Online certifications to grow your career in data science
HyperSense AI Certification Program

Showcase your expertise in machine learning and HyperSense AI by completing online certification programs.

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COURSE 1 – AI 101

Beginners Program

Purpose of the program: To enable non-technical users to design, build and deploy AI/ML models using Subex HyperSense AI by providing an in-depth understanding of fundamentals of Data Science and AI/ML Model Building on a “NO-Code” tool like HyperSense AI.
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Eligibility: Ideal for Beginners

Benefits of the program:

  1. Helps non-technical users become citizen data scientists (data scientists who can build statistical or machine learning models without a need for coding)
  2. Gain understanding of AI/ML application in business context
  3. Implement AI/ML models with business functions and drive value
  4. Work with other data scientists to drive large scale implementation
Introduction to DS and Elements in DS Duration: 45 minutes
  • Introduction to AI/ML
  • EDA
    • Statistical Analysis
    • Visual Analytics
  • Predictive modeling overview
Building your first ML model on HyperSense AI Duration: 60 Minutes
  • Data Science Workflow
  • Data Preparation
  • EDA and feature synthesis
  • Feature selection
  • Model Training – Algorithm selection, Hyperparameter tuning, Evaluation
  • Model Evaluation
Hands-on Lab on HyperSense HyperSense AI Duration: 40 Minutes
  • Build first regression model (Demand forecasting using regression)
  • Build first classification model (Churn Prediction)
COURSE 2 – AI 101

Expert Program

Purpose of the program: To enable ‘Citizen Data Scientist’ to build robust AI/ML models leveraging advanced data science capabilities of HyperSense AI by providing an in-depth understanding of machine learning processes, techniques, and hyper parameterization.
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Eligibility: Ideal for those complete Beginner’s course

Benefits of the program:

  1. Helps data savvy users such as data analyst, business analyst and citizen data scientist build custom AI/ML models
  2. Improve performance of existing AI/ML models
  3. Accelerate impact and value of AI/ML within business functions
  4. Collaborate with data scientists and engineers for large scale AI/ML implementation driving higher adoptionIdeal for those complete Beginner’s course
Introduction to common machine learning technique Duration: 1.5 Hours
  • Common Predictive Modeling Techniques
  • How do the algorithms learn from data?
  • How to evaluate the ML model?
Hands-on Lab on AI Studio Duration: 30 Hours
  • Build custom predictive models in AI Studio
Advanced Machine Learning Duration: 1 Hour
  • How can I improve my model?
  • What is AUTO CASH?
  • Can you explain why the model does what it does?
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