Artificial Intelligence is changing Job Scenarios, are you prepared for the future?

Similar documents
School of Innovative Technologies and Engineering

Python Machine Learning

Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence

STA 225: Introductory Statistics (CT)

Visit us at:

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur

TIMSS ADVANCED 2015 USER GUIDE FOR THE INTERNATIONAL DATABASE. Pierre Foy

Twitter Sentiment Classification on Sanders Data using Hybrid Approach

Unit 7 Data analysis and design

Lecture 1: Basic Concepts of Machine Learning

The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X

DOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME

Nottingham Trent University Course Specification

Level 6. Higher Education Funding Council for England (HEFCE) Fee for 2017/18 is 9,250*

Courses in English. Application Development Technology. Artificial Intelligence. 2017/18 Spring Semester. Database access

Algebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview

Computerized Adaptive Psychological Testing A Personalisation Perspective

Certified Six Sigma - Black Belt VS-1104

Probability and Statistics Curriculum Pacing Guide

BSc (Hons) Banking Practice and Management (Full-time programmes of study)

SRI LANKA INSTITUTE OF ADVANCED TECHNOLOGICAL EDUCATION REVISED CURRICULUM HIGHER NATIONAL DIPLOMA IN ENGLISH. September 2010

ESIC Advt. No. 06/2017, dated WALK IN INTERVIEW ON

MSc Education and Training for Development

PROSPECTUS DIPLOMA IN CENTRAL EXCISE AND CUSTOMS. iiem. w w w. i i e m. c o m

Axiom 2013 Team Description Paper

Spring 2014 SYLLABUS Michigan State University STT 430: Probability and Statistics for Engineering

Faculty of Social Sciences

HARPER ADAMS UNIVERSITY Programme Specification

MASTER OF SCIENCE (M.S.) MAJOR IN COMPUTER SCIENCE

(Sub)Gradient Descent

Laboratorio di Intelligenza Artificiale e Robotica

Learning Microsoft Publisher , (Weixel et al)

Implementing a tool to Support KAOS-Beta Process Model Using EPF

Course Specification Executive MBA via e-learning (MBUSP)

A Case Study: News Classification Based on Term Frequency

GRADUATE STUDENTS Academic Year

ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF

CSL465/603 - Machine Learning

GRADUATE STUDENT HANDBOOK Master of Science Programs in Biostatistics

Statistics and Data Analytics Minor

BUS Computer Concepts and Applications for Business Fall 2012

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming.

CS4491/CS 7265 BIG DATA ANALYTICS INTRODUCTION TO THE COURSE. Mingon Kang, PhD Computer Science, Kennesaw State University

Lecture 1: Machine Learning Basics

Certified Six Sigma Professionals International Certification Courses in Six Sigma Green Belt

Learning From the Past with Experiment Databases

Probabilistic Latent Semantic Analysis

Urban Analysis Exercise: GIS, Residential Development and Service Availability in Hillsborough County, Florida

1. M. Sc. Program objectives

ABHINAV NATIONAL MONTHLY REFEREED JOURNAL OF RESEARCH IN COMMERCE & MANAGEMENT

Specification of the Verity Learning Companion and Self-Assessment Tool

ZHANG Xiaojun, XIONG Xiaoliang School of Finance and Business English, Wuhan Yangtze Business University, P.R.China,

Introduction to Ensemble Learning Featuring Successes in the Netflix Prize Competition

Abstract. Janaka Jayalath Director / Information Systems, Tertiary and Vocational Education Commission, Sri Lanka.

Full text of O L O W Science As Inquiry conference. Science as Inquiry

COURSE LISTING. Courses Listed. Training for Cloud with SAP SuccessFactors in Integration. 23 November 2017 (08:13 GMT) Beginner.

BHARATHIAR UNIVERSITY UNDER UNIVERSITY INDUSTRY INTERACTION PROGRAMMES

International Branches

Bangalore Mysore Pondicherry Tirupati

Artificial Neural Networks written examination

IIT. That s where I long to belong.

