Hello dear reader, I’m Can, just a random data engineer & scientist candidate. I have found that creating this blog page allows me to store my work perfectly and encourages me to always be curious about new technologies and more importantly keep learning. Hopefully you would find content on this blog that interests you.
I was always eager to be an engineer from the very first day. When data science became a thing back then, I was that lucky to be able to combine my interests and it was pretty clear where to head.
I’ve been inevitably finding myself coding in major programming languages such as Python, R, and SQL for over 8 years. To keep my projects traceable, reproducible and scalable, I use git for version control, Conda for virtual environments, RStudio projects for structuring working directories, and Jupyter Notebook and R Markdown for interactive computing and reporting.
When I’m not coding, you may find me reading, exploring, traveling, swimming, or sailing. Therewithal I recently started playing Chess and picked up aerial photography again - my portfolio is at ca.photography.
You can find further information about me below or on my Google Scholar, Github, and blog-posts. Also of course you are very welcome to connect with me via LinkedIn.
📚 Education
- M.Sc. in Operations Research, Bogazici University, 2021 CGPA: 3.81/4.0
- B.Sc. in Industrial Engineering and Economics, Istanbul Technical University, 2019 CGPA: 3.53/4.0
- B.Sc. in Wirtschaftsingenieurwesen, Munich University of Applied Sciences, 2018
Research Interests🔎: Stochastic Processes, Simulation, Applied Statistics, Bayesian Network, ML Algorithms, Artificial Intelligence, Deep Learning, Computer Vision, Natural Language Processing
👨💻 Work experience
- Adastra GmbH
- Data Engineer, 09/2022 - Present
- BSH Home Appliances Group
- Global Graduate in IT, Digital & Strategy, 08/2021 - 08/2022
- Data Analyst @BlueMovement Amsterdam, 05/2022 - 08/2022
- Data Scientist @BSH Berlin Laundry Care Technology Center, 01/2022 - 04/2022
- RPA/AI Developer @BSH Munich HQ, 08/2021 - 12/2021
- Product Marketing Working Master Student, 09/2019 - 07/2021
- Global Graduate in IT, Digital & Strategy, 08/2021 - 08/2022
- Eczacıbaşı Building Products (VitrA Bath)
- Market Development Working Student, 08/2018 - 08/2019
- Ford Motor Company
- Manufacturing Intern, 06/2017 - 08/2017
💪 Skill highlights
Advanced | Intermediate | Beginner | |
---|---|---|---|
Programming and Markup Languages | Python, R, SQL | Bash, HTML, CSS, LaTeX, Matlab, Markdown | C++, Java, VBA |
Frameworks and Libraries | Apache Spark, numpy, pandas, Presto, pytest, scikit-learn, Tensorflow, Tidyverse, Trino | Apache Hadoop, Apache Kafka, Databricks, Delta Lake, Keras, mlflow, Neo4j, plotly, Prometheus, PyTorch, sciPy | Apache Cassandra, Bootstrap, Flask, FastAPI, Django, Grafana, Kibana, OpenSSL |
Infrastructure and DevOps | ArgoCD, Bamboo CI/CD, Bitbucket, Docker, Git, JFrog Artifactory, Jira, Okteto | GitHub Actions, Kubernetes, RedHat Openshift | GitLab CI/CD, SonarQube, Terraform |
Cloud and Databases | AWS EC2, AWS S3 | AWS DynamoDB, AWS ECS, AWS EKS, AWS Fargate, AWS Lambda, Azure Databricks, MySQL | AWS RDS, Elasticsearch, MS Access, MongoDB, OracleDB, PostgreSQL, Redis, VMware |
