The ESOCMS02326: Artificial Intelligence and Machine Learning training course provides a detailed description about the technical and operational aspect of AI and ML and helps the learners to understand the concepts of AI, ML, neural network, reinforcement learning, NLP and artificial ecosystem. It also provides a detailed description about the need of AI ready infrastructure, AI and ML frameworks, implemented machine learning models, and use cases across the industry.

The offering is an engaging mix of key technologies, case examples, and business insights. The course includes recorded lab exercise demonstrations explaining the techniques of machine learning, neural network, reinforcement learning, and infrastructure in detail.

Skills Covered

Upon successful completion of this course, participants should be able to:

  • • Describe the impact and scope of artificial intelligence
  • Describe the concepts of machine learning, deep learning, and neural network
  • Learn about Python and explain the importance of Python in AI and ML
  • Explain AI and ML roles and responsibilities in an organization
  • Describe data preparation and feature engineering
  • Explain the concept and techniques of supervised and unsupervised learning
  • Understand the concepts of deep reinforcement learning, reinforcement learning, neural network, NLP
  • Explore the stages of AI workflow
  • Describe the need of AI Infrastructure and list the considerations of AI Infrastructure
  • Learn about AI and ML frameworks and understand their applications
  • Learn about some industry applications of AI to solve some advanced problems
  • Understand the role of AI in business strategy
  • Explain strategies and steps to manage AI applications
  • Understand and describe the ethical issues, principles, and types of biases of AI

Who Should Attend

This course is intended for data engineers, data scientists, data architects, or anyone else who wants to learn artificial intelligence and machine learning.

Course Curriculum


Recommended: Data Science and Big Data Analytics

Download Syllabus