AI 401: A.I. & Machine Learning
人工智慧與機器學習
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What is A.I., Machine Learning & Data Science:
Data Science is a field of study that collects, streamlines, prepares, and organizes both human and machine generated data. It aims to extract and understand the meaning of collected raw data. Companies of different sizes are constantly generate large amounts of data at any given second around the world, it is becoming an increasingly challenging task to keep track of all of this data. Data scientists analyze the data and create useful information for business operations, medical research, and mechanical automation. Data science is also the critical initial steps of Machine Learning (ML) to enable computers to function intelligently in a challenging, unguided environment. Machine Learning is a subsection of A.I. where large amount of data is used to produce sophisticate models a computer can adopt to solve various problems without explicit instruction from operators.
How are A.I., Machine Learning & Data Science used nowadays:
The adoption of modern technologies generate an increasing large number of data, from social networks, e-commerce activities, manufacturing facilities, and almost every enterprises and government. A.I. and Machine Learning are used not only to understand the behavior of these complex systems, but also to predict future critical events. The ability to predict future events mimic human intelligence. A.I. obtains this intelligence through the method of Machine Learning, similar to the way human being learns.
A.I. through Machine Learning enjoys explosive growth recently due to the advancement of computing power, cloud technology, and the large amount of data available. It has been recognized our society will advance into the next wave of technology driven by information extracted from data, and adoption of A.I. in every aspect of human activities.
A.I. 401 : A.I. & Machine Learning - the instructional plan:
What if your code could turn pictures of zebras into horses, tell the difference between dogs and cats, and beat world champions at car racing? Step aside sorcery, machine learning is here and it’s performing tasks people used to believe were only possible in fantasy worlds. Dive into this developing field using data sets, probability, statistics, and more. With tools like Python and Keras (which helps computers emulate the way a brain works) you’ll turn yesterday's dreams into reality.
Designed for ascending 8th ~ 12th graders with prior experience in Python programming, this advanced class will introduce our youth to the field of A.I. and Machine Learning. It will cover A.I. fundamentals starting from NumPy, Pandas, Pyplotlib, simple linear algebra and statistics concepts. Students will learn about several Deep Learning models & Artificial Neural Networks, and be challenged to build their own models & networks.
In this course, students will:
Upon completion of this class, students will be able to perform the following tasks confidently:
Prerequisites: Familiarity with fundamental Python knowledge such as variables, logical statement, loop, list, function, conditionals, and operators
人工智慧與大數據系列：A.I. 與機器學習
教學目標：實力鞏固 / For skills enhancement
學習難度：4 ~ 5 (5 最難，1 最易) / For advanced learners
適合年級：八年級以上(含), 需具備 A.I. 301 基礎 / For ascending 8th+ graders with prior knowledge in A.I. 301
總共課時：24 hrs. class length
附註說明：需自備手提電腦來上課 / Must bring own laptop computer to the class
Data Science is a field of study that collects, streamlines, prepares, and organizes both human and machine generated data. It aims to extract and understand the meaning of collected raw data. Companies of different sizes are constantly generate large amounts of data at any given second around the world, it is becoming an increasingly challenging task to keep track of all of this data. Data scientists analyze the data and create useful information for business operations, medical research, and mechanical automation. Data science is also the critical initial steps of Machine Learning (ML) to enable computers to function intelligently in a challenging, unguided environment. Machine Learning is a subsection of A.I. where large amount of data is used to produce sophisticate models a computer can adopt to solve various problems without explicit instruction from operators.
How are A.I., Machine Learning & Data Science used nowadays:
The adoption of modern technologies generate an increasing large number of data, from social networks, e-commerce activities, manufacturing facilities, and almost every enterprises and government. A.I. and Machine Learning are used not only to understand the behavior of these complex systems, but also to predict future critical events. The ability to predict future events mimic human intelligence. A.I. obtains this intelligence through the method of Machine Learning, similar to the way human being learns.
A.I. through Machine Learning enjoys explosive growth recently due to the advancement of computing power, cloud technology, and the large amount of data available. It has been recognized our society will advance into the next wave of technology driven by information extracted from data, and adoption of A.I. in every aspect of human activities.
A.I. 401 : A.I. & Machine Learning - the instructional plan:
What if your code could turn pictures of zebras into horses, tell the difference between dogs and cats, and beat world champions at car racing? Step aside sorcery, machine learning is here and it’s performing tasks people used to believe were only possible in fantasy worlds. Dive into this developing field using data sets, probability, statistics, and more. With tools like Python and Keras (which helps computers emulate the way a brain works) you’ll turn yesterday's dreams into reality.
Designed for ascending 8th ~ 12th graders with prior experience in Python programming, this advanced class will introduce our youth to the field of A.I. and Machine Learning. It will cover A.I. fundamentals starting from NumPy, Pandas, Pyplotlib, simple linear algebra and statistics concepts. Students will learn about several Deep Learning models & Artificial Neural Networks, and be challenged to build their own models & networks.
In this course, students will:
- Use Keras to create a neural network
- Explore machine learning with Python
- Train models to learn without being directly coded
- Develop coding and logical thinking skills
Upon completion of this class, students will be able to perform the following tasks confidently:
- Describe what a neural network is, what a deep learning model is, and the difference between them.
- Demonstrate an understanding of unsupervised deep learning models such as auto-encoders and restricted Boltzmann machines.
- Demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks.
- Build deep learning models and neural networks using the Keras library.
Prerequisites: Familiarity with fundamental Python knowledge such as variables, logical statement, loop, list, function, conditionals, and operators
人工智慧與大數據系列：A.I. 與機器學習
教學目標：實力鞏固 / For skills enhancement
學習難度：4 ~ 5 (5 最難，1 最易) / For advanced learners
適合年級：八年級以上(含), 需具備 A.I. 301 基礎 / For ascending 8th+ graders with prior knowledge in A.I. 301
總共課時：24 hrs. class length
附註說明：需自備手提電腦來上課 / Must bring own laptop computer to the class
