Course curriculum

  • 1

    Chapter 1. Introduction Python - Pre - Learning Session

    • 1.1-Python Crash course Introduction

    • 1.2 Python Demo n install

    • 1.3 Python Intro and Installation

    • 1.4 Basic python and datatype

    • 1.5 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

    • 5.2 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 - Machine Learning Models

    • 9.1 Clustering PPT

    • 9.2 Clustering

    • 9.3 Evaluation Metrics

    • 9.4 Logistic Regression - Feature Regression

    • 9.5 Logistic Regression

    • 9.6 Simple Linear regression

    • 9.7 Multiple Linear regression
  • 10

    Microsoft Content-Azure AI Fundamentals (AI-900)

    • 01_Introduction
  • 11

    M01_AzureAIFundamentals

    • M01_Fundamentals

    • M02_AzureAIFundamentals

    • M03_ResponsibleAI

    • M04_ResponsibleAI
  • 12

    M02_Azure ML

    • M02_ML
  • 13

    M03._AzureCV

    • M03_AnalyzeImageswithCV

    • M03_AnalyzeImageswithCV

    • M03_ClassifyImageswithCV

    • M03_ClassifyImageswithCV

    • M03_DetectandAnalyzeFace withFaceservice

    • M03_DetectandAnalyzeFace withFaceservice
  • 14

    M04_AzureNLP

    • 4.1 AzureBot

    • 4.2 Conversational Language Understanding

    • 4.3 NLP

    • 4.4 Recognize and Synthesize Speech 

    • 4.5_Translate Text and Speech
  • 15

    M05_AzureKnowledgeMining

    • 5.1 Knowledge Mining
  • 16

    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
  • 17

    Live Session meeting Links

    • First Live Session- Jul 9, 2022 08:30 PM

    • 2nd Live Session- Jul 13, 2022 08:30 PM

    • 3rd Live Session- Jul 18, 2022 08:30 PM

    • 4th Live Session- Jul 21, 2022 08:30 PM

    • 5th Live Session- Jul 26, 2022 08:30 PM

    • ML- Internship Project - Self Driving Car
  • 18

    Live Session Recordings

    • SESSION-1

    • SESSION-2

    • SESSION-3

    • SESSION-4

    • SESSION-5

    • Internship Project live session recordings
  • 19

    Internship orientation meeting Link

    • Meeting Link- Aug 17, 2022 07:00 PM

    • Orientation Meeting Recordings

  • 20

    Self Driving Car - Internship Project

    • Self Driving Car - 1

    • Self Driving Car - 2
  • 21

    Instructions for Submissions

    • Instructions for Submissions