Shockwheat. Statistics 1, Activity 1

University of Cambridge: Programme Specifications POSTGRADUATE ADVANCED CERTIFICATE IN EDUCATIONAL STUDIES. June 2012

Lesson M4. page 1 of 2

Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for

Mining Association Rules in Student s Assessment Data

Course outline. Code: ICT310 Title: Systems Analysis and Design

Citrine Informatics. The Latest from Citrine. Citrine Informatics. The data analytics platform for the physical world

OFFICE SUPPORT SPECIALIST Technical Diploma

Machine Learning from Garden Path Sentences: The Application of Computational Linguistics

MAHATMA GANDHI KASHI VIDYAPITH Deptt. of Library and Information Science B.Lib. I.Sc. Syllabus

GENERAL SERVICES ADMINISTRATION Federal Acquisition Service Authorized Federal Supply Schedule Price List. Contract Number: GS-00F-063CA

Post-Master s Certificate in. Leadership for Higher Education

MODULE 4 Data Collection and Hypothesis Development. Trainer Outline

Reducing Features to Improve Bug Prediction

1. Programme title and designation International Management N/A

PROGRAMME SPECIFICATION KEY FACTS

Making welding simulators effective

Impact of Cluster Validity Measures on Performance of Hybrid Models Based on K-means and Decision Trees

M55205-Mastering Microsoft Project 2016

Lahore University of Management Sciences. FINN 321 Econometrics Fall Semester 2017

Generative models and adversarial training

SOFTWARE EVALUATION TOOL

DBA Program Curriculum

TotalLMS. Getting Started with SumTotal: Learner Mode

Intermediate Computable General Equilibrium (CGE) Modelling: Online Single Country Course

An Evaluation of E-Resources in Academic Libraries in Tamil Nadu

Colorado s Unified Improvement Plan for Schools for Online UIP Report

2017 FALL PROFESSIONAL TRAINING CALENDAR

Rule Learning With Negation: Issues Regarding Effectiveness

Multivariate k-nearest Neighbor Regression for Time Series data -

Laboratorio di Intelligenza Artificiale e Robotica

SCT Banner Student Fee Assessment Training Workbook October 2005 Release 7.2

Ericsson Wallet Platform (EWP) 3.0 Training Programs. Catalog of Course Descriptions

Diploma in Library and Information Science (Part-Time) - SH220

Introduction to Causal Inference. Problem Set 1. Required Problems

What s in a Step? Toward General, Abstract Representations of Tutoring System Log Data

Deep search. Enhancing a search bar using machine learning. Ilgün Ilgün & Cedric Reichenbach

UNIT ONE Tools of Algebra

Teacher of Art & Design (Maternity Cover)

Transcription:

Artificial Intelligence is changing Job Scenarios, are you prepared for the future? Elimination of 1.8 million jobs by 2018 but 2.3 million jobs will be created by 2020. Offsets deficit Gartner reporting in the Hindu in Oct 2017. Re-skilling/ Up-skilling/ Re-tooling will ensure future relevance & employability Come & Join.. Indian Institute of Technology (ISM), in collaboration with Ativitti AI Technologies Pvt. Ltd. present CERTIFIED COURSE on ATIVITTI AI TECHNOLOGIES PRIVATE LIMITED Brochure_11.indd 1

Data Analytics for Machine with R Line-up for rewarding careers in emerging technologies and become experts with IIT(ISM) Professional Development Program to gain knowledge, practical know-how to solve complex business problems. Program Overview This IIT Certified Intensive Lab Oriented Course is focused on building industry ready Data Scientist who can work on machine learning, data mining, and statistical modelling for predictive and prescriptive enterprise analytics. This program will enable you to develop deep understanding of and experience with machine learning and data analysis. Familiarity with common tools for data management and analysis including machine learning can be applied on real world problems for building predictive models using machine learning on your own. R is the most popular data analytics tool owing to it being open-source, its flexibility, packages and community. R wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. IIT (ISM) 6 day (48 hours) Full Time, Lab Oriented PROFESSIONAL DEVELOPMENT PROGRAM on DATA ANALYTICS for MACHINE LEARNING. IBM Predicts Demand For Data Scientists Will Soar 28% By 2020, the number of jobs for all US data professionals will increase by 364,000 openings to 2,720,000 according to IBM Top notch IIT professors to train the industry professionals imparting real-world skills to improve their capabilities in dealing with emerging technologies in areas of Data Analytics for Machine & helping re-engineer the business sense and the economy. Brochure_11.indd 2