Software, Tools and favorable IDEs | Automation Anywhere, GAMS, Jupyter Notebook, MS Office, Netlogo, RStudio, Spyder IDE, vscode | Anaconda, Arena Simulation, AutoCAD, Google Colab, PowerBI, PyCharm, SPSS Statistics, UiPath | IntelliJ IDEA, Postman, SAP BW, Simulink |
🧠 Projects
-
Volkswagen SQA (Smart Quality Analytics) Associated with Adastra GmbH
-
Low Cost Computer Vision AI on Production Line Associated with BSH Home Appliances Group
-
RPA/AI on Quality Control Checks in Corporate Audit Associated with BSH Home Appliances Group
-
Price-Volume-Mix Analysis Self-Service Dashboard Creation Associated with Eczacıbaşı Building Products (VitrA Bath)
📰 Publications
You are welcome to visit my my Google Scholar profile
🏅 Certifications
HackerRank Certificates
🏆 Course Certifications (over 500 hrs+ of training time)
LinkedIn Learning Certificates
- Data Management with Apache NiFi📅 November 16, 2023 ⏱ 2h 36m
- Learning OpenShift📅 November 8, 2023 ⏱ 1h 8m
- Learning Apache Airflow📅 November 1, 2023 ⏱ 2h 10m
- Using Apache Spark with .NET📅 September 29, 2023 ⏱ 1h 20m
- Advanced SQL for Application Development📅 August 20, 2023 ⏱ 2h 7m
- Advanced SQL for Data Science: Time Series📅 August 9, 2023 ⏱ 1h 18m
- Advanced SQL for Query Tuning and Performance Optimization📅 August 9, 2023 ⏱ 1h 44m
- Advanced SQL - Window Functions📅 August 7, 2023 ⏱ 1h 56m
- Advanced SQL for Data Scientists📅 August 3, 2023 ⏱ 2h 30m
- Advanced Terraform📅 July 25, 2023 ⏱ 2h 25m
- Advanced Kubernetes: Core Concepts📅 July 17, 2023 ⏱ 3h 14m
- Advanced Snowflake: Deep Dive Cloud Data Warehousing and Analytics📅 July 13, 2023 ⏱ 2h 9m
- Advanced BigQuery📅 July 11, 2023 ⏱ 2h 14m
- Deploying and Running Apache Kafka on Kubernetes📅 June 6, 2023 ⏱ 1h 44m
- Learning Terraform📅 May 31, 2023 ⏱ 2h 2m
- Learning BigQuery📅 May 30, 2023 ⏱ 1h 58m
- Kubernetes: Infrastructure as Code with Pulumi📅 May 29, 2023 ⏱ 1h 42m
- Learning SnowflakeDB📅 May 29, 2023 ⏱ 1h 41m
- Kubernetes Essential Training: Application Development📅 May 29, 2023 ⏱ 3h 41m
- Exam Tips: Certified Kubernetes Administrator (CKA)📅 May 23, 2023 ⏱ 1h 37m
- rnetes on AWS (EKS)📅 May 22, 20233 ⏱ 1h 27m
- Kubernetes: Package Management with Helm📅 May 22, 2023 ⏱ 49m
- Kubernetes: GitOps with ArgoCD📅 May 22, 2023 ⏱ 1h 40m
- Getting Started with Kubernetes📅 May 19, 2023 ⏱ 9h 5m
- Securing Containers and Kubernetes Ecosystem📅 May 19, 2023 ⏱ 2h 6m
- Kubernetes: Cloud Native Ecosystem📅 May 15, 2023 ⏱ 34m
- Kubernetes: Microservices📅 May 15, 2023 ⏱ 1h 28m
- Kubernetes: Native Tools📅 May 11, 2023 ⏱ 46m
- Kubernetes: First Project📅 May 11, 2023 ⏱ 2h 44m
- Learning Kubernetes📅 May 9, 2023 ⏱ 1h 26m
- Learning Cloud Computing: Serverless Computing📅 May 8, 2023 ⏱ 1h 17m
- Containerize Applications with Docker📅 May 8, 2023 ⏱ 8h 4m
- Prepare for the Docker Certified Administrator (DCA) Certification Exam📅 May 2, 2023 ⏱ 7h
- Docker Essential Training: 6 Security📅 May 2, 2023 ⏱ 46m
- Docker Essential Training: 5 Networking📅 May 2, 2023 ⏱ 1h 11m
- Docker Essential Training: 4 Storage and Volumes📅 April 29, 2023 ⏱ 54m
- Docker Essential Training: 3 Image Creation, Management, and Registry📅 April 29, 2023 ⏱ 1h 34m
- Docker Essential Training: 2 Orchestration📅 April 28, 2023 ⏱ 1h 4m
- Advanced Pandas📅 April 28, 2023 ⏱ 1h 2m
