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AI & MACHINE LEARNING INTRODUCTION

6 modules

English

Lifetime access

<p>This 10&nbsp;week,&nbsp;40 hour program (3 - 6 hours per week) exposes students &nbsp;( <strong><em>cohorts for grade 10th upwards school students and&nbsp;undergraduate / postgraduate students</em></strong>&nbsp;)&nbsp; to fundamentals of <strong><em>Statistics, Python, AI and Machine Learning</em></strong> concepts. A course completion and internship&nbsp;certificate (meeting requirements)&nbsp;is available to all participants.&nbsp; The program is run online and prior coding experience is not mandatory.&nbsp;</p> <p><a href="/s/courses/62050bc50cf2dbac177f6e38/images/AI for Students Latest.pdf" target="_blank"><strong>Download Brochure</strong></a></p> <p><strong>Batches Starting : Coming Soon</strong></p> <p><strong>Duration :</strong>&nbsp;10&nbsp;weeks ( 3 - 6 hours weekly )</p>

Overview

This 10 week, 40 hour program (3 - 6 hours per week) exposes students ( separate cohorts for grade 10th upwards school students and undergraduate students ) to fundamentals of AI and Machine Learning concepts, and guides them to a capstone project. The program is run online. No prior coding experience is mandatory, however exposure will be helpful. Cohorts will be formed as per programming experience to facilitate equal learning and fast track for advanced learners.

A certification of completion will be made available on successful completion of the course to all participants. This program opens up opportunities for internships and for research based projects for profile building & college admission applications.  

Coverge of the program includes the following 

Module 1

Unit 1: Introduction to AI & Data Science 

Unit 2: Statistics Overview 

Unit 3: Probability theory 

Unit 4: Research Methodology

Module 2

Unit 5: Introduction to Python 

Unit 6: Data types, operations and variables

Unit 7: Conditions, functions & Loops 

Unit 8: Lists, Strings, Tuples and Dictionaries

Module 3

Unit 9: Introduction to Machine Learning

Unit 10: Hands on Case Study with Regression 

Unit 11: Hands on Case Study with Classification

Unit 12: Introduction to Neural Networks & Deep Learning

Module 4

Unit 13: Introduction to Natural Language Processing

Unit 14: Bag of Words Models

Unit 15: Embedding based Models

Unit 16: Implementing a Recommender System

Module 5

Unit 17: Introduction to Computer Vision

Unit 18: Convolutional Neural Networks 

Unit 19: Hands on for Computer Vision

Unit 20: Latest Developments in AI (Open AI, GPT etc.)

Module 6 

Capstone Project

An optional virtual internship certification can be received by sucessfully completing the CAPSTONE project requirements.

Why you should take this course?

  • Build towards a career path in the AI & Data Science field.
  • Make your study abroad application stronger
  • Builds towards an internship or a research project 
  • Introduces to the subject and builds the base for advanced exploration

Most importantly helps explore and build the essential skills for emerging careers like Data Science, AI,  Business Analytics , Actuarists, Algo trading, Health Analytics  etc.

Download Brochure

Modules

Module 1: The Basics Of Data Science

4 attachments

Unit 1: Introduction to AI & Data Science

Unit 2: Statistics Overview

Unit 3: Probability theory

Unit 4: Research Methodology

Module 2: Getting Started With Python

4 attachments

Unit 5: Introduction to Python

Unit 6: Data types, operations and variables

Unit 7: Conditions, functions & Loops

Unit 8: Lists, Strings, Tuples and Dictionaries

Module 3: Machine Learning Overview

4 attachments

Unit 9: Introduction to Machine Learning

Unit 10: Hands on Case Study with Regression

Unit 11: Hands on Case Study with Classification

Unit 12: Introduction to Neural Networks & Deep Learning

Module 4: Natural Language Processing

4 attachments

Unit 13: Introduction to Natural Language Processing

Unit 14: Bag of Words Models

Unit 15: Embedding based Models

Unit 16: Implementing a Recommendation System

Module 5: Computer Vision & The Frontiers of AI

4 attachments

Unit 17: Introduction to Computer Vision

Unit 18: Convolutional Neural Networks

Unit 19: Hands on for Computer Vision

Unit 20: Latest Developments in AI (Open AI, GPT etc.)

Module 6 : Capstone Project

1 attachment

Submission Requirements

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