Teachers Curriculum - The Fundamentals of Artificial Intelligence

Suitable for Educators Introducing AI in Classrooms

Teach Artificial Intelligence (AI) in your classrooms effortlessly using AIClub curriculums! We provide progressive curriculums with a wide range and depth. They include lesson guides, videos, presentation material, exercises and assessments, as well as online support. All the material is available online in your account!

This unit provides a gentle introduction to AI and can be taught by educators with varying backgrounds. It includes introduction to AI algorithms (a) K-Nearest neighbors (b) Linear Regression (c) K-Means clustering and (d) Neural Networks. 

Progressive Curriculum

Below are listed a subset of the huge array of curriculums provided by AIClub. You can also explore the corresponding book for them here

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Get Introduced to Artificial Intelligence and Machine Learning Algorithms 

Artificial Intelligence (AI) is how Google search, Alexa, Siri, auto-correct, speech translation, face recognition, self-driving cars, etc. learn from data and humans. Teach this course effortlessly using AIClub curriculums.

Why our curriculum?

• Designed by AI experts with PhDs in Computer Science!

• Only workshops where students build AIs in their first class! Students love building AIs and learning how they work!
 

We have no math or programming requirement. If they would like to code, they can do that also! 
Please see our brochure for more info about our programs!

Description 

Curriculum contains an introduction to artificial intelligence providing context how we are already using it in our daily life. It explains how AIs learn from data and the different sources from which data is acquired,.It also covers the topic of ethics around creation of AI in the real world and its impact on humans and environment around us. It includes introduction to different type of AI algorithms. It covers how the AI algorithms (a) K-Nearest neighbors (b) Linear Regression (c) K-Means clustering and (d) Neural Networks work internally. 

 

There is no math or programming pre-requisite to teach this class!
 

Topics Covered:
 

• Fundamentals of AI

  - Introduction to AI

  - Hierarchy of AI terms

  - Benefits and challenges of AI

  - AI vs Robotics

  - How is AI used in space

  - How is AI used in space

• How AI Learns

   - How does an AI learn

   - How AIs get built

   - Stages of AI lifecycle

   - AI and self-driving cars

   - Object detection system in a Tesla

• Data for AI

    - Sources of data

    - Data transformations

    - Statistics of data

    - Data visualization

    - Data storytelling

 • AI Ethics

    - AI Trust and Bias

    - AI and Privacy

    - Hands-on exercises

    - Discussion

Classification

    - Introduction to Classification

    - Introduction to Accuracy

    - Adult vs Child Exercise

    - Confusion Matrix

    - AI in Real Life - Detecting COVID with Smart Watches

 • Regression

    - Introduction too Regression

    - Regression Metrics

    - Averages Dataset

    - RMSE vs MAE

    - Exercise: Car Prices Dataset

    - Rules vs AI

    - AI in Real Life - Dynamic Pricing

K-Nearest Neighbors

   - Introduction to the KNN algorithm

   - Exercise - House Prices

   - Demo: KNN

   - AI in Real Life - Dynamic Pricing

Linear Regression

    - Linear regression

    - Averages Exercise

    - Recap RMSE vs MAE

    - Demo: Linear Regression

    - Product Exercise

    - Regression for Curves

    - Curve Exercise

    - Compare KNN and Linear Regression

 K-Means Clustering

    - Unsupervised learning

    - Introduction too Clustering

    - K-means clustering

    - AI in Real Life - Fraud Detection

Neural Network

    - How to think about images

    - Introduction to Deep Learning - MLP

    - Flattening images

    - Introduction to MNIST dataset

    - Train MLP with flattened images

    - Parameters of MLP

    - Exercise - Hyper-parameter tuning in MLP

    - Train directly with color images

 Python Concepts

    - Data-types and input/output

    - Loops and conditionals

    - Lists

      - Try/Catch

    - Modules - Pandas

    - Scikit-learn

    - Data-types and input/output

    - Loops and conditionals

    - Lists

    - Modules - Pandas

    - Scikit-learn

 Python Exercises

    - Read tabular data

    - Read text data

    - Read audio data

    - Read image data

    - Data Visualization

    - Accuracy with binary classification

    - Accuracy with multi-class classification

    - Confusion matrix with binary classification

    - Confusion matrix with multi-class classification

    - Mean Absolute Error

    - Root Mean Square Error

    - K-nearest neighbors classification

    - K-nearest neighbors regression

    - Linear Regression

    - K-means clustering

    - Convert a color image to grayscale

    - Resize an image

    - Flatten a grayscale image

    - MNIST and MLP

What teachers take away

• A good understanding of specific AI algorithms - K-nearest neighbors, linear regression, K-means clustering, neural networks.

• Everything they need to teach AI in a classroom.

What students have accomplished after using these curriculums!

Purchase

Purchasing this curriculum will give you access to all the materials such as slides, videos, teachers guides, discussions, assessments etc needed to teach this course in your classroom.

 
 

Introducing the AIClub Textbook ! 

Artificial Intelligence is all around us. For Middle School and High School students, AI is an opportunity to build critical future skills. Learn how to apply technology to solve real-world problems in varied disciplines from medicine to social good. Develop independent opinions about these technologies and how they affect human lives. This textbook covers the fundamentals of AI at a level of math and coding that matches middle school and high school capabilities.

Purchase your own AIClub textbook from the link below!

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Supriya Bhuwalka, Educator India

Working with AIClub’s educator program to launch my own AI Classes was a great experience. The material energizes students: they are excited to learn more and want to build real world solutions using AI. The AIClub team was very helpful throughout the pilot process. I am expanding my education practice and launching AI classes with the help of AIClub!

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Education Programs,

Mission Bit

The AIClub workshop was a great introduction to artificial intelligence. I could see that the students understood the current real world applications of it and were excited about developments in the future.

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Instructor, Silicon Valley Continuing Technical Education

My 11th and 12th grade students at Silicon Valley Career Technical Education enjoyed learning AI from AIClub's High School Programs. It was a valuable experience to help them prepare for future careers. The AIClub's High School curriculum has the depth to engage students as well as an easy to use web interface. It is a Program that any Computer Science or STEAM teacher could use to teach AI.