- Learning Hadoop📅 April 28, 2023 ⏱ 4h 6m
- Big Data Analytics with Hadoop and Apache Spark📅 April 25, 2023 ⏱ 1h 1m
- Essentials of MLOps with Azure: 4 Spark MLflow Models and Model Registry📅 April 22, 2023 ⏱ 12m
- Essentials of MLOps with Azure: 3 Spark MLflow Projects on Databricks📅 April 22, 2023 ⏱ 18m
- Essentials of MLOps with Azure: 2 Databricks MLflow and MLflow Tracking📅 April 19, 2023 ⏱ 20m
- Essentials of MLOps with Azure: 1 Introduction📅 April 19, 2023 ⏱ 48m
- Azure Spark Databricks Essential Training📅 April 4, 2023 ⏱ 2h 52m
- AWS for DevOps: High Availability and Elasticity📅 April 1, 2023 ⏱ 2h 33m
- Amazon Web Services: Data Analytics📅 April 1, 2023 ⏱ 2h 49m
- Kubernetes: Monitoring with Prometheus📅 March 31, 2023 ⏱ 1h 10m
- Monitoring AWS with CloudWatch📅 March 31, 2023 ⏱ 1h 55m
- AWS: Security and Compliance📅 March 30, 2023 ⏱ 6h 37m
- AWS: High Availability📅 March 27, 2023 ⏱ 4h 45m
- AWS: Networking📅 March 26, 2023 ⏱ 4h 27m
- AWS for Developers: SNS, SQS, and SWF📅 February 21, 2023 ⏱ 1h 12m
- Learning Amazon Web Services Lambda📅 February 14, 2023 ⏱ 1h 37m
- Stream Processing Design Patterns with Spark📅 February 14, 2023 ⏱ 1h 9m
- AWS for DevOps: Monitoring, Metrics, and Logging📅 February 12, 2023 ⏱ 2h 41m
- AWS: Storage and Data Management📅 January 23, 2023 ⏱ 5h 4m
- AWS DevOps: Continuous Docker Deployment to AWS Fargate from GitLab📅 January 21, 2023 ⏱ 1h 25m
- Learning AWS CloudFormation📅 January 21, 2023 ⏱ 39m
- Running Kubernetes on AWS (EKS)📅 January 21, 2023 ⏱ 1h 28m
- Introducing Caching to a Serverless Application with CloudFront📅 January 19, 2023 ⏱ 1h 45m
- Amazon Redshift Essentials📅 January 18, 2023 ⏱ 1h 5m
- AWS for Developers: ECS and Multi-Region Load Balancing📅 January 18, 2023 ⏱ 2h 21m
- AWS Security Best Practices for Developers📅 January 16, 2023 ⏱ 1h 32m
- Docker on AWS📅 January 15, 2023 ⏱ 1h 43m
- Data Engineering with AWS📅 January 11, 2023 ⏱ 1h 50m
- AWS: Automation and Optimization📅 January 11, 2023 ⏱ 2h 9m
- AWS Essential Training for Administrators📅 January 2, 2023 ⏱ 5h 55m
- AWS: Monitoring and Reporting📅 December 27, 2022 ⏱ 1h 17m
- Learning Amazon Web Services (AWS) for Developers📅 December 26, 2022 ⏱ 1h 25m
- AWS: Cost and Performance Optimization📅 December 26, 2022 ⏱ 1h 55m
- Amazon EC2 Load Balancers📅 December 23, 2022 ⏱ 3h 44m
- Amazon EC2 Deep Dive📅 December 21, 2022 ⏱ 2h 58m
- Amazon EC2 Fundamentals📅 December 20, 2022 ⏱ 1h 24m
- AWS for Developers: DynamoDB📅 December 20, 2022 ⏱ 1h 26m
- Develop Your AWS Skills📅 December 19, 2022 ⏱ 11h 54m
- AWS: Monitoring, Logging, and Remediation📅 December 19, 2022 ⏱ 1h 40m
- AWS: Deployment, Provisioning, and Automation📅 December 16, 2022 ⏱ 5h 24m
- AWS Essential Training for Developers📅 December 13, 2022 ⏱ 3h 16m
- Prepare for the AWS Certified Cloud Practitioner (CLF-C01) Certification Exam📅 December 6, 2022 ⏱ 3h 45m
- AWS Essential Training for Architects📅 December 6, 2022 ⏱ 5h 4m
- Introduction to Cloud Computing for IT Pros📅 November 22, 2022 ⏱ 1h 40m
- Learning Cloud Computing: Cloud Security📅 November 21, 2022 ⏱ 53m
- Cloud Computing: Private Cloud Platforms📅 November 21, 2022 ⏱ 1h 2m
- Cert Prep: Scrum Master📅 November 17, 2022 ⏱ 1h 26m
- Scrum: Advanced📅 November 16, 2022 ⏱ 1h 2m
- Presto Essentials: Data Science📅 November 16, 2022 ⏱ 1h 48m
