AI Machine Learning

Data Analysis using Python | Game Deployment | Data Science Process

AI Machine Learning

  • Course Content
  • Who will benefit?
  • Project Outcome
  • Duration
  • Prior skills requirement

  • Introduction to data analysis using Python
  • Use of Matplotlib library for graphical representations
  • File handling capabilities
  • Game development using PyGame library
  • Object recognition – objects, animals, objects from videos using OpenCV
  • Speech recognition
  • Handwriting recognition
  • XML file handling protocols
  • JSON file handling
  • Introduction to Data Science and Big Data using ApacheSpark
  • Data Science Process
  • Intro to Machine learning
  • Scikit library and usage
  • Supervised Learning – Classification, Regression models
  • Un-Supervised Learning – Clustering, Dimensionality Reduction models
  • Prediction and forecasting from the ML models
  • High level views on other emerging ML models
  • This course is ideal for any student completing their undergraduate or postgraduate degree who is keen to pursue a career in the growing field of Artificial Intelligence and Machine Learning.

  • Projects in Data science
  • Prediction and Forecasting patterns in weather, stock markets, in recent Covid pandemic,
  • Probability of an event happening
  • Arriving in Real-time decisions
  • Creating customer segmentation, sales forecasting
  • Sentiment Analyser
    • 60 Hours

      Basic Python coding skills or must have completed the ‘Python Primer’ course.

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