AOE Computer Programming Courses

 

 

Level 1: Python Programming for Beginners (above 12 years old):

 

This course is primarily aimed at giving students aged 12 and older valuable insight into the Python programming language and its real world applications.   The course will first teach the basics of the Python programming language syntax (e.g. Python keywords, variable declarations).  The course will then move into more complicated topics such as logical operators, string operations, function declarations, and loops.  Finally, the course will cover advanced concepts such as list comprehensions, data structures, file I/O and class design--aspects of Python that are essential in a real world software development context.

 

To register this course, please click here

Level 2: Data Science and Big Data Analysis (above 14 years old):

 

Data science is a large field covering everything from data collection, cleaning, standardization, analysis, visualization and reporting. It offers a powerful approach to making discoveries. By uniting aspects of computer science, statistics, and visualization, Data Science can turn the vast amounts of data generated by digital age into new knowledge. This course cover the following concrete components which are powerful and standard Python tools for data science: data exploration & analysis tools including Pandas; NumPy; SciPy; data visualization tool Matplotlib. Data manipulation and visualization are thoroughly discussed. Real world data science examples are analyzed and python code to solve these problems are provided step by step

 

To register this course, please click here

 

Level 3: AI and Machine Learning (above 14 years old):

 

This course introduces what is Machine Learning and its purpose. It presents several scenarios of how it applies to the real world. The students get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. The course will first start by introducing familiar concepts such as linear regression in one and multiple variables from a machine learning perspective as well as the linear algebra that will be necessary to understanding those concepts.  The course will then move on and introduce regression, classification, clustering and data vectorization.  Finally, the course will focus on neural networks, their representation, and applications in tasks such as image recognition and natural language processing.  Python and its libraries such as scikit-learn are used in this course.

 

To register this course, please click here

Course Schedule: 

  • Level 1: 1/20/2019 ~4/7/2019 (Sundays), 15:30 ~17:00  

  • Level 2: 1/19/2019 ~4/6/2019 (Saturdays), 16:00 ~17:30  

  • Level 3: 1/19/2019 ~ 4/6/2019 (Saturdays), 18:30 ~20:00

 Location: 100 Park Avenue, #108 Rockville MD 20850

 

Tuition: $485 (including $35 non-refundable registration fee)

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