Programme Overview

Given the current state of advancing technology and its adaption in businesses, it is clear that the next few years will witness far-reaching transformations in every area. Yesteryear’s bleeding edge technologies such as SMAC and Digital are now considered as given. We expect spectacular changes in our lives and in businesses with the advent of IoT, Artificial Intelligence, Machine Learning and Robotics. This programme addresses issues relating to AI/ML and their impact on businesses.

Machine learning being at the core of artificial intelligence we commence with ML concepts and the hands-on practicals. Understanding and solving business problems will be the key here. We will build ML models using various datasets. Having gotten a grip of ML we move into the field of AI to discuss some of the implementations and business impact.

This programme aims at getting first-hand experience in Machine Learning using cloud-based tools as well as desktop tools. The focus will be on understanding concepts and principles. Although the tools are not central to the learning they will aid in this process of clarifying basics. There will be multiple hands-on exercises. Concepts and usability of Machine Learning, Deep Learning in business will be discussed.

Learning Outcomes

By the end of this programme participants will be able to understand:

  • ML concepts and the hands-on practical.
  • Building ML models
  • Exploring solutions for business problems

Pedagogy

A completely hands-on programme offering experiential and immersive learning with a practice focus.

Please note

  • No prior coding knowledge is required; the cloud-based GUI tool will be used for doing exercises.
  • This programme does not include learning any of the languages.
  • Participants need a computer and a reasonable connection to the Internet.
  • Participants will need to download open-source software, as required.

Programme Details

Theme
Topic 1 Artificial Intelligence & Machine Learning
– Concepts
– Relationship between AI & ML
Topic 2 ML Introduction
– Overview – Applied ML
– Terminology
– Processes
– Concept of Model & Algorithm
– Classification, Regression, Clustering
– Tools – Cloud, Orange & Weka
Topic 3 Algorithms
– Introduction
– Concepts
– Types
Topic 4 Evaluation
– Metrics
– Model evaluation
Topic 5 Pre-processing
– Features data transformation
– Features selection, engineering
– Features extraction
Topic 6 Deep Learning
– Neural networks
– Image processing
Topic 7 Orange 3
– Introduction – Panes and help available
– Classification, Regression, Clustering

Fees

INR 24,900 + GST

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