Python 301: A.I. & Machine Learning ~ A Competition Approach
探索高科技：A.I. 專家養成+科技競賽準備班
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Python 301: Python for Artificial intelligence and Machine Learning -- A competition approach
One of the purposes of learning Python is to explore the world of A.I. and Data Science. In the academy landscape, there are quite a few opportunities to compete in A.I. in order to gain industrial aspect, and to be noticed and recognized. We design this 10-week program not only to teach the basic skills in developing A.I. solutions, but also to show students ways of applying the learning experience in real world competition such as Kaggle Competition. Kaggle is the most renowned A.I. event sponsored by Google. Many of its participants have become the cornerstones of modern A.I. revolution.
The instructional plan is designed as:
1. Math for Machine Learning ~ Linear Algebra and Statistic: Class materials are designed to be absorbed by high school and advanced middle school students. Our students are not expected to have prior experience in similar coursework. We will cover all the basics, enough for working with programming tools to solve A.I. challenges.
2. Python for Machine Learning ~ Numpy, Scipy and visualization package: Once acquired basic understanding of Linear Algebra and Static concept and terminology, students will be able to learn Numpy and Scipy for numerical processing of large dataset, and visualize the information extracted from data using various plotting packages.
3. Machine Learning Model, Supervised and Unsupervised Learning, Re-enforcement Learning and Classification.
4. Popular Python Machine Learning frameworks.
5. Execution of simple machine learning projects in image processing and natural language understanding.
6. Preparation for Kaggle Competition, topic selection, dataset acquisition, and data preparation.
We strongly recommend all students to stay active and proactive while learning this subject, and possessing team spirits. The competition is always a teamwork involving students with diverse interest and career track. Students will be encouraged to choose their own track of interest when deciding on their roles in the competition team, either being the team captain, the technical researcher, the marketer, the communicator, or the business executive. Our instructional goal is to prepare students for participation in this competitive event under the guidance of our mentors.
Prerequisites: Python 201 (or equivalent background)
人工智能專家養成：競賽準備班
教學目標：實力鞏固、競賽準備
學習難易度：4 ~ 5 (5 最難，1 最易)
適合年級：7~12 年級，需具備 Python 201 基礎。學生需自備手提電腦來上課
One of the purposes of learning Python is to explore the world of A.I. and Data Science. In the academy landscape, there are quite a few opportunities to compete in A.I. in order to gain industrial aspect, and to be noticed and recognized. We design this 10-week program not only to teach the basic skills in developing A.I. solutions, but also to show students ways of applying the learning experience in real world competition such as Kaggle Competition. Kaggle is the most renowned A.I. event sponsored by Google. Many of its participants have become the cornerstones of modern A.I. revolution.
The instructional plan is designed as:
1. Math for Machine Learning ~ Linear Algebra and Statistic: Class materials are designed to be absorbed by high school and advanced middle school students. Our students are not expected to have prior experience in similar coursework. We will cover all the basics, enough for working with programming tools to solve A.I. challenges.
2. Python for Machine Learning ~ Numpy, Scipy and visualization package: Once acquired basic understanding of Linear Algebra and Static concept and terminology, students will be able to learn Numpy and Scipy for numerical processing of large dataset, and visualize the information extracted from data using various plotting packages.
3. Machine Learning Model, Supervised and Unsupervised Learning, Re-enforcement Learning and Classification.
4. Popular Python Machine Learning frameworks.
5. Execution of simple machine learning projects in image processing and natural language understanding.
6. Preparation for Kaggle Competition, topic selection, dataset acquisition, and data preparation.
We strongly recommend all students to stay active and proactive while learning this subject, and possessing team spirits. The competition is always a teamwork involving students with diverse interest and career track. Students will be encouraged to choose their own track of interest when deciding on their roles in the competition team, either being the team captain, the technical researcher, the marketer, the communicator, or the business executive. Our instructional goal is to prepare students for participation in this competitive event under the guidance of our mentors.
Prerequisites: Python 201 (or equivalent background)
人工智能專家養成：競賽準備班
教學目標：實力鞏固、競賽準備
學習難易度：4 ~ 5 (5 最難，1 最易)
適合年級：7~12 年級，需具備 Python 201 基礎。學生需自備手提電腦來上課
