Course curriculum

  • 1

    Chapter 1. Introduction Python - Pre - Learning Session

    • 1.1 Python Intro and Installation

    • 1.2 Basic python and datatype

    • 1.3 Basic,Number,string

    • 1.6 Data types
  • 2

    Chapter 2. Control flow

    • 2.1 If else conditions

    • 2.2 While & for loop conditions

  • 3

    Chapter 3. Exception Handling

    • 3.1 Exception Handling
  • 4

    Chapter 4. Functions

    • 4.1 Functions
  • 5

    Chapter 5. OOPS

    • 5.1 CLASSES

    • .2 OOP
  • 6

    Chapter 6.Deep Learning

    • 6.1 Logistic Regression vs DL

    • 6.2 TesorFlow and Keras
  • 7

    Chapter 7. Libraries

    • 7.1 Introduction to Libraries

    • 7.2 Library Introduction

    • 7.3 Matplolib

    • 7.4 Numpy

    • 7.5 Pandas
  • 8

    Chapter 8 . Mathematics

    • 8.1 Data

    • 8.2 Linear Algebra

    • 8.3 Statistics

    • 8.4 Stats - Probs
  • 9

    Chapter 9. Intro to Probability & DV

    • 9.1 Introduction to Probability, Statistics & SQL

    • 9.2 Data Visualization with Tableau

    • 9.3 LSTM
  • 10

    Chapter 10. Machine Learning Models

    • 10.1 Clustering

    • 10.1 Clustering PPT

    • 10.2 Evaluation Metrics

    • 10.3 Logistic Regression - Feature Regression

    • 10.3 Logistic Regression

    • 10.4 Simple Linear regression

    • 10.5 Multiple Linear regression
  • 11

    Microsoft Content-Azure AI Fundamentals (AI-900)

    • 01_Introduction
  • 12

    M01_Azure AI Fundamentals

    • M01_Fundamentals

    • M01_Azure AI Fundamentals

    • M01_Responsible AI

    • M01_Responsible AI
  • 13

    M02_Azure ML

    • M02_ML
  • 14

    M03_AzureCV

    • M03_Analyze Images with CV

    • M03_Analyze Images with CV

    • M03_Classify Images with CV

    • M03_Detectand Analyze Face with Face service

    • M03_Detect and Analyze Face with Face service
  • 15

    M04_AzureNLP

    • 4.1 Azure Bot

    • 4.2 Conversational Language Understanding

    • 4.3 Numpy Arrays

    • 4.4 Numpy Array Attributes

    • 4.5 Numpy Math
  • 16

    M05_AzureKnowledgeMining

    • 5.1 Knowledge Mining
  • 17

    Extra Content for AI 900

    • 1 Artificial Intelligence Workloads and Considerations

    • 2- Fundamental Principles of Machine Learning on Azure

    • 3. Features of Computer Vision Workloads on Azure

    • 4.Features of Natural Language Processing (NLP) Workloads

    • 5.Features of Conversational AI Workloads on Azure
  • 18

    LIVE SESSIONS LINKS

    • First Live Session- Aug 10, 2022 07:00 PM

    • 2nd Live Session- Aug 11, 2022 07:00 PM

    • 3rd Live Session-Aug 12, 2022 06:00 PM

    • 4th Live Session- Aug 13, 2022 07:00 PM

    • 5th Live Session- Aug 15, 2022 07:00 PM

    • Internship orientation meeting

    • DS -Internship Project - ChatBot
  • 19

    Live Sessions Recordings

    • SESSION-1

    • SESSION-2

    • SESSION-3

    • SESSION-4

    • SESSION-5

    • Internship Orientation Meeting Recordings

    • Chatbot- Part-1

    • Chatbot-Part-2
  • 20

    ChatBot - Internship Project

    • ChatBot with DialogFlow - Theory

    • ChatBot with DialogFlow - Code

    • ChatBot - Code

    • Test.qa

    • Train.qa
  • 21

    Internship Project Submissions

    • Internship Project Submisions