AI & Machine Learning | EVComputing

AI & Machine Learning

Artificial intelligence (AI) is a field of computer science where machines think, work, and react like humans. Examples of AI include Google Home and Amazon Echo.

Machine learning (ML) is a sub-field of AI where computers use data to improve their performance from experience on their own, without being programmed. For example, Siri recognizes patterns in your questions over time and how you ask them and learns to deliver more customized answers.

AI and ML are already impacting how we live, work and play in ways we are sometimes not even aware of. It is the future. The exciting world of AI & Machine Learning is explored at EVComputing in two ways:

AI & ML Course:
- Explores data analysis, visualization and ML algorithms of the students’ choice
- Projects include sentiment analysis and recommender systems
- Suitable for middle school and up
- For students who have completed three levels of Python
- Offered year round in weekly classes
- Two-three 12-week sessions

AI & ML Workshop:
- Introduces students to AI and ML
- Teaches students how to make the computer self-learning and smarter
- Hands-on, interactive Scratch projects
- Suitable for 5th-7th grades
- Usually offered during school breaks, such as Spring Break and Thanksgiving
- 3-6 hours long

Description of the Workshop and Course

AI & ML Workshop

Prerequisites: Familiar with using a browser, basic keyboarding skills, ability to follow instructions in guided tutorials, basic algebra, and a lot of imagination.

Objective: Starting with guided tutorials, students learn how to create and collect data such as text or images, train the computer to recognize them, and explore how to make the computer better at learning. Students gain an understanding of concepts such as supervised learning, image classification, text classification, biometrics, predictive model, training bias, and Natural Language Processing.

Projects: Projects include unlocking the phone with face (image) recognition, handwriting recognition and teaching the computer to make recommendations (food, movies, etc.).

Duration: 3-6 hours over 1-3 days.

Grade Level: Suitable for 5th-7th grades.

AI & ML Course

Prerequisites: Beginner and Advanced Levels I, II of Python

Objective: Students explore data analysis libraries such as NumPy and pandas using Anaconda. They learn data visualization with Matplotlib/Seaborn for datasets that the students can relate to. Students also dive into machine learning with concepts of linear regression, decision trees, recommender systems. AI topics such as NLP and chatbots are also covered.

Projects: There will be quizzes and open-ended mini-projects to provide structure and direction.

Duration: Students can expect to work on this course for 2-3 sessions (each 12 weeks long). The course series is roughly divided into three levels, but the actual content of each level is customized based on the student’s interests and time available for homework.

Grade Level: Middle and early high school, but the course series is suitable for all students who have an existing interest in the topic, are self-motivated and tend to take charge of their learning — the kind who when coding find it hard to switch off the computer and go to sleep.

FAQ

How are the AI & ML Workshop and the AI & ML Course different?

The AI & ML workshop has no programming requisites. The workshop’s emphasis is on providing a gentle introduction to AI & ML, and the language used is Scratch. The workshop is about 3-6 hours long, over 2-3 days.

On the other hand, the AI & ML Python course requires the student to be comfortable writing Python programs of medium complexity (using lists, dictionaries, file I/O, lambdas, map and filter methods). The student can expect to spend 2-3 sessions (each session is 12 one-hour weekly classes) on the AI & ML Python track. More information about this track can be found here.

Should the student have learned Python at EVComputing only?

Students who have Python knowledge that they believe is the equivalent of the Python Advanced Level II of EVComputing can contact us by email. They can share samples of their Python work or attempt some of the EVComputing Advanced Level II exercise assignments.