Continuing Education Program in Data Science

& Artificial Intelligence

Up skill yourself today and become a certified Data Scientist 7 Months | Weekend Classes | Entry through DSAT | 100% Job Assistance for selected Candidates with Partner

Organizations

Offered by EICT (Electronics & ICT) Academy, IIT Kanpur in association with MeitY (Ministry of

Electronics and Information Technology, Govt of India)

Move from Data Insights to Business Impact

Continuing Education Program in Data Science & Artificial

Intelligence

The Continuing Education Program in Data Science & Artificial Intelligence is a 7 Months

(6 Months + 1 Month Capstone) classroom program offered by EICT (Electronics & ICT)

Academy, IIT Kanpur in association with MeitY (Ministry of Electronics and Information

Technology, Government of India). The state-of-the-art curriculum is designed and

taught by award- winning academician’s AI Professionals from our knowledge partner –

The Ikigai Lab..

The program is designed with an experiential approach of both intellectual studies and

hands-on application to ensure that candidates who successfully complete the program

excel in sectors such as consumer markets, finance and risk management, and

information technology.

With an estimated worldwide demand of 4.4 Million jobs for skilled data practitioners,

certified Data Scientists are poised to scale new heights and create impact in global

companies.

Program Objective

This course aims to impart the ability to understand and resolve complex business analytics

problems across a variety of different industries and environments, using appropriate data-

driven analytics techniques and tools. These highly in-demand skills enhance executives’ career

prospects and competency in business analytics.

Your Future

Research suggests that data–driven companies simply perform better. Business analytics

competencies combined with big data technologies is the new route to bigger profits. 60% of

Fortune 500 companies have already adopted big data strategies, thus fueling the demand for

highly skilled data practitioners.

The Course is designed to equip you for these new career opportunities.

Key Advantages

o Strong Potential for Breakthrough and Innovations: The program provides a firm grounding

in analytical foundations and applications as well as a valuable exposure to top-notch

research and practice.

o High Quality of Business and Social Networking: In business, who you know matters! The

program provides a conducive platform for students from diverse industries to network with

senior managers in leading companies.

o Inter-disciplinary Education and Experience: Enterprises increasingly demand cross-

organization skills. The program provides an integrated education involving business

modeling and analytics technologies.

Curriculum Overview

The program comprises several modules that concurrently run with a Capstone module.

Capstone includes one full-time project of 100 hours with industry partners.

Business Requirement Gathering and understanding

Basic of Probability and Statistics

Python as a Data Science/Artificial Intelligence Language

Machine Learning

Regression (Lasso, Ridge)

Classification (Logistic, Tree based)

Clustering (K-means, Fuzzy, Hierarchical, Density Based Clustering)

K-Nearest Neighbor

Support Vector Machines

Forecasting (ARIMA, Holtz Winters)

Ensemble Learning

Markov Models

Dimension Reduction

Bagging (Random Forest)

Gradient Boosting

Data Wrangling

Pandas

Outlier treatment

Missing values treatment

Handling Imbalance Data

Introduction to Deep Learning

Neural Network Basics

Reinforced And Federated Learning

Introduction to GAN

GPU, CPU, TPU architecture and their role in DL

Deep Neural Network

Convolutional Neural Networks (CNN)

Recurrent Neural Networks (RNN)

Natural Language Processing

Text Mining and Applications

Basics of NLP (POS, entity recognition)

Applications of Regular expression

Sentiment Analysis

Topic Modelling

Clustering in Text Documents

Computer Vision

Image Processing

Convolutional features for visual recognition

Object Detection

Object tracking and Action Recognition

Image Segmentation and Synthesis

Tools for AI

Introduction to SQL and MySQL

Introduction to NoSQL and MongoDB

Introduction to Docker and Kubernetes

Data Lake and centralization strategy

Using cloud specific services for AI solution

Creating and Deploying API

Introduction to ELK Stack

Introduction to Spark and Distributed Computing

Deployment of AI Solutions

Unit and System Testing

Model Lifecycle management

Integration with Dev Ops and relevant architectures

Retraining Pipeline

Deployment of AI on Cloud

AI Ops Best Practices

Data Visualization

Tableau

Power BI

Admission Requirements:

Entry to the Course is through Data Science Aptitude Test Only.

About DSAT:

Data Science aptitude is based on Sternberg Theory of intelligence and aims to evaluate

“Analytical Intelligence of the candidate”. Analytical Intelligence is the kind of intelligence which

helps one in decipher complex scenarios and draw patterns out of it.

Syllabus for DSAT

Data Interpretation

Business Understanding

Quantitative Aptitude

Integrated Reasoning

Statistics and Probability

ENTRY REQUIREMENTS:

University degree with mathematics background, preferably in any of the following

disciplines: B.Sc. (Stat, Math, Physics, Chemistry, Geology) or B.E/B. Tech

Cleared Data Science Aptitude Test (DSAT)

Good grasp of mathematical and statistical concepts

_________________________________________________________________

Key Contact Person:

Sudhir Singh Nayak- (+91-9871998784, sudhir@theikigailab.com)

Abhay Pandey – (+91-8882050481, abhay.pandey@theikigailab.com)

Industry Partner: Knowledge Partner: