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About the course

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly becoming popular among today’s organizations. The adoption of AI has entered the mainstream, but in most organizations, it remains in the early stages and is used for developing strategies and for governance. Although these technologies are still emerging, they are delivering practical benefits to help resolve real problems.

Keeping the upcoming demand in mind, EY has launched a comprehensive eLearning program on Artificial Intelligence and Machine Leaning using Python. The program will help you to learn AI and ML algorithms in a step-by-step format. In this course, you will understand Python’s concepts for AI, ML and related concepts like Artificial Neural Network, K Means Theorem, Natural Language Processing, Deep Learning, Naïve Bayes Theorem, etc.

Currently Python’s certification is one of the most sought after programming certifications in the world. There are more than 8.2 million developers who use Python, making it one of the most popular languages for ML and Internet-of-Things (IoT) apps. New-age and tech companies like IBM, Netflix, Google, You-Tube, NASA, Amazon, Instagram and Facebook also use Python for their apps.

Course benefits

  • In-depth learning of AI and ML algorithms through practical examples.
  • May build capability to implement tools built on AI platforms.
  • The course enable you to learn and acquire the required skills in Python at analytics and program development work areas.
  • The course can help you create your own AI and ML solutions.
  • Learn from the experienced professionals and industry experts.

Who should take this course?

  • Working professionals who intend to build their career in the field of analytics.
  • Working professionals who intend to build their career in the field of Machine learning and Artificial Intelligence.
  • Professionals who are currently in the Big Data and Data Science domains.
  • IT-Professionals in scripting and automation industry.
  • Entrepreneurs
  • Fresh graduates and young professionals
  • Mid-level Managers
  • Professionals working with MIS (Management Information System) and operations

Course coverage

  • Artificial Neural Network
  • Unsupervised Learning-K means Clustering Algorithm in Machine Learning
  • KNN methods
  • Naïve Bayes Theorem
  • Deep Learning
  • Principal Component Analytics
  • Random Forest for weather dataset
  • Neural Networks NLP (Natural Language Processing)
  • Reinforcement Learning
For queries, feedback or assistance

Contact EY Virtual Academy Support