Program Description

Before now, data analytics tasks were reserved for data practitioners; as AI becomes commonplace, business/non-technical individuals can now create dashboards for data visualization and advanced data querying. AI enables users to perform data analytics functions by communicating with the system using natural language processing. This generational change in data analytics allows for quicker and easier access to data insights, enabling decision-makers to make data-driven decisions without relying on technical experts.
This certification program is designed for anyone, who like to sharpen their skills in Data Science at a broader perspective, by learning coding, applications and use case experiences from scratch.

On successful completion of the programme, you will
Yes. You will get IITM Pravartak Foundation Certificate when you get at-least 60% of the course score. You will get GradsKey certificate if you get more than 50% of the course mark. Course scores would be cumulative of weekly assignments/test, projects, viva, and mock-interviews that happens then and there.

Key Highlights

check svg

Live class courses would be recorded and available for replay, this recording would be available for an year.

check svg

Placement assistance for the top students through GradsKey partners and from IITM Pravartak partners.

Learning Format

Online

Duration

12 weeks

Certified by

IITM Pravartak Technologies Foundation
Technology Innovation Hub (TIH) of IIT Madras and
GradsKey

Program Fee

12,000/- (inclusive of GST)

Program Description

Education Qualification

B.Tech/B.Sc/MCA passed out students or in the pre-final / final years

Suggested Prerequisites

No pre-requisites

Teaching Hours

60 hours

Learning Module

  • Overview of data science and its role in various industries
  • Types of data and their characteristics
  • Data collection, storage, and retrieval methods
  • Basic data analysis techniques and tool

  • Introduction to programming languages, particularly
  • Python or R
  • Data types, operators, and expressions
  • Control structures and functions
  • Debugging and error handling
  • Working with external libraries and APIs

  • Principals of data visualization and storytelling
  • Data visualization tools and libraries
  • no-code/low-code Tableau Platform
    and Matplotlib, Plotly Libraries
  • Plotting charts, graphs, and maps
  • Interactive data visualization using web-based tools and frameworks
  • Plotly, Bokeh Libraries, and Dash framework.

  • Data cleaning and preprocessing techniques - Pandas Library, DataWrangler tool
  • Exploratory data analysis (EDA) techniques - no-code/low-code with Tableau
  • Linear regression and predictive modeling - with no-code/low-code Google Cloud AutoML Tables.
  • Time-series analysis and forecasting - with no-code/low-code Google Cloud AutoML Tables.


Are you interested in this program?

Our Learning Partners

Want To Know More

Guiding Star with Our Help!

Contact Us