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JetBrains Academy for Organizations - 2023年4月期リリース
Java、Python、Kotlinの36の新しい教育トピックと10の新しいプロジェクトを追加
4月 11, 2023
新バージョン
機能
Java
Project: Traffic Light (Beta) - In this project, you'll have the opportunity to create a simplified version of your own traffic light and learn a variety of new skills in the process. By the end of the project, you'll be able to work with multi-threading, handle exceptions, inherit classes, and use the circular queue data structure.
Project: Hospital Appointment Booking System (Beta) - In this project, you'll learn how to build REST services with Spring Boot and work with databases, JSON, and REST API basics. Using your newfound skills, you'll develop an appointment system based on a REST API that will improve the management of hospitals. Patients can easily schedule appointments, the head physician can monitor doctors' workloads, and doctors can better plan their days.
Project: Password Hacker (Beta) - Through this project, you'll learn about the key tools and techniques used in hacking, including iterators, generators, and the itertools module in Java. You'll also develop a client app and connect to a server using the socket module, all while gaining a deeper understanding of JSON and the time module.
The Meal Planner project has been released from Beta.
Topics:
Code organization: Thread-safe singleton.
Spring Boot: Custom queries with @Query, Testing repositories.
Python
Project: Jeopardy! Question Answering Bot (Beta) - Learn how to use sentence-embedding algorithms to separate user questions, and gain insights into preparing a corpus for creating a Q&A system.
Project: Marathon Runners (Beta) - In this project, you'll use basic Python tools to code the KNN algorithm from scratch and solve classification problems. You'll learn about basic data types, practice using Python functions, and get an introduction to object-oriented programming. Additionally, you'll learn how to prepare and normalize data before feeding it into a machine learning algorithm.
Project: Learning Progress Tracker (Beta) - Build an education platform to manage registrations, track learning progress, and provide detailed information for users and categories. You'll practice using loops, flow controls, functional decomposition, and SOLID principles. Learn how to process strings and leverage the unit test framework to ensure error-free code. Suitable collections such as lists will be used to sort and filter data.
The projects Simple Text Summarization, Sorting Tool, and Video Game Database have been released from Beta, with improved features and functionality for learners.
Flask
Project: Movie Database API (Beta) - Using a movie database, you'll learn how to use SQLAlchemy to design and implement database table mappings, insert and retrieve data, and filter data by building SQL queries. You'll also gain valuable experience in implementing data models and relations in a database schema.
The Memorization Tool has been released from Beta.
Frontend
Project: URL Shortener (Beta) - In this project, you will create a web page to shorten website URLs using HTML and JavaScript. You will also practice manipulating the Document Object Model (DOM) to take input from the user and display the results dynamically. This is a great opportunity to apply your HTML and JavaScript skills in a practical setting and gain hands-on experience with web development.
Project: Dog Glossary (Beta) - Create your web page to display random dog pictures and a list of dog breeds using a public API. This project will help you practice handling APIs and improve your HTML and JavaScript skills. Through fetching data from an API and displaying it on the web page, you'll learn how to work with promises and handle different data structures.
Topics:
CSS: Grid gaps, Introduction to Grid.
JavaScript: Local Storage.
Node.js: Working with filesystem, Creation of HTTP server, Querystring module, What is module?
Data science
Machine learning project: Naive Bayes Classifier with Pen and Paper (Beta) - In this project, you'll gain insight into the process of converting words into numerical data and discover the inner workings of the Naive Bayes classifier. Through working on a simple dataset, you'll develop familiarity with solving classification problems. You'll also learn about language identification, a crucial task in natural language processing, and discover how to create a basic classifier with only a pen and paper.
The Generating Randomness and Linear Regression from Scratch projects are now out of Beta.
Topics:
Tools: K-Means in sklearn.
Machine learning: Basics of neural network architecture, MAE, Introduction to Question Answering.