures
- Descriptive statistics
- Data Distribution
- Hypothesis testing
- Graphs and plots
- Summary statistics etc
- Linear Regression and case study
- Logistic Regression and case study
- Case studies in Regression
Time Series Analysis
- Stationary process
- AR, MA, ARIMA modelling using R with examples
- What is classification ?
- Decision Tree, k-NN, Neural network
- Probabilistic methods, SVM, Random Forest
- What is Clustering ?
- k-means , Hierarchical clustering
Market Basket Analysis
- Association Rule mining and case study
- Credit Risk evaluation using R
- Few more…