'R' and Python Programming for Data Science, Analytics & AI

Program Fees: ₹ 44,000

Early Bird: ₹ 39,600 (after 10% discount)

Program Dates: August 14 - 18, 2018 (Full-time: 9 am - 6:00 pm daily )

Program Venue: India (further details to be communicated after registering interest)

Why 'R' and Python

  1. A good conceptual & application knowledge of the two most popular & widely used languages in the domains of Data Science & Analytics, Machine Learning and AI helps launch an individual for an exciting & rewarding career in these domains.
  2. Good first languages for learning the basics of easily readable, elegant code which looks like rudimentary English or simple, abstract Mathematics. 
  3. Both ‘R’ and Python allow the programmer to code quickly. Owing to their agile design and flexibility, these languages are used by several enterprises for a variety of other applications including web development.
  4. Data Science, Analytics, Machine Learning & AI are among the fastest growing and most rewarding domains for professionals and a grounding in both ‘R’ & Python is the ideal launchpad for a rewarding career in these domains.

Key takeaways for participants:

  • Equipping oneself for a rewarding career in Data Science and AI.
  • Getting a theoretical and application grounding of the two most popular languages used in Analytics, Machine Learning & AI.
  • Picking up two of the hottest and most sought-after skills currently for software development professionals.

Faculty - Dr. S. Das


Dr. Das graduated in Electrical Engineering and has subsequently done his Ph.D. in the same discipline, after doing his post-graduation in Control Systems.

He has several years of industry experience and is currently an Asst. Professor in the Department of Data Science for a private University, where, among various subjects, he has also been involved in teaching ‘R’.

He has a number of published papers in the domains mentioned to his credit and is a visiting scientist at the Indian Statistical Institute (ISI), involved in the areas of Statistical Quality Control & Operations Research. His research interests include Data Analytics, Stochastic Systems and Real-time Systems

Typical participant feedback:
“The workshop used tutorials & practical exercises to create interest and to help in understanding some applications of R and Python Programming. I recommend this program for all those wanting to pursue a career in the domains of Analytics & AI.” -- Experienced participant from the 'Financial Services' sector

FAQs about the Program answered:

Course Content Outline:


Day 1

Basic Statistics

Basic Probability and Distributions

Basic Linear Algebra

Introduction to R

R fundamentals

Arithmetic with R

Numerical Data Handling

Vectors

Matrices

Categorical Data Handling

Data frames

Lists

Tutorials

Day 2

R programming

Conditionals and Control Flow

Loops

Functions

Data Visualization in R

Basic R graphics

Different plot types

Plot customizations

Data Importation

Descriptive Statistics using R

Exploring Categorical Data

Exploring Numerical Data

Numerical Summaries

Tutorials

Day 3

Bivariate data visualization

Correlation

Simple regression

Regression model and its interpretation

Logistic Regression

Regression model and its interpretation

Quiz

Project


Day 4

Introduction to Python

Python Setup

Variable and Arithmetic in Python

Python Data Types

List, Tuple, String, Set, Dictionary, Array and Matrix

Python programming

Conditionals and Control Flow

Loops

Functions

Modules and Packages: NumPy, Pandas, etc.

Data Importation in Python

Python graphics

Numerical Summaries in Python

Tutorials


Day 5

Descriptive Statistics using Python

Exploring Categorical Data

Exploring Numerical Data

Inferential Statistics using Python

Simple regression: Model fit and its interpretation

Logistic regression: Model fit and its interpretation

Quiz

Project




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