uCertify

Introduction to Machine Learning and Artificial Intelligence

(DV-SIS180.AW1)
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Skills You’ll Get

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1

What is AI

  • Introduction to Artificial Intelligence
  • Types of AI systems
  • Introduction to Machine Learning
  • Supervised learning
  • Unsupervised learning
  • Reinforcement Learning
  • Bleeding edge AI research
  • Conclusion
  • Further readings
  • Questions
2

Building AI Model to Predict Housing Prices

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
3

Getting Started with No-code AI

  • Introduction to no-code AI
  • History of no-code AI
  • Different types of no-code AI solutions
  • Advantages of no-code AI solutions
  • Conclusion
  • Questions
4

Building AI Model to Perform Sales Forecasting

  • Data selection
  • No-code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
5

Classifying Different Images

  • Data selection
  • No-Code AI tool selection
  • Data labeling
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
6

Building AI Model for Healthcare Information Identification

  • Data selection
  • No-code AI tool selection
  • Exploratory Data Analysis
  • Model selection and training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
7

Building AI Model to Find Fraudulent Claims

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
8

Building AI Model to Create Targeted Customer Offerings

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and Further improvements
  • Conclusion
  • Questions
9

Building AI Model for Video Action Recognition

  • Data selection
  • No-code AI tool selection
  • Exploratory Data Analysis
  • Model selection and training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
10

Building AI Model to Detect Diseases in Plants

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
11

n8n

  • AI Automation Tools
  • AI Automation Tool: n8n
  • AI Automation Case Studies
  • Why Use Agentic AI
  • Choosing a Workflow
  • Advantages of AI Automation: n8n
  • Limitations of n8n
  • Summary
12

Building AI Applications with Coded AI

  • Introduction to Python programming language
  • Popular AI libraries
  • Build AI projects with Python in Google Colab
  • Using pretrained models for AI Applications
  • Using Kaggle for AI and data science challenges
  • Conclusion
  • Questions

1

Building AI Model to Predict Housing Prices

  • Predicting Housing Prices using Amazon SageMaker Canvas
2

Getting Started with No-code AI

  • Adding a Text to an Image Using Runway
3

Classifying Different Images

  • Classifying Images Using Google Teachable Machine
4

Building AI Model to Find Fraudulent Claims

  • Predicting Insurance Fraud in DataRobot Using eXtreme Gradient Boosted Trees Classifier Model
5

Building AI Model to Create Targeted Customer Offerings

  • Predicting Customer Offerings in DataRobot Using the RandomForest Regressor Model
6

Building AI Model to Detect Diseases in Plants

  • Predicting Plant Disease in DataRobot with a Keras Slim Residual Neural Network
7

n8n

  • Using n8n
8

Building AI Applications with Coded AI

  • Implementing Basic Python Programs
  • Implementing Linear Regression with scikit-learn
  • Implementing Linear Regression with TensorFlow
  • Summarizing Text Using Hugging Face in Google Colab

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