- Advance Your Skills in the Hadoop/NoSQL Data Science Stack📅 November 15, 2022 ⏱ 12h 32m
- Analyzing Big Data with Hive📅 November 15, 2022 ⏱ 1h 53m
- Cassandra Data Modeling Essential Training📅 November 14, 2022 ⏱ 1h 38m
- Git Essential Training: The Basics📅 November 10, 2022 ⏱ 2h 55m
- NoSQL Data Modeling Essential Training📅 October 14, 2022 ⏱ 1h 20m
- Learning GitLab📅 October 14, 2022 ⏱ 1h 3m
- Planning and Releasing Software with Jira📅 October 14, 2022 ⏱ 1h 7m
- Continuous Integration Tools📅 October 14, 2022 ⏱ 1h 16m
- Hadoop for Data Science Tips, Tricks, and Techniques📅 October 13, 2022 ⏱ 1h 12m
- Hands-On Data Science📅 October 13, 2022 ⏱ 2h 43m
- R Data Science Code Challenges📅 October 12, 2022 ⏱ 44m
- Introduction to Spark SQL and DataFrames📅 October 12, 2022 ⏱ 1h 53m
- Docker Essential Training📅 October 9, 2022 ⏱ 1h 28m
- Getting Started with Cloud Development📅 September 17, 2022 ⏱ 7h 31m
- Apache Kafka Essential Training: Building Scalable Applications📅 September 17, 2022 ⏱ 1h 17m
- Azure: Understanding the Big Picture📅 September 17, 2022 ⏱ 3h 25m
- Learning Amazon Web Services (AWS) for Developers📅 September 16, 2022 ⏱ 1h 31m
- Choosing a Cloud Platform for Developers: AWS, Azure, and GCP📅 September 13, 2022 ⏱ 1h 7m
- Learning Cloud Computing: Public Cloud Platforms📅 September 12, 2022 ⏱ 1h 12m
- Learning Cloud Computing: Core Concepts📅 September 12, 2022 ⏱ 1h 32m
- Cloud Computing Careers and Certifications: First Steps📅 September 12, 2022 ⏱ 1h 31m
- Learning the AWS Well-Architected Framework📅 September 11, 2022 ⏱ 49m
- Advance Your Data Engineering Skills📅 September 11, 2022 ⏱ 24h 47m
- Advanced NoSQL for Data Science📅 September 11, 2022 ⏱ 1h 56m
- Cloud NoSQL for SQL Professionals📅 September 10, 2022 ⏱ 2h 39m
- Designing RESTful APIs📅 September 10, 2022 ⏱ 1h 20m
- HTTP Essential Training📅 September 10, 2022 ⏱ 50m
- Learning REST APIs📅 September 10, 2022 ⏱ 1h 6m
- SQL Tips and Tricks for Data Science📅 September 5, 2022 ⏱ 59m
- Architecting Big Data Applications: Real-Time Application Engineering📅 September 5, 2022 ⏱ 1h 4m
- Architecting Big Data Applications: Batch Mode Application Engineering📅 September 4, 2022 ⏱ 1h 37m
- Advance Your Data Skills in Apache Spark📅 August 14, 2022 ⏱ 17h 55m
- Spark for Machine Learning and AI📅 August 14, 2022 ⏱ 1h 51m
- Apache Spark Essential Training: Big Data Engineering📅 August 13, 2022 ⏱ 1h 2m
- NoSQL Essential Training📅 July 22, 2022 ⏱ 43m
- Data Science Foundations: Data Engineering📅 July 15, 2022 ⏱ 53m
- Apache Spark Deep Learning Essential Training📅 July 9, 2022 ⏱ 42m
- Apache PySpark by Example📅 July 9, 2022 ⏱ 1h 58m
- Amazon Web Services: Data Services📅 June 29, 2022 ⏱ 3h 11m
- Deploying Scalable Machine Learning for Data Science📅 May 29, 2022 ⏱ 1h 43m
- Machine Learning and AI Foundations: Decision Trees with SPSS📅 May 29, 2022 ⏱ 1h 16m
- Get Ahead in Data Science📅 May 28, 2022 ⏱ 12h 3m
- Blockchain Basics📅 May 28, 2022 ⏱ 1h 6m
- Smarter Cities: Using Data to Drive Urban Innovation📅 May 28, 2022 ⏱ 58m
- Open Data: Unleashing Hidden Value📅 May 28, 2022 ⏱ 1h 11m
- Learning Data Governance📅 May 27, 2022 ⏱ 1h 24m
- Learning Information Governance📅 May 27, 2022 ⏱ 1h 11m
- Building a Recommendation System with Python Machine Learning and AI📅 May 25, 2022 ⏱ 1h 38m
