fbpx
Open

Data Analytics with Tableau & R

Data Analytics with Tableau & R

Course Description

The key skill of a Statistical Analyst is to be able to derive actionable insights from Data and be able to communicate that to the stakeholders. The primary focus of the ‘Data Analytics with Tableau & R’ course is Project based learning where students will work on various Industry level Analytics projects and gain real confidence
The course is divided into two sections Students will start with Data Visualization, Descriptive Analytics, Dashboarding with Tableau and then deep-dive into more focused advanced topics on Predictive Analytics & Time Series Analysis with R-programming.
Each class will involve working on business case studies, examples, and assignments. Students will also work on and present 3 Capstone projects.

Our Instructor

Amar Vajjhala

IIT Bombay, Faculty – NYU, Ex VP Nomura, UNP Director for Emerging Tech.

Vivek Kalyanarangan

BTech, WBUT Young leader in the banking industry, UNP advisor on emerging techs.

In collaboration with the Dept. of Mathematics & Statistics, Bhavan's Vivekananda College

Data Analytics with Tableau & R

Duration:

30 hour [2 hours x 15 sessions]

At the end of the course:

Students will enhance their concepts in statistics and gain hands-on experience on relevant industry projects. You will be able to confidently apply the learnings to deliver Data Analytics assignments and projects.  You will be comfortable using Tableau and R, two widely used visual analytics tools in the industry for data analytics projects.

Prerequisite:

Basic hand-on programming experience in R

*Starting form Starting from 27-Nov-2021 !

Session 1 - 6: Predictive Analytics with R using ML Algorithms

Meeting-amico (1)

Session 7 - 10: Time-series Analysis with R

Session 11 - 15: Data Handling, Visualization, Descriptive Analytics, Dashboarding with Tableau

Coworking-amico

Certification:

You will receive a course completion Certificate from UNP upon successful submission of Assignments and Capstone projects.

Project Topics:

The projects that you will work on during this course will be data science based problems occurring in different industries.

The project execution will be simulated as to how a real-time project is executed in corporate organizations.

At the end of the project, you will get to present your findings and recommendations to Industry leaders.

This process will be helpful for students, specially freshers, to get accustomed to the life cycle of a project as executed in the industry.

– Telecommunication – the rate of adoption and prediction of internet usage in rural India
– E-commerce – recommendation of products from previous purchase history
– Health care – prognosis from ICU data
– Finance & Banking -balanced portfolio design by identification of correlated and contra related stocks
– Power and heavy industry – predicting equipment failure and reliability from past operation data

More of You

Additional self-learning materials and assignments

Sessions from Industry experts

Help create Digital footprints, Resume preparations for Students

Sessions on Presentation, Interview skills

Discussion forum for immediate doubts

Quiz, class assignments, practice work

Peer-to-peer assignment discussion