continuing education program in data science & artificial ... · the program comprises several...
TRANSCRIPT
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, [email protected])
Abhay Pandey – (+91-8882050481, [email protected])
Industry Partner: Knowledge Partner: