Advance ML/AI Program Overview

This course has been designed by a professional having 28+ years overall experience in IT industry, with hands on practical experiences experienced first-hand. This will help the audience to learn complex theory, algorithms and coding libraries in a simple way.

This course introduces several fundamental concepts and methods for machine learning. The objective is to familiarize the audience with some basic learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.

Learning Outcomes

  • Have a great understanding of many Machine Learning models
  • Make accurate predictions
  • Make powerful analysis
  • Make robust Machine Learning models
  • To provide a broad survey of approaches and techniques in machine learning;
  • To develop a deeper understanding of several major topics in machine learning;
  • To develop the design and programming skills that will help you to build intelligent, adaptive artefacts;
  • To develop the basic skills necessary to pursue research in machine learning.

Assignments

  • Submit assignments at the end of each module and know how to apply the concepts to new problems, master the basics and develop intelligent applications
  • Assess your progress with grade/score of each assignment that contributes to the overall grade
  • Projects & Quizzes

                              

 

Capstone Project

Every machine learning project begins by understanding what the data and drawing the objectives. While applying machine learning algorithms to your data set, you are understanding, building and analysing the data as to get the end result.

Following are the steps involved in creating a well-defined ML project:

  1. Understand and define the problem
  2. Analyse and prepare the data
  3. Apply the algorithms
  4. Reduce the errors
  5. Predict the result
  6. Evaluation
  7. Assignments and quizzes

 

Evaluation

Class performance will be based on following components:

  • Module-based Assignments
  • Quizzes

Post Training Assistance

  • Enhance your aspirations with assistance from our trainers’ partners and network.
  • Free Online/On call support for 3 months after the course