By the end of this introductory course, students will have acquired a comprehensive understanding of the core concepts and theories behind machine learning and artificial intelligence. They will learn how different algorithms enable computers to process and analyze data, essentially teaching them how computers "think" and make decisions. The course will also equip students with essential data handling skills, including how to collect, sort, and validate datasets, which are foundational to any machine learning project. Students will gain hands-on programming experience, learning to design simple programs using Scratch and Python that can sort and manipulate various types of data, such as images and text. One of the key outcomes is that students should be able to independently replicate the projects covered in the course, thereby solidifying their foundational knowledge and skills. This will enable them to think critically and logically about how to apply machine learning and AI technologies in different real-world scenarios.

As a college professor with over 10 years of experience in the data and technology fields, I bring a wealth of hands-on and academic knowledge to the classroom. My background is diverse, covering everything from data analytics and machine learning to software development. I've led teams in both academic and corporate settings to create innovative, real-world solutions.

What sets me apart is my experience teaching students of all ages. I've designed college courses that give students the practical skills they need to understand complex data, and I always make sure to stay updated with the latest industry trends. But it's not just college students who benefit from my teaching; I've also conducted workshops and educational programs for younger learners, making the fascinating world of data science and programming accessible to them.

I bring a balanced, well-rounded teaching approach to the table. I use real-world examples and interactive activities to make complex topics relatable and engaging for students, regardless of their age.

Homework Offered
There will be a small homework assignment to practice what we cover in each lesson.
0 - 1 hours per week outside of class
Assessments Offered
Feedback will be provided for all submissions, due to the complexity of the type of code will be working with, the goal is to recreate the projects in the class and expand them working with new and interesting types of data sets and conducting experiments. There will be a small homework assignment to practice what we cover in each lesson. the concepts that we cover in each class and feedback will be provided.
Grades Offered