on machine learning · e-certificate will be given to the participants attending 80% of session and...
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Department of Information Technology
19th Km Stone, NH-09 (Formerly NH-24), Ghaziabad, UP, (INDIA)|Ph.: 0120-7135112/113, Fax: 0120-7135115, +91 9999889341Email: [email protected]|Web: www.abes.ac.in
[College Code-032]
NAAC Accredited and NBA Accredited UG Programs (CSE, ECE, EN & IT)
Five Day Online Faculty Development Program
MACHINE LEARNINGth th
11 – 15 January, 2021
Dr. APJ Abdul Kalam Technical University, LucknowSponsored by
Resource Persons
v Dr. Jagdish Chand Bansal, Associate Professor, South Asian University New
Delhi and Visiting Faculty at Maths and Computer Science, Liverpool Hope
University UK.
v Dr. Vivek Kumar Singh, Professor, Department of Computer Science, BHU.
v Dr. Vishal Bhatnagar, Professor, Department of CSE, NSUT East Campus
(Formerly Ambedkar Institute of Advanced Communication Technologies &
Research), Geeta Colony, Delhi.
v Dr. Shampa Chakraverty, Professor, Computer Engineering, Netaji Subhas
University of Technology, Dwarka, Delhi.
v Dr. Aniruddha Shelotkar, Director, Pashyaa Technologies Pvt. Ltd., Pune.
v Dr. Sudeep Tanwar, Professor, CSE Department, Nirma University, Gujarat.
v Dr. Ankur Choudhary, Professor, Department of Computer Science &
Engineering, Sharda University, Greater Noida.
v Dr. Arun Prakash Agrawal, Professor, Department of Computer Science &
Engineering, Sharda University, Greater Noida.
v Dr. Vikram Bali, Professor, JSS Academy of Technical Education Noida.
v Dr. Shishir Kumar, Professor, Department of Computer Science & engineering,
Jaypee University of Engineering and Technology, Guna, MP.
v Dr. Ritesh Srivastava, Associate Professor, Galgotias College of Engineering &
Technology, Greater Noida.
v Dr. Vinay Kumar Jain, Research Engineer, IFP Energies Nouvelles, France.
v Dr. Balakrishnan S, Professor and Head, Sri Krishna College of Engineering&
Technology (Autonomous), Coimbatore.
v Mr. Ravi Srivastava, Sr. Tech Lead, HCL UK.
Contact Person
The interested participants should register themselves through.
I. Google form: https://tinyurl.com/FDPREGISTRATION1115012021
II. Scan QR code to registration form:
III. Faculty members of the college affiliated with AKTU
can only register for this FDP. There is for such faculty members. NO REGISTRATION FEE
Prof. (Dr.) Amit Sinha
[email protected]|+91 9899949001
Prof. (Dr.) Anish Gupta
[email protected]|+91 8510932323
Address for CorrespondenceDepartment of Informa�on Technology
ABES Engineering College, 19th Km Stone, NH-09 (Formerly NH-24), Ghaziabad, UP, (INDIA)Ph.: 0120-7135112/113, Fax: 0120-7135115, +91 9999889341|Email: [email protected]|Web: www.abes.ac.in
on
Registration Process & Fee (NIL)
E-certificate will be given to the participants attending 80% of session and secured minimum 60%
marks in the quiz. The quiz will be conducted on the last day of FDP.
Certificate
Dr. Harikesh Singh
Associate Professor-IT, ABESEC
Dr. Kanika Gupta
Assistant Professor-IT, ABESEC
Chief Patrons
Prof. (Dr.) Vinay Kumar PathakVice Chancellor, Dr. APJAKTU, U.P.
Sh. Neeraj GoelPresident, ABESEC
Patrons
Sh. Sachin GoelVice President, ABESEC
Dr. Shailesh Tiwari
Director, ABESEC
Prof. (Dr.) Amit Sinha Professor & Head-IT, ABESEC
ConvenerProf. (Dr.) Anish Gupta
Professor-IT, ABESEC
Co-Convener
Mr. Manish Kumar Sharma
Assistant Professor-IT, ABESEC
Program Coordinators
Organizing Commitee
Mr. Ashwin Perti
Assistant Professor-IT, ABESEC
Dr. Deepak Kr. Singh
Professor-IT, ABESEC
Dr. Parashu Ram Pal
Professor-IT, ABESEC
Registration Form
Name (in block letters) ______________________________________________
Designation:_______________________________________________________
Organization:______________________________________________________
Mailing Address:____________________________________________________
_________________________________________________________________
Mobile:__________________ Email:____________________________________
Educational Qualifications:_______________
Signature of Applicant:_____________________
Five Day Online Faculty Development Program
on
ABES Engineering College, Ghaziabad
Signature of Head of Department / Director of Institute (with date & seal)
Department of Information Technology
Machine Learning
Sponsored by-Dr. A.P.J. Abdul Kalam Technical University, Lucknow, U.P.
