Self Development, Continuous Learning and Skills Acquisition

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Tech Stack : Tools, Languages, Libraries

Skill	Tech Stack
Programming	Python, Pandas, Numpy, Scikit-Learn, C++ Pytorch, Pytorch Lightning, OpenCV, Tensorflow, Keras
Visualization, Dashboards & Reporting	Pandas, Matplotlib, Seaborn, Plotly Power BI, Tableau Excel/Google Sheet Charts, Google Slides, Canva
Data and Database Management	PostgreSQL, SQLAlchemy, Dbeaver , Pipelines, ETL
Version Control	Git, Github, Gitlab
Ingestion, Processing and Orchestration	Pyspark (beginner) , Apache NiFi (beginner) , Apache Airflow (beginner)
Containerization (beginner)	Docker (beginner) , Kubernetes (beginner)
Organization	Kanban Board, Trello, Jira, Zenhub
OS - Shell	Linux, Unix, Windows
Editors (IDE)	VSCode, Visual Studio, Jupyter
Dashboards & Web Dev (beginner)	Streamlit (beginner), HTML (beginner), CSS (beginner), Flask (beginner)
Scraping	APIs, ...
Cloud (beginner)	IBM Cloud (beginner), ...

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Current Training/Learning Focus:

• Coursera Certification:
  • Google Data Analytics Professional Certificate (Ongoing)

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Certificates, Seminars, Workshops

Completed

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• DataTrain/UBremen Research Alliance:

  • Operator Track: Data Scientist

  A cross-discipline training program in “Data Train–Training in Research Data Management and
  Data Science” for doctoral researchers from member institutions of the cooperation network
  “U Bremen Research Alliance” teaches competencies in data literacy, research data management
  and data science. The program is associated with consortia of the German National Research Data
  Infrastructure (NFDI) initiative.
  
  In the Operator Track Data Scientist methods from mathematics, statistics, artificial intelligence
  and computer science for data analysis and further data science competencies are conveyed.
  
  #IndustrialMathematics # DataManagement #Research #Datascience #DataAnalysis #ETL #Python #Pytorch
  #DeepLearning #MachineLearning #WeightsandBiases #Optimisation #OptimalControl #ParameterEstimation
  #ImageProcessing #ComputerVision #ModelInterpretability #DataEthics
  

  • A preview of certificate
  
  

• Coursera Certification:

  • DevOps, Cloud, and Agile Foundations Specialization (IBM)

  As an actively curious and continuous learner, I decided to take a foundational course on DevOps,
  Cloud Computing, Agile, and Scrum foundational specialization.
  The purpose for me as a data analytical engineer was to re-introduce myself to core concepts on
  agile software development and  gain new skills as well that could be used to bring about actionable impact
  on businesses, introduce oneself to current best practices as a practitioner, get introduced to the benefits
  of cloud computing, emerging technologies and the cloud services usage. 
   
  #AgileSoftwareDevelopment #AgileMindset #Devops  #Zenhub #Scrum #CICD #CloudComputing
  

• Others

  • Udemy Certification: Learn Basic to Advance JIRA for Testers/QA/Test Manager-2022.

  • Forage Virtual Internship: Goldman Sachs Excel Skills for Business Virtual Experience Program

  • Forage Virtual Internship Certification: Standard Bank Data Science Virtual Experience Internship.

  • Forage Virtual Internship Certification: Accenture Data Analytics and Visualization Virtual Experience.

  • Coursera Certification: Mathematics for Machine Learning: Linear Algebra.

  • Coursera Certification: Bayesian Statistics: From Concept to Data Analysis(with Honors).

  • Coursera Certification: Machine Learning: Regression.

  • Coursera Certification: Neural Networks and Deep Learning.

  • Coursera Certification: Machine Learning with Python.

• Course projects and Seminars:

  • Final Project : Applications of Neural Network Models in Kaggle Competition: Malaria Dataset and Kvasir Endoscopic Images dataset, Ivan Franko National University of Lviv, Ukraine.

  • Course Project Seminar: Applications of Neural Network Models in Kaggle Competition: Digit Recognizer, Ivan Franko National University of Lviv, Ukraine.

  • Data Analytics - Predictive Monitoring and Optimization of Transport And Logistic Processes: Cargo 2000 as Case Study, University of L’Aquila, Italy.

  • Big Data Models and Algorithms - Dimensionality Reduction, University of L’Aquila, Italy.

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Learned Skills

• Fields:
  • Applied Mathematics,
  • Predictive Modelling,
  • Data-Driven Decision Making,
  • Data Extraction,
  • Data Cleaning,
  • Data Modelling,
  • Data Analysis,
  • Data Wrangling,
  • Data Engineering,
  • Data Visualization,
  • Machine Learning,
  • Deep Learning,
  • Computer Vision,
  • Statistical Analysis,
  • Business Intelligence.

• Soft Skills:
  • Research,
  • Problem Solving,
  • Agile Project Management,
  • Agile Mindset
  • Critical Thinking,
  • Communication,
  • Teamwork.

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Learning Platforms

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Coursera

School/Univerisity Training , Seminars and Workshops e,g. DataTrain/Ubremen Research Alliance

Forage

Udemy

Linkedin Learning

Microsoft Learn

-etc