← Back to cohort

Zunera zahid

NUST · 2024
Email
zunera.zahid@seecs.edu.pk
Phone
+92 333 5482787
LinkedIn
GitHub

Academic

Program
BS in Computer Science
CGPA
2.94
Year
2024
Education
School of Electrical Engineering and Computer Science
Address
DOB

Career

Current role
Target role
Skills
programming concepts, Machine Learning, recommendation system, E-Commerce App, AI-powered shopping app, image recognition technologies, Cosine similarity, SVD, Kaggle Dataset, customer data analysis, Linux file system, Tree structure
Interests / quote
Computer science expert with a strong foundation in programming concepts. I am eager to expand my skills in programming languages. My ability to think critically and solve complex problems allows me to excel in developing efficient and robust software solutions. I am ready to contribute my enthusiasm and technical expertise to make a meaningful impact in the field of computer science.

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.
Name: Zunera zahid 
Company: Nust(seecs) 
Phone: +92 333 5482787 
Email: zunera.zahid@seecs.edu.pk 
Professional Profile
Computer science expert with a strong foundation in programming concepts. I am
eager to expand my skills in programming languages. My ability to think critically and
solve complex problems allows me to excel in developing efficient and robust software
solutions. I am ready to contribute my enthusiasm and technical expertise to make a meaningful impact in the field of computer science.
Education
BS in Computer Science 
School of Electrical Engineering and Computer Science , 2.94 
FSC(Pre-engineering) 
Kinnaid college , 1006/1100 (2020) 
Matric 
LDA Model Girls HIgh School, Johar Town , 1065/1100 (2018) 
Internship Experience
Agri-tech Lab SINES ( 15-Jun-2023 - 17-Aug-2023 ) 
Worked as an Machine Learning intern. Develop a recommendation system of E-
Commerce App.
Projects
Intelli Shop: An AI powered shopping app (FYP) 
The proposed project is an AI-powered shopping app that will use machine learning and image
recognition technologies to offer personalized recommendations and an enhanced shopping
experience for users. The app will include an admin dashboard that will allow the admin to analyze
sales data, providing insigh
Recommendation system (Shopping app) 
A recommendation system guiding users towards tailored content and products. One of the primary
paradigms within recommendation systems is the item-based similarity and user-based similarity
approaches. Implement Cosine similarity and SVD.
Marketing Strategy Project 
Campaign design for a retail client using Kaggle Dataset. To analyse customer data and predict their
behaviour, enabling businesses to deliver more targeted and personalized marketing campaigns.
Filesystem 
A Linux file system's implementation. The commands are similar to the Linux. Tree structure is used to
implement this system.

AI enrichment

Zunera Zahid is a recent Computer Science graduate with an internship in machine learning and experience developing recommendation systems. Her academic projects include an AI-powered shopping app and a Linux filesystem implementation, demonstrating foundational skills in software development and data analysis.
Skills (AI)
["Machine Learning", "Python", "Recommendation Systems", "Image Recognition", "SVD", "Cosine Similarity", "Linux Filesystem", "Data Analysis", "Kaggle"]
Status: ai_done
Provenance
Source file: GB-BSCS-2024-updated.pdf
From job #251 page 29
Created: 1778162373