About ABES Engineering College
ABES Engineering College (Estd. 2000) is affiliated to Dr. A.P.J Abdul Kalam Technical University, Lucknow. ABESEC has been established with an objective of providing education in Engineering and Management. The programs offered by the institute includes various verticals under Bachelor of Technology (B.Tech) i.e., Computer Science & Engineering, Electronics & Communication Engineering, Electrical & Electronics Engineering, Information Technology, Mechanical Engineering, Computer Science, Computer Science & Engineering (Artificial Intelligence and Machine Learning), Computer Science & Engineering (Data Science). The post graduate courses include MBA, MBA (Business Analytics) MBA (Logistics & Supply Chain Management), MCA and M.Tech. ABESEC is approved by AICTE, Ministry of HRD, Government of India. The college is ISO 9001:2015 certified, NAAC Accredited & NBA Accredited UG Programs (CSE, ECE, EN, IT) with NIRF India Rankings 2020: Engineering Rank Band 201-250. ABESEC achieved the excellent academic performance for consecutively Four Years in B.Tech. First Year AKTU results and also achieved ARIA, IIC Ranking .
About the Department
The Department of Information Technology is one of the oldest department in ABESEC and accredited by National Board of Accreditation (NBA). The department is working towards advance technical enhancement and runs industry readiness program through training, certification and development program. The department has signed MOU with ICT Academy, Oracle Academy and is a lead zone partner of leading India. The department also owns ABESEC- IEEE student Branch Chapter for the overall development of students.
Objectives of FDP
Machine learning is the field of study that gives computers the ability to learn without being
explicitly programmed. It is a form of AI that enables a system to learn from rather than
through explicit programming. It helps in analyzing the data as well as identifying trends.
Machine learning and Artificial Intelligence (AI) are among the most sought after and highly
compensated digital economy skills.
The objective of this FDP is to present recent trends and applications of machine learning.
This area is of utmost importance as there is a significant and growing demand for Artificial
Intelligence (Al) professionals and researchers in businesses, public, agencies, and non-
profits organizations. This FDP would provide participants with the guidelines to explore
the area of Machine Learning and its Application. The participants would learn to develop
methods for solving problems related to diverse computational fields. This program will
Unlock the potential of participants and introduce various skills that go into Machine
Learning, provide practical walk-through of relevant languages, tools and lay down study
plan for moving forward in this field.
Benefits of attending this programAttendees will be benefited in the following areas: Ø Familiarize with the basic concepts of Machine Learning.Ø Understanding the need for machine learning for various problem solving.Ø Latest trends in machine learning and deep learning techniques. Ø Case studies and gain "industry-like experience".Ø Provide the innovative ideas for research approach.Ø Provide the solution for business like compete Intelligently, Enhance Customer Services,
Manage Sales and Detect Fraudulent Activity.Ø Help us in terms of Financial services, Governmental, Health and Retail.
Course ContentsThe Faculty Development Program aims to include the major topics:
Ø Basics of Machine Learning
Ø Machine Learning: AI and it's applications
Ø The Rise of Swarm Intelligence
Ø Role of Machine Learning in IoT-based Security Solutions
Ø Machine Learning in Industries
Ø Machine Learning for Text Processing
Ø Data Stream Mining
Ø Regularization Techniques in Machine Learning
Ø Basics of Optimization and Nature Inspired Approaches
Ø Nature Inspired Optimization and its Applications to Complex Engineering Problems
Ø Industry 4.0 and the digital twin
Ø Machine Learning using Generative Adversarial Networks (GAN)
Ø Business Intelligence Tool Tableau
Who can apply?
The FDP is open to all discipline of engineering and designed for the faculty members from Dr.
APJ Abdul Kalam Technical University, affiliated colleges, who are keen to learn machine
learning tools for different research areas.
Availability of SeatsLimited to 100 participants on first come first serve basis.
Important Dates
Start date of Registration: December 14, 2020
Last date of Registration: December 31, 2020
Intimation of confirmation: January 05, 2021
th th11 – 15 January, 2021