ProgramHighlights Especially developed in collaboration with academia & AI Industry experts to reskill and retool working professionals towards Artificial Intelligence space, this program offers the following benefits: Top notch IIT Faculty Led Sessions: 6days/48 Hours of Intensive Classroom & Lab oriented Classes. Program content & structure designed by IIT (ISM) in conjunction with Industry Real-life Case: Live project based on any of the selected use cases, involving implementation of R tool providing hands-on exposure Assignments: Each class has practical assignments which shall be finished before the next class and helps you to apply the concepts taught during the class. Access to LMS: You get access to Management System (LMS) where presentations, quizzes, installation guide & class recordings are there. 24 x 7 Expert Online Support team to resolve all your technical queries Certification: IIT (ISM) certifies you as a Data Analyst for Machine based on your project performance, reviewed by our expert panel. Course Delivery Methodology (48 hours of intensive classroom & lab lessons focussed over 6 days) Full-time classroom based course led by IIT faculties focused on Problem-based-learning methodology allowing students to become more active learners as they figure out which information is needed to solve a problem. There are many advantages to students in using this approach, as it allows them to: Develop transferable skills and enhance their employability Improve communication and team working Practice research and information processing Develop Machine analytical skills All enrolled participant s will be provided access to other learning aids, reference materials, assessments and hands on workshops as appropriate. During the course students will also be allocated Project work that is designed to provide adequate practical and hands on experience in implementing the concepts learned during the course. Brochure_11.indd 3

DAY 3 DATA VISUALIZATION AND BASIC STATISTICS Introduction to Data Visualization Basic Graphics: line, bar, box, histogram plots Trellis Scatter plots Instructor Data visualization Program Content Data Analytics for Machine with R is organized in twelve modules over 6 full days. The course will be in two parts Introduction to R, Data Visualization & statistics with hands on lab sessions. Building predictive models & introduction to latest tools/ technologies for solving real-life problems. DAY 1 BASICS OF ARTIFICIAL INTELLIGENCE, MACHINE LEARNING & DATA ANALYTICS WITH R Introduction to Artificial Intelligence (Evolution of Technology) Branches of Artificial Intelligence and what is Machine. Supervised, Unsupervised & Reinforcement. How machine learning can be applied in technology, science, trading etc. Comparison B/W R, Python & SAS. Why Learn R? Introduction to R. R Overview, R Interface, R Work Space, Help, Variables, Programming Install R. Running a few simple programs. DAY 2 BASIC PROGRAMMING IN R Tutorial: Machine & Activity Discussion about the Machine Discussion about the R programming 03:00-05:00 Some Common Terms & Basics in R Data Types Importing Data Keyboard Input, Database Input, Export Data Variable Labels, Value Labels, Missing Data, date Values R Iteration & Conditional Constructs. R Packages: installation and Usages. Data Manipulation Creating New Variable Operators Built-in functions Control Structures User Defined Functions Sorting Data Merging Data Aggregating Data Reshaping Data Sub-setting Data Data Type Conversions Hands On Session Some Advance Programs using Data from R Data repository. Lab - Basics of R. R programming Lab Discussion about the R programming Lab Basic Statistics: mean median, mode, percentile, quantile Frequency Distribution, Histogram Analysis Data: Distribution Types of Data Distribution Hypothesis Testing DAY 4 BASIC STATISTICS Basic Statistics using R Sample Data: Summarizing Samples Cumulative Statistics Summary Statistics for Data Frames Summary Statistics for Matrix objects Hands on Practice Basic Statistics using R Summary Statistics for Lists Summary for Table objects Hands on Practice DAY 5 BUILDING PREDICTIVE MODEL Introduction to Predictive Models Linear Regression Logistic Regression Decision Tree Random Forest Implementation of Predictive Models using R The Art of Feature Engineering. Pattern recognition Principal component analysis. DAY 6 INTRODUCTION TO LATEST TOOLS & TECHNOLOGIES Classification & Clustering Supervised K- Nearest Neighbors Classification Unsupervised K means Clustering Algorithm Reinforcement Implementation of Classification & Clustering Using R Introduction to Neural Networks Introduction Deep. Implementation of Neural Network using R Multi layer Perceptron (MLP) Support Vector Machine (SOM) Instructor Machine Instructor Basics of Statistics in R Instructor Predictive Model Algorithms & Activity Instructor discuss about the Feature Engineering Instructor Basics of Statistics in R Instructor discuss about Data analysis in R Brochure_11.indd 4

