AIU Bootcamp Artificial Intelligence and Data Science

The AIU Bootcamp an Artificial Intelligence and Data Science track, allowing you to focus on courses to help develop a deeper understanding of data science and artificial intelligence. The Artificial Intelligence and Data Science track will provide a strong skill set in data cleaning, data analysis, data management, statistical inference, data visualization, data mining, and machine learning algorithms.

ReactJS / Angular

Facebook ReactJS is a GUI Library based on JavaScript and ECMA Script. It is arguably the most popular GUI Library of JavaScript since 2013. Google Angular is the most complete GUI Framework since 2016. The course will discuss the following subjects of ReactJS: HTML, CSS, JavaScript, Typescript online coding, ECMA, JSX/Babel components, React props/state/class/refs/memo/fragment components, React functional component, parent/child components, data communication, HOC, Hooks, Redux Data Center between components, HTTP Axios and Ajax libraries, Middleware framework logger, thunk for production optimizations.

Python, OpenCV, and Django

In this course, students will work on a project using Python, OpenCV, and Django/ReactJS. OpenCV is C++ Parallel Programming libraries for Image Processing and Deep Learning. Django is most popular server framework for Frontend React/Angular and Backend Python/Data Science/Machine Learning. This course will be divided into three parts:
Part 1: Python Programming.
Part 2: Python/OpenCV.
Part 3: Integrate frontend to the Backend.

Data Science Using Python

This course will use the Python programming language for Data Analysis and Visualization. There will be a practical introduction to the Python programming language syntax and data structures. This course is divided into three parts.
Part 1: ETL (Extract, Transform, and Load) and Data Preparation.
Part 2: Data Analysis and Visualization.
Part 3: Predictive Model and Project Study.

Machine Learning Using Python

This course introduces the fundamentals of Machine Learning using the Python programming language. There will be a practical introduction to the Python programming language syntax and data structures. This course is divided into five parts.
Part 1: Supervised Vs. Unsupervised Learning.
Part 2: Recommender or Recommendation System.
Part 3: Data Mining and Data Handling.
Part 4: Big Data.
Part 5: Experimental Design.

Deep Learning

Deep Learning technique is a subset of Machine Learning in artificial intelligence, influenced by the way a human thinks and learns. This course covers the fundamental methods of Deep Learning or Artificial Neural Networking, using TensorFlow and PyTorch. TensorFlow is an open source Deep Learning library developed by Google. PyTorch is an open source Machine Learning library developed by Facebook’s AI Research Lab.