Summary

Course Name : BSc in Artificial Intelligence and Machine Learning

Eligibility : 10 + 2 (Science & Maths) or equivalent, in Information Technology stream.

Programme fees : 60,000/- Per Annum

FAQ

IT - Information Technology Enabled Services (IT-ITeS)

Introduction of the Sector

In today’s digital era Information and Communication Technology have become one of the basic requirements of society. It is difficult to think of any event without the use of digital devices. ITeS sector includes IT services, engineering design, R & D services and BPO services. IT includes a wide variety of operations that uses information technology to improve the efficiency of any organization. ITeS services are delivered over telecom or data network to a range of external business areas. The changing economic and business conditions, rapid technological innovation, the proliferation of the internet and globalization are creating an increasingly competitive environment. The role of technology has evolved from supporting corporations and their transformation. All these factors have made IT-ITeS a competent vertical among others.

BSc in Artificial Intelligence and Machine Learning

Programme Introduction

As per a report published by Gartner, Artificial Intelligence is expected to create a huge job market with around 2.3 million opportunities during 2020- 2021. This number gets bigger with each passing day as more and more companies are transforming themselves to harness the power of data lying with them. “Data is the new oil”; there is a deeper truth to this saying than being mere words. Data has been growing by leaps and bounds like never before. Most industries across the globe, adopted data analytics as one of their chief functions since the last decade. This has fueled the development of Artificial Intelligence (AI) and Machine Learning (ML) as chief disciplines. Data analysis has multifaceted functions; it has helped businesses attain key goals, decipher actionable insights, formulate critical decisions and generate innovative products and services. The course brings an overall platter of knowledge and skills, needed to hop on the ML and AI domains. With a diligently crafted course curriculum, students will gain a root-level understanding of concepts driving the ML algorithms. Successful completion of the courses will enable students to take on multiple job roles in the data analytics discipline.

Eligibility for Admission

10+2 (Science & Maths) or equivalent, in Information Technology stream.

Career Prospects/Job Role

Skills in ML can also lead to fresh graduates becoming junior data scientists. Graduates can take up the role of a Data Scientist in Deep Learning. Those interested in end-point security can have a career in Automation with ML, for example to recognize file malware threats and deal with them effectively. Many jobs are available as Scientist in Analytics and Machine Intelligence.

Knowledge Provider for Skill Trainning

Soft Scibble, Mukesoft, Rath Infotech, The Cybertech, Wolfx.

Semester-wise Listing of Courses

SEMESTER I			SEMESTER II
Course Code	Course Name	Credits	Course Code	Course Name	Credits
GE 1.1	Functional English	2	GE 2.1	Communication Skills	2
GE 1.2	Computing Skills and Digital Literacy	2	GE 2.2	Environmental Studies	2
AI 1.1	Foundational course on Artificial Intelligence (AI) and Machine Learning (ML)	2	AI 2.1	Fundamental Programming using R	2
AI 1.2	Mathematics for Data Science	2	AI 2.2.	Statistics for Data Science	2
AI 1.3	Programming Concepts and Problem Solving using Python	2	AI 2.3	Machine Learning Methods using Python and R - I	2
AI ST1	Skill Training	12	AI ST2	Skill Training	12
CDPNE	*Domain Practicum	NC	CDPNE	*Domain Practicum	NC



SEMESTER III			SEMESTER IV
Course Code	Course Name	Credits	Course Code	Course Name	Credits
GE 3.1	Financial Literacy	2	GE 4.1	Design Thinking	2
GE 3.2	Basics of Legal and HR Policies	2	GE 4.2	Organizational Behaviour	2
AI 3.1	Database Management Systems and Data Warehousing	2	AI 4.1	Machine Learning Methods using Python and R - II	2
AI 3.2	Programming for AI and ML using Python and R	2	AI 4.2	Big Data and NoSQL	2
AI 3.3	Advance Statistics for Data Science	2	AI 4.3	Data Visualization and Story- telling with Tableau	2
AI ST3	Skill Training	12	AI ST4	Skill Training	12
CDPNE	*Domain Practicum	NC	CDPNE	*Domain Practicum	NC


SEMESTER V			SEMESTER VI
Course Code	Course Name	Credits	Course Code	Course Name	Credits
GE 5.1	Health and Wellness	2	GE 6.1	Entrepreneurship	2
GE 5.2	Personal Grooming	2	GE 6.2	Employment Readiness	2
AI 5.1	Natural Language Processing with Machine Learning	2	AI 6.1	Computer Vision using Artificial Intelligence	2
AI 5.2	Artificial Intelligence and Robotics	2	AI 6.2	Machine Learning for Business Domains - HR Analytics	2
AI 5.3	Machine Learning for Business Domains - Marketing Analytics	2	AI 6.3	Machine Learning for Business Domains - Finance and Risk Analytics	2
AI ST5	Skill Training	12	AI ST6	Skill Training	12
CDPNE	*Domain Practicum	NC	CDPNE	*Domain Practicum	NC

Note: Laptop / Desktop is recommended for the program.

*Domain Practicum- “Compulsory and Non-Credit, non-evaluative component"

The Skill Training component is 50% to 60% ranging from 600 hours to 720 hours per year depending upon the industry requirement

Programme fees: Rs. 60,000/-per annum
Examination fees: Rs. 1,600/- per semester and Rs.3200/- per annum
Caution Deposit (Refundable): Rs.5000/-
Convocation Fees: Rs.2000/- (In absentia Rs.2500/-)