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Advance Certification in Machine Learning

Machine learning (ML) is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output while updating outputs as new data becomes available. The processes involved in machine learning are similar to that of data mining and predictive modeling. Both require searching through data to look for patterns and adjusting program actions accordingly. Many people are familiar with machine learning from shopping on the internet and being served ads related to their purchase. This happens because recommendation engines use machine learning to personalize online ad delivery in almost real time. Beyond personalized marketing, other common machine learning use cases include fraud detection, spam filtering, network security threat detection, predictive maintenance and building news feeds.

Certified by AICRA

Industry Oriented Curriculum

Real Time Projects

Designed by Industry Experts
Course Module
    Semester 1
  •  Introduction to AI
  •  Python
  •  Numpy
  •  Pandas
  •  Matplotlib and Seaborn
    Semester 2
  •  Machine Learning
  •  Supervised Learning Algorithms
  •  Unsupervised Learning      Algorithms
  •  Introduction to Deep learning
  •  Artificial Neural Network
  •  Convolutional Neural Network

No product is made today, no person moves today, nothing is collected, analysed or communicated without some “digital technology” being an integral part of it. That, in itself, speaks to the overwhelming ‘value’ of digital technology.

Louis Rossetto