Current Location: Kerman Province, Iran

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  [email protected]

• Data Science    (Entry-level)
• AI Project Management    (Entry-level)
• AI Research and Development    (Entry-level)
• ...

• Open to remote work
• Not willing to relocate

🎓 I am pursuing a Master's in Electrical Engineering specializing in Telecommunications-System at the Shahid Bahonar University of Kerman. My academic focus includes various facets of artificial intelligence, including Machine Learning, Deep Learning, and Data Analysis. 💡 I am eager to apply my skills and knowledge in these areas to contribute effectively to AI-related roles.

Employment

• Organization
  AI.Group
• Region
  Kerman, Kerman Province, Iran
• Role
  AI Project Manager

2024-present

Employment

• Organization
  IDPL-Lab
• Region
  Kerman, Kerman Province, Iran
• Role
  AI Research & Development (R&D)

2021-2023

Data Science Challenge | Coursera Projects

Nov 2023 - Nov 2023 (3 days)

• Project scenario
  

A Data Science Coding Competition project that uses a real-world dataset to develop a prediction or classification model. Participants approached the problem using Python and Jupyter Notebook, focusing on data manipulation, feature engineering, and model evaluation. The competition allowed students to practice their problem-solving and critical thinking skills and gain experience with machine learning algorithms and data visualization techniques.

• Skills demonstrated
  

Data Science Data Analysis Python Programming Machine Learning

• Tools used
  

Python

• Summary
  

Optimized data for balance, removed redundancy and enhanced predictive power using advanced techniques. Achieved project objectives seamlessly.

• Solution
  

In this project, I addressed data imbalances by configuring predictors to 'balanced' mode. Identified and removed redundant features using Gradient Boosting Classifier for feature selection. Applied One-Hot encoding to convert nominal to numerical data. Achieved optimal model performance through Hyperparameter tuning using Grid Search. Overall, I successfully streamlined the dataset and achieved project objectives.

• Approach
  

In carrying out the research, I began with extensive data exploration, resolving imbalances by configuring 'balanced' predictors. Using the Gradient Boosting Classifier, redundant features were identified and eliminated, nominal data was encoded with One-Hot, and feature selection was performed. We refined the model using hyperparameter tuning with grid search to ensure optimal performance and project completion.

• Project links
  

GitHub Repo
Coursera Read-Only File

Clean and Analyze Social Media Usage Data with Python | Coursera Projects

Nov 2023 - Nov 2023 (2 hours)

• Project scenario
  

You're a data analyst at a marketing firm that promotes brands on social media. Your team wants you to use Python to extract tweets based on specific categories (health, family, food, etc.), clean and analyze the data, and create visualizations. They will use your analysis to help clients improve their social media performance. This insight will allow the firm to deliver tweets on time and within budget, leading to faster results.

• Skills demonstrated
  

Seaborn Data Analysis Python Programming Pandas Data Visualization

• Tools used
  

Python

• Summary
  

Taking on "Clean and Analyze Social Media Usage Data with Python," I described, displayed, and analyzed data. Python's "Data Visualization" improved my insights and honed my abilities for future assignments.

• Solution
  

Using Python to analyze social media data, I computed average likes and shares over time, uncovered trends, and grouped data by country to reveal engagement patterns. I used a correlation matrix to investigate relationships between likes and shares, demonstrating my ability to extract useful insights.

• Approach
  

To understand the dataset, I started the project by writing a descriptive "Data Description." Moving on to "Data Information," I established a solid foundation for future analysis. "Data Visualization" in Python improved clarity. With a well-prepared dataset, the "Data Analysis" step revealed significant patterns. This process demonstrated the successful use of Python for modification, visualization, and analysis in completing the "Clean and Analyze Social Media Usage Data with Python" project.

• Project links
  

GitHub Repo
Coursera Read-Only File

Masters Student:
Electrical Engineering (Telecommunication-System)
@Shahid Bahonar University of Kerman
2020 - Present

Bachelor's Degree:
Electrical Engineering (Telecommunication-System)
@Shahid Bahonar University of Kerman
2016 - 2020

Other Educations:


Note: For viewing the education details click on each image.