- Fundamentals of Dynamic Programming📅 May 24, 2022 ⏱ 1h 25m
- Data Science Foundations: Data Mining📅 May 22, 2022 ⏱ 4h 40m
- pandas Essential Training📅 May 16, 2022 ⏱ 2h 14m
- Cloud Hadoop: Scaling Apache Spark📅 May 15, 2022 ⏱ 3h 13m
- Apache Spark Essential Training📅 May 10, 2022 ⏱ 1h 27m
- HTML Essential Training📅 January 29, 2022 ⏱ 2h 45m
- Succeeding in Web Development: Full Stack and Front End📅 January 20, 2022 ⏱ 1h 3m
- Programming Foundations: Fundamentals📅 January 19, 2022 ⏱ 2h 10m
- Programming Foundations: Databases📅 January 19, 2022 ⏱ 1h 25m
- Agile Product Owner Role: Foundations📅 January 7, 2022 ⏱ 1h 7m
- Creating Interactive Presentations with Shiny and R📅 November 4, 2021 ⏱ 1h 53m
- Learning the R Tidyverse📅 November 2, 2021 ⏱ 3h 50m
- Advance Your Skills in Deep Learning and Neural Networks📅 October 31, 2021 ⏱ 15h 31m
- NLP with Python for Machine Learning Essential Training📅 October 31, 2021 ⏱ 4h 14m
- Neural Networks and Convolutional Neural Networks Essential Training📅 October 12, 2021 ⏱ 1h 19m
- Building and Deploying Deep Learning Applications with TensorFlow📅 October 12, 2021 ⏱ 1h 46m
- Deep Learning: Image Recognition📅 October 12, 2021 ⏱ 1h 43m
- Deep Learning: Face Recognition📅 October 6, 2021 ⏱ 1h 25m
- Building Deep Learning Applications with Keras 2.0📅 October 6, 2021 ⏱ 1h 24m
- Getting Started with AI and Machine Learning📅 October 5, 2021 ⏱ 17h 21m
- Artificial Intelligence for Cybersecurity📅 October 5, 2021 ⏱ 1h 15m
- Learning XAI: Explainable Artificial Intelligence📅 October 4, 2021 ⏱ 1h 14m
- Artificial Intelligence for Project Managers📅 October 4, 2021 ⏱ 41m
- Artificial Intelligence Foundations: Neural Networks📅 October 3, 2021 ⏱ 1h 16m
- Artificial Intelligence Foundations: Thinking Machines📅 September 28, 2021 ⏱ 1h 27m
- Artificial Intelligence Foundations: Machine Learning📅 September 27, 2021 ⏱ 1h 17m
- Getting Started with R for Data Science📅 September 26, 2021 ⏱ 28h 37m
- AI Accountability Essential Training📅 September 26, 2021 ⏱ 2h 21m
- R for Excel Users📅 September 25, 2021 ⏱ 1h 26m
- Social Network Analysis Using R📅 September 24, 2021 ⏱ 1h 6m
- R Essential Training: Wrangling and Visualizing Data📅 September 23, 2021 ⏱ 4h 18m
- Getting Started as an Agile Project Manager📅 September 22, 2021 ⏱ 10h 34m
- Agile at Work: Planning with Agile User Stories📅 September 21, 2021 ⏱ 51m
- RPA, AI, and Cognitive Tech for Leaders📅 September 19, 2021 ⏱ 53m
- Learning Industrial Automation📅 September 19, 2021 ⏱ 40m
- Code Clinic: R📅 September 16, 2021 ⏱ 1h 18m
- Learning R📅 September 15, 2021 ⏱ 2h 51m
- Digital Technologies Case Studies: AI, IOT, Robotics, Blockchain📅 September 14, 2021 ⏱ 43m
- RPA: Automation Anywhere IQ Bot📅 September 14, 2021 ⏱ 47m
🌐 About canaytore.github.io
This site is hosted on Github Pages (for free!) and powered by Jekyll (which is run on Ruby) using the Minimal Mistakes theme (which I tweaked a bit). Comments are hosted on Disqus, and automated e-mails for Newsletter are handled by Blogtrottr. Thanks to all this, I was able to host this small chunk of my brain on the Internet.
All blog posts are released under a Creative Commons Attribution-ShareAlike 4.0 International License.
All opinions and views are my own and do not represent my employer.