Course curriculum

  • 1

    Let's Get Started

    • Students Guide Book

    • Jupyter Note Book Installation Guide
  • 2

    Recorded Sessions

    • Artificial Intelligence Class 1

    • Assignment 1: Python Basics

    • Artificial Intelligence Session 2

    • Data Structure in Python

    • Control Flow and Loops in Python

    • Assignment 2: Practice and FAQ's

    • Artificial Intelligence Live Session 3

    • Artificial Intelligence Live Session 4

    • Artificial Intelligence Live Session 5

    • Practice Statistics Question

    • Artificial Intelligence Live Session 6

    • Artificial Intelligence Live Session 7

    • Artificial Intelligence Live Session 8

    • Artificial Intelligence Live Session 9

    • Reference material : Statistics

    • NUMPY

    • PANDAS

    • Artificial Intelligence Live Session 10

    • Artificial Intelligence Live Session 11

    • EDA Dataset

    • Artificial Intelligence Live Session 12

    • Reference Material: Data Perts - MATPLOTLIB

    • DataPerts - SEABORN

    • DataPerts - EDA

    • Session 1 - Types of Data, Measures of Central & Dispersion_stats

    • Session 2 - Skewness, Kurtosis, Descriptive Stats

    • Artificial Intelligence Live Session 13

    • Artificial Intelligence Live Session 14

    • Artificial Intelligence Live Session 15

    • Artificial Intelligence Live Session 16

    • Artificial Intelligence Live Session 17

    • Artificial Intelligence Live Session 18

    • Artificial Intelligence Live Session 19

    • Artificial Intelligence Session 20
  • 3

    ML & AI DEC 2020

    • ML & AI _Session1_26-12-20

    • ML & AI_Session2_02-01-21

    • ML & AI_Session3_03-01-21

    • ML & AI_Session4_04-01-21

    • ML & AI_Session5_07-01-21

    • ML & AI_Session6_10-01-21

    • ML & AI_Session7_16-01-21

    • ML & AI_Session8_30-01-21

    • ML & AI_Session9_31-01-21

    • ML & AI_Session10_06-02-2021

    • ML & AI_Session11_07-02-2021

    • ML & AI Session12_14-02-2021

    • Ml & AI_Session13_15-02-2021
  • 4

    Major Project

    • Create a Model to predict house prices using Python