Specializations

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Courses

GAN Field

• Build Better Generative Adversarial Networks (GANs) | Coursera - DeepLearning.AI
• Apply Generative Adversarial Networks (GANs) | Coursera - DeepLearning.AI
• Build Basic Generative Adversarial Networks (GANs) | Coursera - DeepLearning.AI

Data Science Field

• Data Analysis with Python | Coursera - IBM
• Python for Data Science, AI & Development | Coursera - IBM
• Data Analysis with R Programming | Coursera - Google

NLP Field

• Sequence Models | Coursera - DeepLearning.AI
• Natural Language Processing with Classification and Vector Spaces | Coursera - DeepLearning.AI

Deep Learning Field

• Generative AI for Everyone | Coursera - DeepLearning.AI
• Convolutional Neural Networks | Coursera - DeepLearning.AI
• Introduction to Machine Learning in Production | Coursera - DeepLearning.AI
• AI Capstone Project with Deep Learning | Coursera - IBM
• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization | Coursera - DeepLearning.AI
• Deep Neural Networks with PyTorch | Coursera - IBM
• Advanced Learning Algorithms | Coursera - DeepLearning.AI, Stanford University
• Supervised Machine Learning: Regression and Classification | Coursera - DeepLearning.AI, Stanford University
• Building Deep Learning Models with TensorFlow | Coursera - IBM
• Unsupervised Learning, Recommenders, Reinforcement Learning | Coursera - DeepLearning.AI, Stanford University
• Structuring Machine Learning Projects | Coursera - DeepLearning.AI
• Machine Learning | Coursera - Stanford University
• Neural Networks and Deep Learning | Coursera - DeepLearning.AI

Project Management Field

• Foundations of Project Management | Coursera - Google

Cybersecurity Field

• Play It Safe: Manage Security Risks | Coursera - Google
• Foundations of Cybersecurity | Coursera - Google

Git & GitHub Field

• Getting Started with Git and GitHub | Coursera - IBM

Web Development Field

• Introduction to Back-End Development | Coursera - Meta

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Cybersecurity Portfolio

This cybersecurity portfolio demonstrates expertise by auditing a fictional company's controls, risks, and compliance. The comprehensive report details the security posture through an asset inventory, risk assessment, control types and purposes, and a compliance checklist. It offers recommendations to mitigate identified risks and gaps. Conducting audits to identify and remediate vulnerabilities showcases cybersecurity skills.


View the full document of this cybersecurity Portfolio here .

Machine Learning & Deep Learning Skills

Convolutional Neural Networks (CNNs) Artificial Neural Network Transformers Logistic Regression Linear Regression Decision Trees Recommender Systems Facial Recognition System Object Detection and Segmentation Concept Drift ML Deployment Challenges Mathematical Optimization Tree Ensembles Xgboost Anomaly Detection Reinforcement Learning Collaborative Filtering Multi-Task Learning ...

NLP Skills

Recurrent Neural Networks (RNNs) Transformers Gated Recurrent Unit (GRU) Long Short Term Memory (LSTM) Attention Models Machine Translation Sentiment Analysis Word Embeddings Vector Space Models ...

Data Science Skills

Model Selection Data Analysis Data Visualization Predictive Modelling Data Science R Markdown ...

Generative AI Skills

Transformers Image-to-Image Translation StyleGANs Large Language Models (LLMs) AI Strategy Generative AI Tools AI Productivity Pix2Pix Privacy Preservation ...

Programming Skills

Tensorflow PyTorch Pandas Numpy R Programming Distributed Version Control Systems (DVCS) Git GitHub ...

Project Management Skills

Project Scoping and Design Project Management Change Management Strategic Thinking Organizational Culture Career Development ...

Cybersecurity Skills

Information Security (INFOSEC) NIST Risk Management Framework (RMF) Security Audits NIST Cybersecurity Framework (CSF) Incident Response Playbooks Ethics in Cybersecurity Historical Attacks ...

Web Development Skills

HTML CSS Javascript Bootstrap React