Skills

Statistics: 

• Descriptive Statistics: Mean, Mode, Median

• Variability: Standard Deviation, Variance, Range, Percentile, Quartile

• Correlation: Positive, Negative

• Probability Distribution

• Regression:Linear Regression, Logistic Regression

• Pie Chart, Bar Chart, Histogram  

Machine Learning: 

• Supervised Learning : Linear Regression, Logistic Regression, Decision Trees, K-Nearest Neighbors, Naive Bayes, Support Vector Machines, Random Forest

• Unsupervised Learning : K-means Clustering, Hierarchal Clustering, Apriori Algorithm, Neural Networks etc. 

Data Analysis Library (Python) :

• NumPy, Pandas

• Matplotlib, SciKit-Learn, Seaborn

Working Areas :

• Cardiovascular Disease Identification

• People Thoughts Prediction on Online Shopping

• Wheat Production Forecasting

• Insurance Purchase Behavior Prediction

Working Tools :

• Microsoft Excel, Google Colab, Jupyter Notebook 

Application Development (Android - Java & Kotlin) :

• Different types of components

• UI design with XML

• Different types of design layouts: Constrain Layout, Linear Layout, Relative Layout, Frame Layout etc.

• Database : Room SQLite, Shared Preference

• Implementation of Firebase database in Android System

• Networking library : Retrofit, Volley, Fast Android Networking

• Coding architecture pattern : MVVM (Model - View - View Model), MVP (Model - View - Presenter)

• Dependency Injection, APIs, Json

• RxJava, Coroutine, Live Data, Flow

• Google Map SDK & Google Map APIs

• Git, GitHub, GitLab

• Different types of third-party libraries

• Working Platform : Android Studio

• Working Areas : Data Collection and Analysis, Ride Sharing, E-commerce, Food Delivery, Appointment Management System

Web Design: 

• HTML

• CSS and Bootstrap

• Java Script (Basic)

Java and Kotlin :

• Fundamental programing skills

• Object Oriented Programing : Encapsulation, Abstraction, Inheritance, Polymorphism

• Android Application Development

C : 

• Fundamental programing skills

• Problem Solving and build some console based simple projects in university

Python : 

• Fundamental programing skills

• Data Analysis, Machine learning, Data Mining

Miscellaneous Languages: 

I have some basic skills about these programing languages and know some syntexts. I learn these languages in different courses of undergraduate level but don't have any application or professional experience with these language. If these need to learn in future I hope, I able to learn these languages very quickly. 

•  C++

• Assembly Language

• PHP

• Prolog

• Dart

• Java Script

Thesis Article and Documentation :

• LaTeX & Overleaf

• Microsoft Word

• Microsoft Excel

Video, Photo Editing and Presentation : 

• Camtasia Studio

• VideoScribe

• Microsoft Power Point

• Adobe Photoshop