Course Overview
Course Goals:
Students will learn the basics of python programming and additional prerequisites relating to AI understanding, going from writing their first line of python code to creating a small data analysis final project. Students will become familiar with important python packages: numpy, pandas, plotly, and sklearn. Students will learn how to operate python code through Colab Notebooks. Students will gain understanding in math and logic topics that are crucial for AI and machine learning (ML) understanding.
- Students will be able to enroll in Aiphabet’s online course, having the prerequisite coding and math background.
- No coding experience is required. Basic understanding of graphing and algebra is expected.
Course Format:
The class will be held in a lecture and discussion format. In lecture, concepts will be explained in an interactive way with relevant examples and real-world applications. In discussion, students will be given practice problems that they can solve and ask questions on. There will also be additional seminars on fundamental topics for understanding AI and ML.
Course Logistics:
- The class will be held from June 23th - July 31st. There will be four sessions a week on Monday to Thursday from 6:00 - 7:00 PM EST.
- Students are encouraged to attend all sessions. However, materials will be posted online if a student misses a section.
Course Outline:
- Unit 1: “Hello World”
- Unit 2: Variables, Operators and Conditionals
- Unit 3: Lists
- Unit 4: Loops
- Unit 5: Functions
- Unit 6: Numpy
- Unit 7: Pandas
- Unit 8: Graphing
- Unit 9: ML Basics
- Final Project
Final Project:
- Students will conduct an open ended data analysis and prediction on a dataset of their choosing. The goal of the project is for students to create a project that they can show on a future resume. The project will be introduced to students on the second to last week of class and workshop sessions will be held on the last week. Students are allowed to work in groups if they’d like.