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Setareh Ghafouri Gharavi
Learner
(1)
31
Location
Toronto, Ontario, Canada
Bio

I am a graduating Computer Science student from Toronto Metropolitan University with a strong foundation in programming, particularly in Python and Java. I also have experience in Rust, where I developed a Boggle game using the Depth First Search algorithm.
Through my participation in The Information and Communications Technology Council of Canada (ICTC)โ€™s Cybersecurity and Work-Integrated Program, I developed fundamental cybersecurity skills and earned Microsoft certificates in Cloud Computing, Security and Compliance, and Artificial Intelligence. Additionally, I spent 16 months working at MHI RJ Aviation as an Intelligence Analyst where I applied my technical skills in Python and data analysis to design and develop an online sales tool. I contributed to the full stack development of the tool, uncovered actionable insights from company data, and presented findings to senior management through oral and visual presentations.

Resume
resumeSGG (7).pdf
Portals

Skills

Algorithms 2 Applications of artificial intelligence 2 Artificial intelligence 2 Cyber security 2 Cyber threat intelligence 2 Machine learning algorithms 2 Research 2 Threat detection 2

Socials

Achievements

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Level UP exit survey completion- February 2025 cohort
Issued by Level UP: February 2025
Awarded for sharing your feedback โ€” your insights help us improve Level UP, and this badge recognizes your valuable contribution.
Completed on March 31, 2025
Level UP community builder - February 2025 cohort
Issued by Level UP: February 2025
Awarded for providing feedback at the end of a Level UP project.
Completed on March 31, 2025
Level UP Community Builder
Issued by Level UP: February 2025
Awarded for providing feedback at the end of a Level UP project.
Completed on March 31, 2025

Latest feedback

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Sylvia Kmiecik
President
March 31, 2025
Individual endorsement
Algorithms Applications of artificial intelligence Machine learning algorithms Cyber security Cyber threat intelligence Threat detection Artificial intelligence Research

I had the privilege of working with Setareh, and she is truly an exceptional talent. From the very start, she demonstrated intelligence, initiative, and a deep passion for AI and cybersecurity. Her ability to research, analyze, and apply machine learning models to real-world security challenges was remarkable. Not only did she develop a Python-based model for classifying network intrusions, but she also provided well-researched insights into optimal AI models for cybersecurity. Setareh is highly organized, meets deadlines with precision, and communicates her ideas effectively. She has a rare combination of technical expertise, analytical thinking, and problem-solving skills that make her stand out. Her dedication and enthusiasm for her work were inspiring, and I have no doubt she will excel in any opportunity she pursues. I highly recommend Setareh for any role or project requiring a sharp, innovative, and highly capable individual.

Learner feedback
Setareh is an exceptionally sharp and intelligent individual who demonstrated remarkable expertise and initiative from the very beginning of the project. She stood out as the strongest in the cohort, showcasing a deep understanding of AI and cybersecurity. Her ability to apply machine learning to real-world challenges was truly impressiveโ€”she not only researched optimal AI models for cybersecurity but also developed a working Python-based machine learning model for classifying network intrusions. Her passion for the subject was evident in both her work and the way she presented her knowledge. I was truly amazed by her brilliance, and her contributions added immense value to the project.
Algorithms Applications of artificial intelligence Machine learning algorithms Cyber security Cyber threat intelligence Threat detection Artificial intelligence Research
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Level UP: February 2025
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The Lady Instructor
AI-Driven Cybersecurity Threat Detection
The Lady Instructor

Recent projects

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The Lady Instructor
The Lady Instructor
Mississauga, Ontario, Canada

AI-Driven Cybersecurity Threat Detection

In today's digital landscape, cybersecurity threats are becoming increasingly sophisticated, posing significant challenges to organizations worldwide. Vloe is seeking to enhance its cybersecurity measures by integrating artificial intelligence to detect and mitigate potential threats more effectively. The project aims to develop a prototype AI model that can analyze network traffic data and identify anomalies indicative of cyber threats. Learners will apply their knowledge of machine learning algorithms and cybersecurity principles to create a solution that can adapt to evolving threats. The project will involve researching existing AI models used in cybersecurity, selecting appropriate algorithms, and training the model using sample datasets. The ultimate goal is to provide Vloe with a proof-of-concept tool that demonstrates the potential of AI in strengthening cybersecurity defenses.

Matches 1
Category Artificial intelligence + 4
Open

Work experience

Business Intelligence Analyst
MHI RJ Aviation
Mississauga, Ontario, Canada
September 2022 - April 2023

-Maintained and enhanced functionality of MHI RJโ€™s sales analytics tool by creating new features using Python, such as utilizing data files to visualize timely purchase of parts and allow users to filter by time frame (monthly, weekly, yearly) and specific buyers, maximizing access to important insights for strategic decision-making.
-Overhauled analytics data by writing Python scripts to remove redundant data and merge old and new data files, conserving user time by making data more accurate and readable for users
-Customized data visualization and user interface by using HTML to optimize graphics, decreasing time spent by users to configure tool
-Used Excel and Python (Pandas) to analyze company data and discover significant insights on buyer purchases of specific products over time and factors influencing them, conveyed findings to senior management, influencing future strategic decisions

Education

BSc, Computer Science
Toronto Metropolitan University
September 2020 - May 2025

Personal projects

AI900 - Azure AI Fundamentals

SC900 - Security, Compliance, and Identity Fundamentals

AZ900 - Azure Fundamentals

Machine Learning Report - Air Pollution

Analyzed hourly air quality data using PCA and K-means clustering in Python, identifying pollution patterns in an Italian city. Preprocessed data, reduced dimensionality, and visualized results, revealing key insights on peak and low pollution times based on traffic patterns