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Some points for a short interview about basis from programming to application.

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Interview Point

Java to Full Stack

Keyword

Language Java, JavaScript, HTML, CSS

Framework Spring, Spring boot, Spring MVC, Hibernate/Mybatis, JQuery, Vue.js/Angular.js

Software MySQL, MongoDB, Apache, Tomcat, Nginx, Node.js, Docker, Kubenetes

Basis

Select one or several concepts below and make an explanation with a demo in 30 minutes.

  • Java

    • Array, Vector, ArrayList, LinkedList, Map, Set
    • Abstract class, Interface
    • Inheritance, Encapsulation, Polymorphism
    • Deep copy, Shallow copy
    • Overload, Override
  • HTML 5 / CSS 3 / ECMAScript 6

    • HTML grammar
    • CSS grammar
    • Responsive design
    • var, let, const
    • Set, Map
    • Arrow (=>) function
    • Ajax
    • Promise
    • Module

Framework

Select one type and one or several concepts in the selected below with a demo and make an explanation in 30 minutes.

  • Backend

    • Spring, Spring boot
    • Spring MVC
    • Spring data JPA, Hibernate, Mybatis
    • junit
    • Shiro, Spring security
    • maven
  • Frontend

    • Node.js
    • Vue.js / Angular.js / React.js
    • Any UI Framework
    • Webpack
    • MVVM, MVC
  • Deployment

    • Docker
    • Kubernetes

Advance

Select one deliverable demo including at least frontend, backend and database below, and make a presentation in 30 minutes.

  • Blog
  • CMS
  • E-business
  • Forum
  • Hybrid mobile app

Python

Keyword

Language Python

Data Processing Library numpy, pandas, matplotlib, Python Imaging Library, opencv-python

Machine Learning Library scikit-learn, XGBoost, PyTorch, Tensorflow, Keras

Software Anaconda

Basis

Make an explanation of Python grammar with a demo in 30 minutes.

Library

Select one type and one or several concepts in the selected below with a demo and make an explanation in 30 minutes.

  • Anaconda
  • numpy, pandas, matplotlib
  • scikit-learning
  • Keras / PyTorch / tensorflow

Machine Learning Theory

Select one concept below with a demo and make an explanation in 30 minutes.

  • Classification / Clustering
  • Linear regression, Logistic regression
  • Support Vector Machine
  • Perceptron
  • K-Means, PCA
  • Anomaly Detection
  • Regularization
  • Overfitting

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