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Sakar O. Khidr
Contact information:
Working Address (Fulltime):
3rd Floor
Basic and Education Building
College of Informatics and Programming Engineering
The University of Raparin
Main Street
Ranya – Al Sulaymaniyah
KRG – Iraq
Education & Qualification:
BSc in Software Engineering / Salahaldin University-Erbil (2014)
MSc of Artificial Intelligence and Robotics/ Kurdistan University, Sanandaj-Iran (2021)
Scientific Rank:
Assistant Lecturer: June 9, 2022
Positions:
1. Administration:
Lecturer at College of Basic Education- department of computer science Since 2022- Present.
Employee in the Office of Computer Sciences from 2016 to 2019.
2. Scientific Duty:
o Assistant Lecturer at College of Engineering- Informatics and Programming Engineering department / University of Raparin
o Researcher (University of Raparin)
o Visiting Lecturer at Dukan Technical Institute, Department of Information technology.
Summary of Working Experiences:
On 25th Nov 2015 I Started as an assistant engineer in University of Raparin/ College of Basic Education- department of Computer Science.
In the private sector, I worked as a lecturer from Raparin private Institute (20016-2019), which is private institute for computer science.
I was supervised of many students when they graduate from Raparin private institute.
Given presentations on many topics in the computer science and programing field at the Raparin private Institute.
Skills:
1. Programming Languages
Python: Widely used for AI and ML due to its extensive libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Java, C++, and C#: Useful for performance-intensive applications.
JavaScript: Relevant for AI in web development.
2. Mathematics and Statistics
Linear Algebra: Essential for understanding ML algorithms.
Calculus: Important for gradient-based optimization techniques.
Probability and Statistics: Critical for data analysis and algorithm development.
3. Machine Learning and Deep Learning
Supervised and Unsupervised Learning: Understanding different types of learning techniques.
Neural Networks: Knowledge of deep learning architectures like CNNs, RNNs, and GANs.
Frameworks: Proficiency in TensorFlow, PyTorch, Keras, etc.
4. Data Handling and Processing
Data Wrangling: Skills in cleaning and preprocessing data.
Big Data Technologies: Familiarity with Hadoop, Spark, and other big data frameworks.
Databases: Knowledge of SQL and NoSQL databases.
5. Algorithms and Data Structures
Algorithm Design: Strong foundation in designing efficient algorithms.
Data Structures: Proficiency in common data structures like arrays, linked lists, trees, and graphs.
6. Computer Vision
Image Processing: Understanding of techniques for image recognition and processing.
CV Libraries: Experience with OpenCV, PIL, and similar libraries.
7. Reinforcement Learning
RL Algorithms: Understanding of Q-learning, policy gradients, and other RL techniques.
8. Cloud Computing and Deployment
Cloud Platforms: Experience with AWS, Google Cloud, Azure, etc.
Containerization: Proficiency in Docker and Kubernetes.
CI/CD: Knowledge of continuous integration and continuous deployment pipelines.
9. Soft Skills
Problem-Solving: Strong analytical and critical thinking skills.
Communication: Ability to explain complex technical concepts to non-technical stakeholders.
Collaboration: Experience working in cross-functional teams.
Training:
Field of interest:
Artificial Intelligence (AI) and Machine Learning (ML) for Distributed Systems
Reinforcement Learning
Combinatorial Optimization Algorithms
Edge/Fog/Cloud Computing
Workshop activity and Attended:
Professional Activities and Societies:
Computer and Other Equipment Skills:
Language:
Mother tongue: Kurdish-Sorani
Knowledge of other languages:
Language: Written Reading Speaking Understanding
Arabic: Good, Good, Medium, Good
English: Very Good Very Good Very Good Very Good
Parsian: Very Good Very Good Very Good Good
English Language Certification:
English Language Certification. 10th April 2020
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