Artificial Intelligence and Machine Learning




About Course


Do you want to learn essential Artificial Intelligence concepts like search, optimization, planning, and pattern recognition from top AI experts? AI and Deep learning have shown promising growth in recent years and in the near future can change the way companies operate.


Benefits

  • Trainers with more than a decade of Industry Expertise.
  • Our emphasize is more on practical based learning. 
  • 24X7 support
  • We are associated with 500+ corporates.
  • Standout performers will be projected for placements in these corporates based on requirements.
  • Every session will be recorded and will be available on our LMS (Learning Management System) and students will have life time access to it. 
  • We provide Interview Guidelines to help in better understanding of industry requirements and expectations. 
  • Our trainings are available online and offline mode.
  • We focus and prefer Instructor Led Live training programs.
  • Assessments will there on weekly basis. Pre and post training assessment are included to rate yourself after the learning.
  • Course Completion Certificate will be provided.

Why should I take this course?

Today, the amount of data that is generated, by both humans and machines, far outpaces humans' ability to absorb, interpret, and make complex decisions based on that data. Artificial intelligence forms the basis for all computer learning and is the future of all complex decision making. Moreover, machine learning focuses on the development of computer programs. The primary aim is to allow the computers to learn automatically without human intervention.

How are Machine Learning and Artificial Intelligence different?

Artificial Intelligence is a subfield of Computer Science whereas Machine Learning is a subfield of Artificial Intelligence.

How does a Machine ‘learn’?

At a high-level, algorithms learn by generalising from multiple historical examples, For example: ‘Inputs like this usually come before outputs like that.’ The generalisation, e.g. the learned model, can then be used on new examples in the future to predict what is expected to happen or what the expected output will be.

Where is AI used?

A few examples of where AI is used are, speech recognition, problem-solving, learning and planning.



Highlights