FACULTY DR. SUSANTA MUKHOPADHYAY Associate Professor Department of Computer Science and Engineering, Indian Institute of Technology (ISM) Program Outcome On completion of the program, students will have developed a world-class skillset in their selected technology domain that provides Employability Enhancing skills and capabilities thereby substantially increasing their earning potential and compensation benchmarks. Candidates can expect to be hired in positions such as: Machine Specialist Data Science Researcher Data Engineer DR. DIPANKAR RAY System Programmer Indian Institute of Technology (ISM) IIT (ISM) CERTIFICATE On the payment of course fees of (` 80,000/- plus GST @ 18% = ` 94,400/-; For international Students : US$ 1500 plus GST (@18%) and upon satisfying the requisite attendance and other evaluation criteria of the Professional Development Program in Data Analytics for Machine with R, participants will be awarded a Certificate of Completion issued by IIT (ISM),. DR. SUBHASHIS CHATTERJEE Associate Professor Department of Applied Mathematics Indian Institute of Technology (ISM) WHO SHOULD ATTEND Professionals who want to learn the practical aspects of data handling across applicable areas like Machine, IT Services, Marketing, ecommerce, Research etc. Project Managers, Business Managers and Senior Leaders managing large data analytics machine learning based projects interested in gaining understanding of AI/ML domain. Executives, young professionals & managers with analytical aptitude who are interested in and want to learn Data Individuals who aspire to switch to or embark on a career in Business Analytics & Machine Prerequisites Mathematics as a subject up to Class XII. Programming knowledge will be preferable Though full-fledged Lab access will be provided at IIT (ISM) facility, it will be preferable to bring your own laptop HOW TO APPLY For admissions, students can register at our website www.ativitti.in Total Tuition Fee `80,000 plus GST @ 18% For international Students: US$ 1500 plus GST @18% DURATION OF PROGRAM 14th -19th May 2018 Course Fee: `80,000/- plus GST @18% = `94,400 ; For international Students: US$ 1500 plus GST @18% For Outstation Students, (at their own cost) their stay can be arranged at negotiated rates at Hotel Crown Plaza, Okhla Phase-1, New Delhi DURATION 6 Days/48-Hours From Monday till Saturday, every day from 9:00AM to 05.00PM For Course Payment Please pay to IIT (ISM) account, details of which are as follows: Name of Account Holder : IIT(ISM), Bank Name : CANARA BANK Bank Account No. : 0986101009746, IFSC Code : CNRB0000986 Branch Address : Canara Bank, Saraidhela Branch, Shree Shyam Bhawan, Main Road, Distt., Pin 828127, Jharkhand MICR Code : 826015003 ELIGIBILITY CRITERIA For Indian Participants Graduates (10+2+3) or Diploma Holders (only 10+2+3) from a recognized university (UGC/ AICTE/State Government) in any discipline. For International Participants Graduation or equivalent degree from any recognized University or Institution in their respective country. For Indian and International Participants Interns or Working professionals. ATIVITTI AI TECHNOLOGIES PRIVATE LIMITED Address for Communication Ativitti AI Technologies Pvt. Ltd, IIT (ISM) Centre, 4th Floor, Unit # 401, NBCC Centre, Plot # 2, Okhla Phase -1, New Delhi 110020 For any enquiry, please write to us at: enquiry@ativitti.ai Call us at: +91-9267999473; +91-9267994573 Brochure_11.indd 5