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CY302
Online Advanced Artificial Intelligence Course for Kids - CodingYoung.com
COMPLETED CY301

Course Description

Artificial Intelligence is a newly developing field that is gaining traction every year. It is used to create scripts and robots that are self-learning which reduces the need for human input. The goal is to make the process efficient and less time consuming so that once the script is coded, the program learns and adapts on its own. Companies like YouTube, for example, use machine learning to detect copyright violations in the billions of hours of content that is uploaded every day on its servers. Tesla is also using machine learning to advance its self-driving systems at an incredible pace. In the near future, Artificial Intelligence will probably have the most demand in the job market as the race to automation gets heated.

This course is meant to help your kids explore artificial intelligence so that they can figure out if it is something they might be interested in pursuing. It is meant for older kids having a solid understanding of Python as it will be required to code scripts that perform Artificial Intelligence. A strong foundation in algebra and a basic understanding of statistics are also pre-requisites. The curriculum further covers training of models using Supervised Learning which involves parametric/non-parametric algorithms and neural networks for machine learning scripts. Unsupervised learning on the other hand will teach them clustering and dimension reduction, reinforcement learning along with various classification and regression techniques, decision trees etc. Students will also learn about python’s data analysis library- pandas including tools like numpy, plotly and tableau to be able to apply algorithms to build models with text, audio understanding capabilities, database mining and in other areas.

Artificial Intelligence is going to soon mature into a mainstream field and if your child starts to learn about it now then they will gain enough competitive edge. When computer programming turned into a mainstream field, those who began learning it early got hired in tech startups without much difficulty. Eventually, the stock compensation in companies such as Facebook and Amazon ballooned while they got promoted with experience and in this process, created an incredible fortune just because they were in the right place at the right time. Machine learning and artificial intelligence are powering the 4th industrial revolution and impacting the future of every industry and every human being. Companies such as NASA are always on a look out for young, curious minds to fill their ranks with and our curriculum can steer the future of your kid in that direction.

Course Curriculum

Learning Algorithms:
right-icon K-Means
right-icon Adaboost
right-icon Decision Trees

 

Support Vector Machines:
right-icon Implement an SVM classifier in SKLearn/sci-kit-learn

 

Supervised Machine Learning:
right-icon Regression & Classification
right-icon Linear Regression 
right-icon Support Vector Regression 
right-icon Random Forest Regression 
right-icon Logistic Regression
right-icon XGBoost Regression
right-icon XGBoost Classification
right-icon Random Forest Classification
right-icon Support Vector Classification

 

Unsupervised Machine Learning:
right-icon Clustering
right-icon K-Means Clustering: Inertia, Dunn Index, Cluster Tendency
right-icon Hierarchical Clustering: Linkages, Dendograms, Cluster Analysis, Means & Centroid.

 

Modeling-(choose the best prediction model based on their accuracy)
right-icon Resampling, Cross-Validation, Probabilistic Measures, Hyperparameter Tuning

Learning Algorithms:
right-icon K-Means
right-icon Adaboost
right-icon Decision Trees

 

Support Vector Machines:
right-icon Implement an SVM classifier in SKLearn/sci-kit-learn

 

Supervised Machine Learning:  
right-icon Regression & Classification right-icon XGBoost Regression
right-icon Linear Regression  right-icon XGBoost Classification
right-icon Support Vector Regression  right-icon Random Forest Classification
right-icon Random Forest Regression  right-icon Support Vector Classification
right-icon Logistic Regression  

 

Unsupervised Machine Learning:
right-icon Clustering
right-icon K-Means Clustering: Inertia, Dunn Index, Cluster Tendency
right-icon Hierarchical Clustering: Linkages, Dendograms, Cluster Analysis, Means & Centroid.

 

Modeling-(choose the best prediction model based on their accuracy)
right-icon Resampling, Cross-Validation, Probabilistic Measures, Hyperparameter Tuning

 

Choosing the Curriculum that's right for you

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Choose Curriculum

Our academic advisor will help students enroll into various levels and topics based on their age, grade, prior exposure to programming, availability and goals.

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Completion Speed

Speed at which students will complete each topic depends on their level of commitment, frequency of weekly classes, and prior exposure to programming.

How It works

Begin today risk free with 100% money back guarantee on first 3 sessions.

1

Let’s decode your goals

2

Receive personalized learning plan and class schedule

3

Subscribe and pay

4

100% Quality Assurance. If you are not happy, first 3 sessions are on us.

How It works

Begin today, risk free our 3 sessions 100% moneyback guarantee.

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