Beginner Friendly Intro to AI Course (Part 1)

Beginner Friendly Intro to AI Course (Part 1), available at Free, has an average rating of 2.25, with 25 lectures, based on 2 reviews, and has 286 subscribers.

You will learn about Basics of AI, including applications, misconceptions, branches, history, and ethics Basics of python, including variables, loops, data structures, and basic algorithms Basics of libraries, including pandas, numpy, and matplotlib Basics of ML, including supervised, unsupervised, reinforcement learning, regression and classification, and various ML models/algorithms Basics of Computer Vision, including neural networks, convoluted neural networks, deep learning, and transfer learning This course is ideal for individuals who are This course is meant for high schoolers and ambitious middle schoolers who are interested in learning more about AI and making an impact. It is particularly useful for This course is meant for high schoolers and ambitious middle schoolers who are interested in learning more about AI and making an impact.

Enroll now: Beginner Friendly Intro to AI Course (Part 1)

Summary

Title: Beginner Friendly Intro to AI Course (Part 1)

Price: Free

Average Rating: 2.25

Number of Lectures: 25

Number of Published Lectures: 25

Number of Curriculum Items: 25

Number of Published Curriculum Objects: 25

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Basics of AI, including applications, misconceptions, branches, history, and ethics

Basics of python, including variables, loops, data structures, and basic algorithms

Basics of libraries, including pandas, numpy, and matplotlib

Basics of ML, including supervised, unsupervised, reinforcement learning, regression and classification, and various ML models/algorithms

Basics of Computer Vision, including neural networks, convoluted neural networks, deep learning, and transfer learning

Who Should Attend

This course is meant for high schoolers and ambitious middle schoolers who are interested in learning more about AI and making an impact.

Target Audiences

This course is meant for high schoolers and ambitious middle schoolers who are interested in learning more about AI and making an impact.

*This course is meant for purchase by an adult over 18*

Targeted towards high schoolers, this course covers the basics of AI, including its applications, misconceptions, branches, history, and ethics. The student will learn Python programming essentials, such as variables, loops, data structures, and basic algorithms, along with key Python libraries like pandas, numpy, and matplotlib. Moreover, the course introduces machine learning concepts, including supervised, unsupervised, and reinforcement learning, as well as regression, classification, and various ML models and algorithms. The student will also delve into computer vision, exploring neural networks, convolutional neural networks (CNNs), deep learning, and transfer learning.

This course is designed to be engaging and easy to understand, making complex topics accessible for high school students. Each topic is explained with simple examples and hands-on activities to apply what you learn. By the end of the course, the student will have a solid foundation in AI and Python programming, enabling the student to tackle real-world problems using technology.

Whether the student is interested in using AI for health, education, or any other field, this course will give them the tools and knowledge they need to start their journey.  Enroll in this course to build a strong foundation in AI, and acquire the skills and knowledge to create impact in this special field!

Course Curriculum

Chapter 1: Introduction to AI

Lecture 1: What is AI? (1)

Lecture 2: Boston Dynamics Video

Lecture 3: What is AI? (2)

Lecture 4: Branches of AI (1)

Lecture 5: Tonight Show Video

Lecture 6: Branches of AI (2)

Lecture 7: History of AI

Lecture 8: AI Bias and Ethics (1)

Lecture 9: Algorithmic Bias and Fairness: Crash Course AI Video

Lecture 10: AI Bias and Ethics (2)

Lecture 11: AI Dangers Ted Talk

Lecture 12: AI Bias and Ethics (3)

Chapter 2: Introduction to Python

Lecture 1: Intro to Python (1)

Lecture 2: Colab Tutorial For Beginners Video

Lecture 3: Intro to Python (2)

Lecture 4: Printing and Variables

Lecture 5: Conditionals

Lecture 6: Loops

Lecture 7: Functions

Lecture 8: Lists

Lecture 9: (Optional) Sorting

Lecture 10: Dictionaries

Chapter 3: Introduction to Libraries

Lecture 1: Intro to Libraries

Lecture 2: Intro to Pandas

Lecture 3: Great Job!

Instructors

Nidhi Parthasarathy
Instructor at Udemy

Rating Distribution

1 stars: 1 votes

2 stars: 0 votes

3 stars: 1 votes

4 stars: 0 votes

5 stars: 0 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!