Course curriculum

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    Let's get started here..!

    • Curriculum:- Artificial Intelligence
  • 2

    Module 1

    • Assignment 1: Python Basics

    • Artificial Intelligence Live Class 1
  • 3

    Module 2

    • Data Structure in Python

    • Control Flow and Loops in Python

    • Assignment 2: Practice and FAQ's

    • Artificial Intelligence Live Session 2

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    Module 3

    • Artificial Intelligence Live Session 3

  • 5

    Module 4

    • Artificial Intelligence Live Session 4
  • 6

    Module 5

    • Artificial Intelligence Live Session 5

    • Practice Statistics Question
  • 7

    Module 6

    • Artificial Intelligence Live Session 6

  • 8

    Module 7

    • Artificial Intelligence Live Session 7

  • 9

    Module 8

    • Artificial Intelligence Live Session 8

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    Module 9

    • Artificial Intelligence Live Session 9
  • 11

    Important Reading Material

    • Statistics

    • NUMPY

    • PANDAS
  • 12

    Module 10

    • Artificial Intelligence Live Session 10
  • 13

    Module 11

    • Artificial Intelligence Live Session 11

    • EDA Dataset
  • 14

    Module 12

    • Artificial Intelligence Live Session 12
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    Reference Material

    • DataPerts - MATPLOTLIB

    • DataPerts - SEABORN

    • DataPerts - EDA

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

    • Session 2 - Skewness, Kurtosis, Descriptive Stats
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    Module 13

    • Artificial Intelligence Live Session 13
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    Module 14

    • Artificial Intelligence Live Session 14
  • 18

    Module 15

    • Artificial Intelligence Live Session 15
  • 19

    Module 16

    • Artificial Intelligence Live Session 16
  • 20

    Module 17

    • Artificial Intelligence Live Session 17
  • 21

    Module 18

    • Artificial Intelligence Live Session 18
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    Module 19

    • Artificial Intelligence Live Session 19
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    Module 20

    • Artificial Intelligence Live Session 20
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    Module 21

    • Artificial Intelligence Live Session 21
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    Module 22

    • Artificial Intelligence Live Session 22
  • 26

    Module 23

    • Artificial Intelligence Live Session 23
  • 27

    Module 24

    • Artificial Intelligence Live Session 24
  • 28

    Module 25

    • Artificial Intelligence Live Session 25
  • 29

    Module 26

    • Artificial Intelligence Live Session 26
  • 30

    Module 27

    • Artificial Intelligence Live Session 27
  • 31

    Module 28

    • Artificial Intelligence Live Session 28
  • 32

    Module 29

    • Artificial Intelligence Live Session 29
  • 33

    Module 30

    • Artificial Intelligence Live Session 30
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    VERY IMPORTANT Instructions for Project Submission

    • Submission Deadline and Instructions

    • IMPORTANT NOTICE
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    Project Statement

    • Sonar.csv

    • Keras

    • tensorflow_v_2.0

    • Tensorflow

    • ANN.ipynb

    • Sonar.ipynb

    • TensorflowBasics.ipynb

    • Tensorflow_Basics

    • Variables and placeholders
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    AI_MinProj- SPC'20

    • PROJECT TITLE - TITANIC_EDA_DATASET

    • Titanic Dataset

    • Fruits

    • SLR_AdSpendVsSales

    • Multiple LR_Advertising_2_CategoricalVariables

    • Problem Statement

    • InMovidu+DataPerts - SLR - AdSpendVsSales

    • Multiple LR_Advertising_Categorical

    • Logistic Regression

    • Subscription

    • KNN Classification_1 - IRIS

    • KNN Classification - Fruits
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    Important Material

    • 01 - Decision Tree Basics.html

    • 03- Decision Tree - Diabetes (1).html

    • 01 - Random Forest - Introduction.html

    • 02 - Random Forest Classification - Social Network Ads.html

    • 01 - Clustering - Introduction.html

    • KMeans_Case Study1_CreditCard.html

    • KMeans_Case Study2_Seeds.html

    • Hierarchical_Case Study1_CreditCard.html

    • Hierarchical_Case Study2_seeds.html

    • Diabetes.csv

    • Social Network Ads

    • creditcard.csv

    • seeds.csv
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    Face Mask Project

    • Face Mask Project
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    PPT Link

    • Class PPT Link