Course curriculum

  • 1

    E- Learning Content

    • Introduction Video
  • 2

    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
  • 3

    Chapter 2. Control flow

    • 2.1 If else conditions

    • 2.2 While & for loop conditions

  • 4

    Chapter 3. Exception Handling

    • 3.1 Exception Handling
  • 5

    Chapter 4. Functions

    • 4.1 Functions
  • 6

    Chapter 5. OOPS

    • 5.1 CLASSES

    • 5.2 OOP
  • 7

    Chapter 6.Deep Learning

    • 6.1 Logistic Regression vs DL

    • 6.2 TesorFlow and Keras
  • 8

    Chapter 7. Libraries

    • 7.1 Introduction to Libraries

    • 7.2 Library Introduction

    • 7.3 Matplolib

    • 7.4 Numpy

    • 7.5 Pandas
  • 9

    Chapter 7. Libraries

    • 8.1 Data

    • 8.2 Linear Algebra

    • 8.3 Statistics

    • 8.4 Stats - Probs
  • 10

    Chapter 9. Intro to Probability & DV

    • 9.1 Introduction to Probability, Statistics & SQL

    • 9.2 Data Visualization with Tableau

    • 9.3 LSTM
  • 11

    Chapter 10. Machine Learning Models

    • 10.1 Clustering

    • 10.2 Evaluation Metrics

    • 10.3 Logistic Regression

    • 10.4 Simple Linear regression

    • 10.5 Multiple Linear regression
  • 12

    Live Session

    • First Live Session- Jun 28, 2022 08:00 PM

    • 2nd Live Session- Jun 29, 2022 08:00 PM

    • 3rd Live Session-Jun 30, 2022 08:00 PM

    • 4th Live Session-Jul 1, 2022 08:00 PM

    • 5th Live Session- Jul 4, 2022 08:00 PM
  • 13

    LIVE SESSIONS RECORDINGS

    • SESSION-1

    • SESSION-2

    • SESSION-3

    • SESSION-4

    • SESSION-5
  • 14

    Major Project

    • Major Project