Overview

Dear All,

The Department of Data Science proposes to initiate a Technical Training & Career Pipeline focused on strengthening industrial integration for B.Sc. and M.Sc. Mathematics & Data Science students. This initiative is designed to provide structured industry exposure through technical training, hands-on projects, internships, and career-oriented guidance.

The program aims to align academic learning with current industry requirements and equip students with job-ready skills in data science, analytics, and allied domains. By collaborating with industry partners, students will gain practical experience, improve their professional competencies, and enhance their employability.

Objectives of Event

The objectives of this initiative are:

· To bridge the gap between theoretical knowledge and real-world industrial applications in Data Science.

· To provide industry-oriented technical training aligned with current tools, technologies, and practices.

· To offer students hands-on exposure through live projects, internships, case studies, and mentorship.

· To enhance students’ technical, analytical, and problem-solving skills.

· To prepare students for interviews, placements, and higher career opportunities.

· To strengthen industry–academia collaboration for sustainable career development.

Technical Training & Internship Domains

The program will offer training and industry exposure in the following domains:

· Data Scientist / Data Analyst Trainee: Practical exposure to data analysis, statistical modeling, machine learning techniques, and predictive analytics using real datasets.

· Machine Learning & AI Trainee: Hands-on training in supervised and unsupervised learning, model building, evaluation, and deployment basics.

· Business Analytics Trainee: Application of data science techniques to business problems, decision-making, and performance analysis.

· Research & Analytics Trainee: Support in applied research, data collection, data cleaning, quantitative and qualitative analysis, and report preparation.

· IT & Data Support Trainee: Exposure to data handling systems, dashboards, databases, and basic deployment tools.

· Industry Project Intern: Participation in live or simulated industry projects under expert mentorship.

Expected Outcomes

1. Enhanced technical competency among students in Data Science and Analytics.

2. Improved understanding of industry expectations and professional work culture.

3. Increased student participation in internships, projects, and placement activities.

4. Development of communication, teamwork, and problem-solving skills.

5. Stronger linkage between academic curriculum and industry needs.

6. Creation of a sustainable career pipeline for Data Science students.

7. Improved employability and placement readiness of graduating students.

8. Strengthened collaboration between the university and industry partners.

9. Increased recognition of the university as a talent hub in Data Science and Analytics.

Convener Details

Convener Details:      Dr. Khursheed Alam (HOD–Mathematics & Data Science) 

Co-ordinators:

Organizing Secretary:  Dr. Surya Kant Pal (surya.pal@sharda.ac.in)

 

Coordinators:               

                                        Dr. Sachin Singh

                                        Dr. Utpal Dhar Das

                                        Dr. Santosh Kumar

                                        Dr. Reetu

                                        Dr. Sohan Lal

                                        Dr. Neha Bhardwaj 

                                        Dr. Nidhi Sahni 

                                        Dr. Milan Srivastava

Speaker Details:

  • Shoqeen Nabi, Founder & CEO, Sojourn Technocrates Communication Pvt. Ltd. Srinagar | Delhi | Dubai | +91 9149671541